1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
|
<!-- Copyright (c) 2020 ARM Limited. -->
<!-- -->
<!-- SPDX-License-Identifier: MIT -->
<!-- -->
<!-- HTML header for doxygen 1.8.13-->
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
<meta http-equiv="X-UA-Compatible" content="IE=9"/>
<meta name="generator" content="Doxygen 1.8.17"/>
<meta name="robots" content="NOINDEX, NOFOLLOW" />
<meta name="viewport" content="width=device-width, initial-scale=1"/>
<title>ArmNN: src/armnn/Tensor.cpp Source File</title>
<link href="tabs.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<link href="navtree.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="resize.js"></script>
<script type="text/javascript" src="navtreedata.js"></script>
<script type="text/javascript" src="navtree.js"></script>
<link href="search/search.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="search/searchdata.js"></script>
<script type="text/javascript" src="search/search.js"></script>
<script type="text/x-mathjax-config">
MathJax.Hub.Config({
extensions: ["tex2jax.js"],
jax: ["input/TeX","output/HTML-CSS"],
});
</script>
<script type="text/javascript" async="async" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script>
<link href="doxygen.css" rel="stylesheet" type="text/css" />
<link href="stylesheet.css" rel="stylesheet" type="text/css"/>
</head>
<body>
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
<div id="titlearea">
<table cellspacing="0" cellpadding="0">
<tbody>
<tr style="height: 56px;">
<img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/>
<td style="padding-left: 0.5em;">
<div id="projectname">
 <span id="projectnumber">23.05</span>
</div>
</td>
</tr>
</tbody>
</table>
</div>
<!-- end header part -->
<!-- Generated by Doxygen 1.8.17 -->
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&dn=gpl-2.0.txt GPL-v2 */
var searchBox = new SearchBox("searchBox", "search",false,'Search');
/* @license-end */
</script>
<script type="text/javascript" src="menudata.js"></script>
<script type="text/javascript" src="menu.js"></script>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&dn=gpl-2.0.txt GPL-v2 */
$(function() {
initMenu('',true,false,'search.php','Search');
$(document).ready(function() { init_search(); });
});
/* @license-end */</script>
<div id="main-nav"></div>
</div><!-- top -->
<div id="side-nav" class="ui-resizable side-nav-resizable">
<div id="nav-tree">
<div id="nav-tree-contents">
<div id="nav-sync" class="sync"></div>
</div>
</div>
<div id="splitbar" style="-moz-user-select:none;"
class="ui-resizable-handle">
</div>
</div>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&dn=gpl-2.0.txt GPL-v2 */
$(document).ready(function(){initNavTree('_tensor_8cpp_source.xhtml',''); initResizable(); });
/* @license-end */
</script>
<div id="doc-content">
<!-- window showing the filter options -->
<div id="MSearchSelectWindow"
onmouseover="return searchBox.OnSearchSelectShow()"
onmouseout="return searchBox.OnSearchSelectHide()"
onkeydown="return searchBox.OnSearchSelectKey(event)">
</div>
<!-- iframe showing the search results (closed by default) -->
<div id="MSearchResultsWindow">
<iframe src="javascript:void(0)" frameborder="0"
name="MSearchResults" id="MSearchResults">
</iframe>
</div>
<div class="header">
<div class="headertitle">
<div class="title">Tensor.cpp</div> </div>
</div><!--header-->
<div class="contents">
<a href="_tensor_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>  </div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_tensor_8hpp.xhtml">armnn/Tensor.hpp</a>"</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_utils_8hpp.xhtml">armnn/Utils.hpp</a>"</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_exceptions_8hpp.xhtml">armnn/Exceptions.hpp</a>"</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_types_utils_8hpp.xhtml">armnn/TypesUtils.hpp</a>"</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>  </div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_assert_8hpp.xhtml">armnn/utility/Assert.hpp</a>></span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_numeric_cast_8hpp.xhtml">armnn/utility/NumericCast.hpp</a>></span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>  </div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <iostream></span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>  </div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <sstream></span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  </div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> {</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  </div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment">// ---</span></div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment">// --- TensorShape</span></div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment">// ---</span></div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  </div>
<div class="line"><a name="l00025"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c"> 25</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>()</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  : m_NumDimensions(0), m_Dimensionality(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a>::<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Specified</a>)</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> {</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> }</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  </div>
<div class="line"><a name="l00030"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a18cd85c032ed1d07bf07867e50ed143f"> 30</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keywordtype">bool</span> initDimensionsSpecificity)</div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  : m_NumDimensions(numDimensions), m_Dimensionality(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a>::<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Specified</a>)</div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> {</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  CheckValidNumDimensions(numDimensions);</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  </div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  std::fill(m_Dimensions.begin(), m_Dimensions.begin() + m_NumDimensions, 0);</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  std::fill(m_DimensionsSpecificity.begin(), m_DimensionsSpecificity.begin() + m_NumDimensions,</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  initDimensionsSpecificity);</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> }</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  </div>
<div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a1c3de06b2e467f9663079dbb619e4732"> 40</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(<span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* <span class="keyword">const</span> dimensionSizes)</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  : m_NumDimensions(numDimensions), m_Dimensionality(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a>::<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Specified</a>)</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> {</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  CheckValidNumDimensions(numDimensions);</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  </div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">if</span> (dimensionSizes == <span class="keyword">nullptr</span>)</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  {</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Tensor dimensionSizes must not be NULL"</span>);</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  }</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  </div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  std::copy(dimensionSizes, dimensionSizes + numDimensions, m_Dimensions.begin());</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  std::fill(m_DimensionsSpecificity.begin(), m_DimensionsSpecificity.begin() + m_NumDimensions, <span class="keyword">true</span>);</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> }</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  </div>
<div class="line"><a name="l00054"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#ab18f5c64d49bbc1f7a97d031c5e79e3d"> 54</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(std::initializer_list<unsigned int> dimensionSizeList)</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(<a class="code" href="namespacearmnn.xhtml">armnn</a>::<a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">numeric_cast</a><unsigned int>(dimensionSizeList.size()), dimensionSizeList.begin())</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> {</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> }</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  </div>
<div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#aa3f87e5fa5e657a8d1b792b7c43cffe3"> 59</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* <span class="keyword">const</span> dimensionSizes,</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span>* <span class="keyword">const</span> dimensionsSpecificity)</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  : m_NumDimensions(numDimensions), m_Dimensionality(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a>::<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Specified</a>)</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span> {</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  CheckValidNumDimensions(numDimensions);</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  </div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordflow">if</span> (dimensionSizes == <span class="keyword">nullptr</span>)</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  {</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Tensor dimensionSizes must not be NULL"</span>);</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  }</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  </div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordflow">if</span> (dimensionsSpecificity == <span class="keyword">nullptr</span>)</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  {</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Tensor dimensionsSpecificity must not be NULL"</span>);</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  }</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  </div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  std::copy(dimensionSizes, dimensionSizes + numDimensions, m_Dimensions.begin());</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  std::copy(dimensionsSpecificity, dimensionsSpecificity + numDimensions, m_DimensionsSpecificity.begin());</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span> }</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  </div>
<div class="line"><a name="l00080"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a6624ad2ddc20bd7e3be162e0abea38fe"> 80</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(std::initializer_list<unsigned int> dimensionSizeList,</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  std::initializer_list<bool> dimensionsSpecificityList)</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span> {</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keyword">auto</span> numDimensions = <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(dimensionSizeList.size());</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordflow">if</span> (dimensionsSpecificityList.size() != numDimensions)</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  {</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Tensors dimensionSizeList and dimensionsSpecificityList must be same size"</span>);</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  }</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  </div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  *<span class="keyword">this</span> = <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape</a>(numDimensions, dimensionSizeList.begin(), dimensionsSpecificityList.begin());</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span> }</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  </div>
<div class="line"><a name="l00092"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a81652660972380dfe493bf8572e68e39"> 92</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">Dimensionality</a> dimensionality)</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span> : m_Dimensionality(dimensionality)</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span> {</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordflow">switch</span> (dimensionality)</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  {</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Dimensionality::Specified</a>:</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Use other constructor to specify the rest of the values, this one is only "</span></div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="stringliteral">"for tensors that have an unknown number of dimensions or that are scalar"</span>);</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">Dimensionality::NotSpecified</a>:</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  m_NumDimensions = 0;</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  m_Dimensions = {0};</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  m_DimensionsSpecificity = {<span class="keyword">false</span>};</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">Dimensionality::Scalar</a>:</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  m_NumDimensions = 1;</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  m_Dimensions = {1};</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  m_DimensionsSpecificity = {<span class="keyword">true</span>};</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Invalid Dimensionality value"</span>);</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  }</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> }</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  </div>
<div class="line"><a name="l00116"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#abe2c91b98905750c515790c88f329670"> 116</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">TensorShape::TensorShape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other)</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  : m_NumDimensions(other.m_NumDimensions), m_Dimensionality(other.m_Dimensionality)</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span> {</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  std::copy(other.m_Dimensions.cbegin(), other.m_Dimensions.cbegin() + other.m_NumDimensions, m_Dimensions.begin());</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  std::copy(other.m_DimensionsSpecificity.cbegin(), other.m_DimensionsSpecificity.cbegin() + other.m_NumDimensions,</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  m_DimensionsSpecificity.begin());</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span> }</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  </div>
<div class="line"><a name="l00124"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31"> 124</a></span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">TensorShape::operator =</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other)</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span> {</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  m_NumDimensions = other.m_NumDimensions;</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  m_Dimensionality = other.m_Dimensionality;</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  std::copy(other.m_Dimensions.cbegin(), other.m_Dimensions.cbegin() + other.m_NumDimensions, m_Dimensions.begin());</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  std::copy(other.m_DimensionsSpecificity.cbegin(), other.m_DimensionsSpecificity.cbegin() + other.m_NumDimensions,</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  m_DimensionsSpecificity.begin());</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span> }</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  </div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="comment">// read</span></div>
<div class="line"><a name="l00135"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52"> 135</a></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">TensorShape::operator[]</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  CheckUnspecifiedNumDimensions();</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  CheckDimensionIndex(i);</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  CheckDimensionSpecified(i);</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  </div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keywordflow">return</span> m_Dimensions.at(i);</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span> }</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  </div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="comment">// read and write</span></div>
<div class="line"><a name="l00145"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a0bd5fcf80a3838d0922354989762d7c8"> 145</a></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>& <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">TensorShape::operator[]</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span> {</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">Dimensionality::Scalar</a> == m_Dimensionality)</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  {</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  std::stringstream errorMessage;</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  errorMessage << <span class="stringliteral">"TensorShape with Dimensionality::Scalar must be const to use operator[]"</span>;</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(errorMessage.str(), <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  }</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  CheckUnspecifiedNumDimensions();</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  CheckDimensionIndex(i);</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  CheckDimensionSpecified(i);</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  </div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keywordflow">return</span> m_Dimensions.at(i);</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span> }</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  </div>
<div class="line"><a name="l00160"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff"> 160</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">TensorShape::operator==</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other)<span class="keyword"> const</span></div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keywordflow">return</span> ((m_NumDimensions == other.m_NumDimensions) &&</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  (m_Dimensionality == other.m_Dimensionality) &&</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  std::equal(m_Dimensions.cbegin(), m_Dimensions.cbegin() + m_NumDimensions, other.m_Dimensions.cbegin()) &&</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  std::equal(m_DimensionsSpecificity.cbegin(), m_DimensionsSpecificity.cbegin() + m_NumDimensions,</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  other.m_DimensionsSpecificity.cbegin()));</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span> }</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  </div>
<div class="line"><a name="l00169"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349"> 169</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">TensorShape::operator!=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& other)<span class="keyword"> const</span></div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordflow">return</span> !(*<span class="keyword">this</span> == other);</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span> }</div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  </div>
<div class="line"><a name="l00174"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24"> 174</a></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">TensorShape::GetNumDimensions</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  CheckUnspecifiedNumDimensions();</div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  </div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordflow">return</span> m_NumDimensions;</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span> }</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  </div>
<div class="line"><a name="l00181"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7"> 181</a></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">TensorShape::GetNumElements</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  CheckUnspecifiedNumDimensions();</div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  </div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordflow">if</span> (m_NumDimensions == 0)</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  {</div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  }</div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  </div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> count = 1;</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keywordtype">bool</span> atLeastOneDimensionSpecified = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < m_NumDimensions; ++i)</div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  {</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordflow">if</span> (m_DimensionsSpecificity[i])</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  {</div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  atLeastOneDimensionSpecified = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  count *= m_Dimensions[i];</div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  }</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  }</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  </div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keywordflow">if</span> (atLeastOneDimensionSpecified)</div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  {</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordflow">return</span> count;</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  } </div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordflow">else</span> </div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  {</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  }</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span> }</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  </div>
<div class="line"><a name="l00211"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a3919600d4aa8d5cd801a0e0740f62308"> 211</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a3919600d4aa8d5cd801a0e0740f62308">TensorShape:: GetDimensionSpecificity</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  CheckUnspecifiedNumDimensions();</div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  CheckDimensionIndex(i);</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  </div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordflow">return</span> m_DimensionsSpecificity[i];</div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span> }</div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  </div>
<div class="line"><a name="l00219"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a82c7d5a6e675b1a876daa9983cd125d2"> 219</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a82c7d5a6e675b1a876daa9983cd125d2">TensorShape::SetNumDimensions</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions, <span class="keywordtype">bool</span> initDimensionsSpecificity)</div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span> {</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  CheckScalar();</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  CheckSpecifiedNumDimensions();</div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  CheckValidNumDimensions(numDimensions);</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  </div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  m_NumDimensions = numDimensions;</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  m_Dimensionality = <a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Dimensionality::Specified</a>;</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  std::fill(m_Dimensions.begin(), m_Dimensions.begin() + m_NumDimensions, 0);</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  std::fill(m_DimensionsSpecificity.begin(), m_DimensionsSpecificity.begin() + m_NumDimensions,</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  initDimensionsSpecificity);</div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span> }</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  </div>
<div class="line"><a name="l00232"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#ad82b782a8e1a05b6a3756e73c66d5f90"> 232</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#ad82b782a8e1a05b6a3756e73c66d5f90">TensorShape::SetDimensionSize</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimensionSize)</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span> {</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  CheckScalar();</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  CheckDimensionIndex(i);</div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  </div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  m_Dimensions[i] = dimensionSize;</div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  m_DimensionsSpecificity[i] = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span> }</div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  </div>
<div class="line"><a name="l00241"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#acccb75bd1d68a81f6ddd61687f51c5a1"> 241</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#acccb75bd1d68a81f6ddd61687f51c5a1">TensorShape::AreAllDimensionsSpecified</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  CheckUnspecifiedNumDimensions();</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  </div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <span class="keywordtype">bool</span> areAllDimensionsSpecified = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < m_NumDimensions; ++i)</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  {</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="keywordflow">if</span> (!m_DimensionsSpecificity[i])</div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  {</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  areAllDimensionsSpecified = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  }</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  }</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keywordflow">return</span> areAllDimensionsSpecified;</div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span> }</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  </div>
<div class="line"><a name="l00257"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_shape.xhtml#a34e12ab75d9073354565c2039f92112b"> 257</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a34e12ab75d9073354565c2039f92112b">TensorShape::IsAtLeastOneDimensionSpecified</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  CheckUnspecifiedNumDimensions();</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  </div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keywordtype">bool</span> isAtLeastOneDimensionSpecified = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < m_NumDimensions; ++i)</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  {</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">if</span> (m_DimensionsSpecificity[i])</div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  {</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  isAtLeastOneDimensionSpecified = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  }</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  }</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="keywordflow">return</span> isAtLeastOneDimensionSpecified;</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span> }</div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  </div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span> <span class="keywordtype">void</span> TensorShape::CheckDimensionIndex(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keywordflow">if</span> (i >= m_NumDimensions)</div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  {</div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  std::stringstream errorMessage;</div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  errorMessage << <span class="stringliteral">"Invalid dimension index: "</span> << i << <span class="stringliteral">" (number of dimensions is "</span> << m_NumDimensions << <span class="stringliteral">")"</span>;</div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(errorMessage.str(), <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  }</div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span> }</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  </div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span> <span class="keywordtype">void</span> TensorShape::CheckValidNumDimensions(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions)</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span> {</div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keywordflow">if</span> (numDimensions < 1)</div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  {</div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"Tensor numDimensions must be greater than 0"</span>, <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  }</div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  </div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="keywordflow">if</span> (numDimensions > <a class="code" href="namespacearmnn.xhtml#abdcd184ed3bd648bb31d385040cafd5d">MaxNumOfTensorDimensions</a>)</div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  {</div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keywordflow">throw</span> InvalidArgumentException(<span class="stringliteral">"Tensor numDimensions must be less than or equal to MaxNumOfTensorDimensions"</span></div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  , <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  }</div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span> }</div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  </div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span> <span class="keywordtype">void</span> TensorShape::CheckDimensionSpecified(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordflow">if</span> (!m_DimensionsSpecificity[i])</div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  {</div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  std::stringstream errorMessage;</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  errorMessage << <span class="stringliteral">"Dimension index: "</span> << i << <span class="stringliteral">" not specified. Tensor shape not inferred yet."</span>;</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordflow">throw</span> InvalidArgumentException(errorMessage.str(), <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  }</div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span> }</div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  </div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="keywordtype">void</span> TensorShape::CheckScalar()<span class="keyword"> const</span></div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">Dimensionality::Scalar</a> == m_Dimensionality)</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  {</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  std::stringstream errorMessage;</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  errorMessage << <span class="stringliteral">"Invalid action on a tensor shape that holds a scalar value."</span>;</div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keywordflow">throw</span> InvalidArgumentException(errorMessage.str(), <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  }</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span> }</div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  </div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span> <span class="keywordtype">void</span> TensorShape::CheckUnspecifiedNumDimensions()<span class="keyword"> const</span></div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">Dimensionality::NotSpecified</a> == m_Dimensionality)</div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  {</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  std::stringstream errorMessage;</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  errorMessage << <span class="stringliteral">"Invalid action on a tensor shape that has unknown number of dimensions."</span>;</div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keywordflow">throw</span> InvalidArgumentException(errorMessage.str(), <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  }</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span> }</div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  </div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span> <span class="keywordtype">void</span> TensorShape::CheckSpecifiedNumDimensions()<span class="keyword"> const</span></div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">Dimensionality::Specified</a> == m_Dimensionality)</div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  {</div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  std::stringstream errorMessage;</div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  errorMessage << <span class="stringliteral">"Invalid action on a tensor shape that has known number of dimensions."</span>;</div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordflow">throw</span> InvalidArgumentException(errorMessage.str(), <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  }</div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span> }</div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  </div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span> <span class="comment">// ---</span></div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span> <span class="comment">// --- TensorInfo</span></div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span> <span class="comment">// ---</span></div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  </div>
<div class="line"><a name="l00341"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c"> 341</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::TensorInfo</a>()</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span> : m_DataType(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>::<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">Float32</a>), m_IsConstant(false)</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span> {</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span> }</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  </div>
<div class="line"><a name="l00346"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#adf2180cf334a3a58c122d45e7bea567d"> 346</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& shape,</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordtype">float</span> quantizationScale,</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  int32_t quantizationOffset,</div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordtype">bool</span> isConstant)</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  : m_Shape(shape)</div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  , m_DataType(dataType)</div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  , m_IsConstant(isConstant)</div>
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span> {</div>
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(quantizationScale);</div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(quantizationOffset);</div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span> }</div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  </div>
<div class="line"><a name="l00359"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a35a1737605f6b189b67f659b463cdf52"> 359</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordtype">float</span> quantizationScale,</div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  int32_t quantizationOffset,</div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keywordtype">bool</span> isConstant)</div>
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  : m_Shape(numDimensions, dimensionSizes), m_DataType(dataType), m_IsConstant(isConstant)</div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span> {</div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(quantizationScale);</div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(quantizationOffset);</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span> }</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  </div>
<div class="line"><a name="l00371"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a20ef8da79251cbf4a70ec8a335f94e5a"> 371</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& shape,</div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim,</div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordtype">bool</span> isConstant)</div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  : m_Shape(shape)</div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  , m_DataType(dataType)</div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  , m_IsConstant(isConstant)</div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span> {</div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">SetQuantizationScales</a>(quantizationScales);</div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">SetQuantizationDim</a>(MakeOptional<unsigned int>(quantizationDim));</div>
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span> }</div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  </div>
<div class="line"><a name="l00384"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a82427ce9fa1e85bb8b785fbe1c8ad34e"> 384</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions,</div>
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div>
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div>
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div>
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim,</div>
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="keywordtype">bool</span> isConstant)</div>
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  : m_Shape(numDimensions, dimensionSizes)</div>
<div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  , m_DataType(dataType)</div>
<div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  , m_IsConstant(isConstant)</div>
<div class="line"><a name="l00393"></a><span class="lineno"> 393</span> {</div>
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">SetQuantizationScales</a>(quantizationScales);</div>
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">SetQuantizationDim</a>(MakeOptional<unsigned int>(quantizationDim));</div>
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span> }</div>
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  </div>
<div class="line"><a name="l00398"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#aef0989e23ab5fc862df9981d3b371f63"> 398</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo::TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other)</div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span> : m_Shape(other.m_Shape)</div>
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span> , m_DataType(other.m_DataType)</div>
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span> , m_IsConstant(other.m_IsConstant)</div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span> , m_Quantization(other.m_Quantization)</div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span> {}</div>
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  </div>
<div class="line"><a name="l00405"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#ac45c8c0052476cd66ef732de76dd9bc8"> 405</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="classarmnn_1_1_tensor_info.xhtml#ac45c8c0052476cd66ef732de76dd9bc8">TensorInfo::operator=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other)</div>
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span> {</div>
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  m_Shape = other.m_Shape;</div>
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  m_DataType = other.m_DataType;</div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  m_Quantization = other.m_Quantization;</div>
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  m_IsConstant = other.m_IsConstant;</div>
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span> }</div>
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  </div>
<div class="line"><a name="l00414"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a586e1eec08e847abfeb3de3a4038c5ce"> 414</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a586e1eec08e847abfeb3de3a4038c5ce">TensorInfo::operator==</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other)<span class="keyword"> const</span></div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keywordflow">return</span> ((m_Shape == other.m_Shape) &&</div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  (m_DataType == other.m_DataType) &&</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  (m_Quantization == other.m_Quantization) &&</div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  (m_IsConstant == other.m_IsConstant));</div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span> }</div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  </div>
<div class="line"><a name="l00422"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a2a944e616dc6fdde5287b17f2265307d"> 422</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a2a944e616dc6fdde5287b17f2265307d">TensorInfo::operator!=</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other)<span class="keyword"> const</span></div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <span class="keywordflow">return</span> !(*<span class="keyword">this</span> == other);</div>
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span> }</div>
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  </div>
<div class="line"><a name="l00427"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0"> 427</a></span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">TensorInfo::GetNumBytes</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aa02b9e06fb20fa3c13da0427e6ee5ab2">GetDataTypeSize</a>(m_DataType) * <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>();</div>
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span> }</div>
<div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  </div>
<div class="line"><a name="l00432"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a22f377fc4e10dc1773a3f979061e85f1"> 432</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a22f377fc4e10dc1773a3f979061e85f1">TensorInfo::IsTypeSpaceMatch</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& other)<span class="keyword"> const</span></div>
<div class="line"><a name="l00433"></a><span class="lineno"> 433</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="keywordtype">bool</span> match = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  </div>
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  match &= m_DataType == other.m_DataType;</div>
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  </div>
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd">IsQuantized</a>() && !<a class="code" href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">HasMultipleQuantizationScales</a>())</div>
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  {</div>
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  match &= <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>() == other.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>() &&</div>
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>() == other.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>();</div>
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  }</div>
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <span class="keywordflow">return</span> match;</div>
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span> }</div>
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  </div>
<div class="line"><a name="l00446"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48"> 446</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48">TensorInfo::HasPerAxisQuantization</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">HasMultipleQuantizationScales</a>() || m_Quantization.m_QuantizationDim.has_value();</div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span> }</div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  </div>
<div class="line"><a name="l00451"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270"> 451</a></span> std::vector<float> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270">TensorInfo::GetQuantizationScales</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="keywordflow">return</span> m_Quantization.m_Scales;</div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span> }</div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  </div>
<div class="line"><a name="l00456"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332"> 456</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">TensorInfo::SetQuantizationScales</a>(<span class="keyword">const</span> std::vector<float>& scales)</div>
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span> {</div>
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  m_Quantization.m_Scales = scales;</div>
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span> }</div>
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  </div>
<div class="line"><a name="l00461"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0"> 461</a></span> <span class="keywordtype">float</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">TensorInfo::GetQuantizationScale</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="keywordflow">if</span> (m_Quantization.m_Scales.empty())</div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  {</div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="comment">// NOTE: old default for backward compatibility</span></div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <span class="keywordflow">return</span> 1.0f;</div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  }</div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  </div>
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(!<a class="code" href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">HasMultipleQuantizationScales</a>());</div>
<div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="keywordflow">return</span> m_Quantization.m_Scales[0];</div>
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span> }</div>
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  </div>
<div class="line"><a name="l00473"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6"> 473</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">TensorInfo::SetQuantizationScale</a>(<span class="keywordtype">float</span> scale)</div>
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span> {</div>
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  m_Quantization.m_Scales = { scale };</div>
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span> }</div>
<div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  </div>
<div class="line"><a name="l00478"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5"> 478</a></span> int32_t <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">TensorInfo::GetQuantizationOffset</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <span class="keywordflow">if</span> (!m_Quantization.m_Offset.has_value())</div>
<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  {</div>
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <span class="comment">// NOTE: old default for backward compatibility</span></div>
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <span class="keywordflow">return</span> 0;</div>
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  }</div>
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  </div>
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <span class="keywordflow">return</span> m_Quantization.m_Offset.value();</div>
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span> }</div>
<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  </div>
<div class="line"><a name="l00489"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c"> 489</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">TensorInfo::SetQuantizationOffset</a>(int32_t offset)</div>
<div class="line"><a name="l00490"></a><span class="lineno"> 490</span> {</div>
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  m_Quantization.m_Offset = MakeOptional<int32_t>(offset);</div>
<div class="line"><a name="l00492"></a><span class="lineno"> 492</span> }</div>
<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  </div>
<div class="line"><a name="l00494"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8b8fc85ce966c035d789cf22db5088a1"> 494</a></span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<unsigned int></a> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b8fc85ce966c035d789cf22db5088a1">TensorInfo::GetQuantizationDim</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keywordflow">return</span> m_Quantization.m_QuantizationDim;</div>
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span> }</div>
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  </div>
<div class="line"><a name="l00499"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e"> 499</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">TensorInfo::SetQuantizationDim</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<unsigned int></a>& quantizationDim)</div>
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span> {</div>
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  m_Quantization.m_QuantizationDim = quantizationDim;</div>
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span> }</div>
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  </div>
<div class="line"><a name="l00504"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd"> 504</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd">TensorInfo::IsQuantized</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ad44c007f21af2d0375e3ef9400a1b275">IsQuantizedType</a>(m_DataType);</div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span> }</div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  </div>
<div class="line"><a name="l00509"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919"> 509</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">TensorInfo::IsConstant</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <span class="keywordflow">return</span> m_IsConstant;</div>
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span> }</div>
<div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  </div>
<div class="line"><a name="l00514"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8ffca1e21bdfa7f945617acd606aac91"> 514</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8ffca1e21bdfa7f945617acd606aac91">TensorInfo::SetConstant</a>(<span class="keyword">const</span> <span class="keywordtype">bool</span> IsConstant)</div>
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span> {</div>
<div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  m_IsConstant = <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">IsConstant</a>;</div>
<div class="line"><a name="l00517"></a><span class="lineno"> 517</span> }</div>
<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  </div>
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span> <span class="comment">// ---</span></div>
<div class="line"><a name="l00520"></a><span class="lineno"> 520</span> <span class="comment">// --- BaseTensor</span></div>
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span> <span class="comment">// ---</span></div>
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  </div>
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div>
<div class="line"><a name="l00524"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed"> 524</a></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed">BaseTensor<MemoryType>::BaseTensor</a>()</div>
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  : m_MemoryArea(nullptr)</div>
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span> {</div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span> }</div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  </div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div>
<div class="line"><a name="l00530"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aa84008eafa57252bcb4cc4b2d779a6f4"> 530</a></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType>::BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& info, MemoryType memoryArea)</div>
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  : m_MemoryArea(memoryArea)</div>
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  , m_Info(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span> {</div>
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span> }</div>
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  </div>
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div>
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType>::BaseTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType></a>& other)</div>
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  : m_MemoryArea(other.m_MemoryArea)</div>
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  , m_Info(other.GetInfo())</div>
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span> {</div>
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span> }</div>
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  </div>
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div>
<div class="line"><a name="l00544"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a844fc6ba8f5435b5a200072a3ec163af"> 544</a></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType></a>& <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType>::operator =</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<MemoryType></a>& other)</div>
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span> {</div>
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  m_Info = other.m_Info;</div>
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  m_MemoryArea = other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>;</div>
<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div>
<div class="line"><a name="l00549"></a><span class="lineno"> 549</span> }</div>
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  </div>
<div class="line"><a name="l00551"></a><span class="lineno"> 551</span> <span class="comment">// Explicit instantiations.</span></div>
<div class="line"><a name="l00552"></a><span class="lineno"> 552</span> <span class="keyword">template</span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<const void*></a>;</div>
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span> <span class="keyword">template</span> <span class="keyword">class </span><a class="code" href="classarmnn_1_1_base_tensor.xhtml">BaseTensor<void*></a>;</div>
<div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  </div>
<div class="line"><a name="l00555"></a><span class="lineno"> 555</span> } <span class="comment">// namespace armnn</span></div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<div class="ttc" id="anamespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">armnn::Dimensionality::Specified</a></div><div class="ttdeci">@ Specified</div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a770b51078da02f44a819e9f95d8058b5"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">armnn::TensorInfo::GetQuantizationOffset</a></div><div class="ttdeci">int32_t GetQuantizationOffset() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00478">Tensor.cpp:478</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a047ca888c43bd7fb5702853bf72410d0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">armnn::TensorInfo::GetQuantizationScale</a></div><div class="ttdeci">float GetQuantizationScale() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00461">Tensor.cpp:461</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">armnn::Dimensionality::NotSpecified</a></div><div class="ttdeci">@ NotSpecified</div></div>
<div class="ttc" id="a_utils_8hpp_xhtml"><div class="ttname"><a href="_utils_8hpp.xhtml">Utils.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a6e6dab22049a4432e8306a301dceff52"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a6e6dab22049a4432e8306a301dceff52">armnn::TensorShape::operator[]</a></div><div class="ttdeci">unsigned int operator[](unsigned int i) const</div><div class="ttdoc">Read only operator.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00135">Tensor.cpp:135</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681">armnn::Dimensionality</a></div><div class="ttdeci">Dimensionality</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00169">Types.hpp:169</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00473">Tensor.cpp:473</a></div></div>
<div class="ttc" id="a_exceptions_8hpp_xhtml_aa3be76aec4ce713822a5ea1ecbb7bc61"><div class="ttname"><a href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a></div><div class="ttdeci">#define CHECK_LOCATION()</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00203">Exceptions.hpp:203</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorShape::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdoc">Function that calculates the tensor elements by multiplying all dimension size which are Specified.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00181">Tensor.cpp:181</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a586e1eec08e847abfeb3de3a4038c5ce"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a586e1eec08e847abfeb3de3a4038c5ce">armnn::TensorInfo::operator==</a></div><div class="ttdeci">bool operator==(const TensorInfo &other) const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00414">Tensor.cpp:414</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a2a944e616dc6fdde5287b17f2265307d"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a2a944e616dc6fdde5287b17f2265307d">armnn::TensorInfo::operator!=</a></div><div class="ttdeci">bool operator!=(const TensorInfo &other) const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00422">Tensor.cpp:422</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_ac45c8c0052476cd66ef732de76dd9bc8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#ac45c8c0052476cd66ef732de76dd9bc8">armnn::TensorInfo::operator=</a></div><div class="ttdeci">TensorInfo & operator=(const TensorInfo &other)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00405">Tensor.cpp:405</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_ad44c007f21af2d0375e3ef9400a1b275"><div class="ttname"><a href="namespacearmnn.xhtml#ad44c007f21af2d0375e3ef9400a1b275">armnn::IsQuantizedType</a></div><div class="ttdeci">constexpr bool IsQuantizedType()</div><div class="ttdef"><b>Definition:</b> <a href="_types_utils_8hpp_source.xhtml#l00298">TypesUtils.hpp:298</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">armnn::Dimensionality::Scalar</a></div><div class="ttdeci">@ Scalar</div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a77d202fcd47612eb5a4d6d23a7d4b349"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a77d202fcd47612eb5a4d6d23a7d4b349">armnn::TensorShape::operator!=</a></div><div class="ttdeci">bool operator!=(const TensorShape &other) const</div><div class="ttdoc">Inequality comparison operator.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00169">Tensor.cpp:169</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a519efe8ff6dc3aacdfe8a999415e3e4e"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">armnn::TensorInfo::SetQuantizationDim</a></div><div class="ttdeci">void SetQuantizationDim(const Optional< unsigned int > &quantizationDim)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00499">Tensor.cpp:499</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml_aba26e5decca8be8786d8a5faf2e06a49"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">armnn::BaseTensor::m_MemoryArea</a></div><div class="ttdeci">MemoryType m_MemoryArea</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00312">Tensor.hpp:312</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a0ca6f42172d27e9799da3e3f7840ac31"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a0ca6f42172d27e9799da3e3f7840ac31">armnn::TensorShape::operator=</a></div><div class="ttdeci">TensorShape & operator=(const TensorShape &other)</div><div class="ttdoc">Assignation function.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00124">Tensor.cpp:124</a></div></div>
<div class="ttc" id="a_assert_8hpp_xhtml"><div class="ttname"><a href="_assert_8hpp.xhtml">Assert.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml">armnn::BaseTensor</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00277">Tensor.hpp:277</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a8ffca1e21bdfa7f945617acd606aac91"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8ffca1e21bdfa7f945617acd606aac91">armnn::TensorInfo::SetConstant</a></div><div class="ttdeci">void SetConstant(const bool IsConstant=true)</div><div class="ttdoc">Marks the data corresponding to this tensor info as constant.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00514">Tensor.cpp:514</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_aa02b9e06fb20fa3c13da0427e6ee5ab2"><div class="ttname"><a href="namespacearmnn.xhtml#aa02b9e06fb20fa3c13da0427e6ee5ab2">armnn::GetDataTypeSize</a></div><div class="ttdeci">constexpr unsigned int GetDataTypeSize(DataType dataType)</div><div class="ttdef"><b>Definition:</b> <a href="_types_utils_8hpp_source.xhtml#l00169">TypesUtils.hpp:169</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a07e348fae6036aecdaf41e738d1ae9ff"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a07e348fae6036aecdaf41e738d1ae9ff">armnn::TensorShape::operator==</a></div><div class="ttdeci">bool operator==(const TensorShape &other) const</div><div class="ttdoc">Equality comparison operator.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00160">Tensor.cpp:160</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors.</div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.xhtml#l00006">01_00_quick_start.dox:6</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a1a8675f9d64c3fb59e6af15362bb6332"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">armnn::TensorInfo::SetQuantizationScales</a></div><div class="ttdeci">void SetQuantizationScales(const std::vector< float > &scales)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00456">Tensor.cpp:456</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a82c7d5a6e675b1a876daa9983cd125d2"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a82c7d5a6e675b1a876daa9983cd125d2">armnn::TensorShape::SetNumDimensions</a></div><div class="ttdeci">void SetNumDimensions(unsigned int numDimensions, bool initDimensionsSpecificity=false)</div><div class="ttdoc">Sets the tensor rank and therefore the Dimensionality is set to Specified if it was not.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00219">Tensor.cpp:219</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00489">Tensor.cpp:489</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a76d053cd9b4373d90682ad646dad334c"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a76d053cd9b4373d90682ad646dad334c">armnn::TensorShape::TensorShape</a></div><div class="ttdeci">TensorShape()</div><div class="ttdoc">Empty (invalid) constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00025">Tensor.cpp:25</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_base_tensor_xhtml_aca0044508ebeb3b236a777db828910ed"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed">armnn::BaseTensor::BaseTensor</a></div><div class="ttdeci">BaseTensor()</div><div class="ttdoc">Empty (invalid) constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00524">Tensor.cpp:524</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a7c00efeb540198b33b8558c76e5cc2dd"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd">armnn::TensorInfo::IsQuantized</a></div><div class="ttdeci">bool IsQuantized() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00504">Tensor.cpp:504</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a945263e85c27f3216a8323cfc16d8919"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a945263e85c27f3216a8323cfc16d8919">armnn::TensorInfo::IsConstant</a></div><div class="ttdeci">bool IsConstant() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00509">Tensor.cpp:509</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a3919600d4aa8d5cd801a0e0740f62308"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a3919600d4aa8d5cd801a0e0740f62308">armnn::TensorShape::GetDimensionSpecificity</a></div><div class="ttdeci">bool GetDimensionSpecificity(unsigned int i) const</div><div class="ttdoc">Gets information about if the dimension size has been specified or not.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00211">Tensor.cpp:211</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a22f377fc4e10dc1773a3f979061e85f1"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a22f377fc4e10dc1773a3f979061e85f1">armnn::TensorInfo::IsTypeSpaceMatch</a></div><div class="ttdeci">bool IsTypeSpaceMatch(const TensorInfo &other) const</div><div class="ttdoc">Check that the types are the same and, if quantize, that the quantization parameters are the same.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00432">Tensor.cpp:432</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div><div class="ttdeci">@ Float32</div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00196">Tensor.hpp:196</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="a_tensor_8hpp_xhtml"><div class="ttname"><a href="_tensor_8hpp.xhtml">Tensor.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_ab85cd8cc10c96a7c99c14042c251fc48"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48">armnn::TensorInfo::HasPerAxisQuantization</a></div><div class="ttdeci">bool HasPerAxisQuantization() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00446">Tensor.cpp:446</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdoc">Function that returns the tensor rank.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00174">Tensor.cpp:174</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00048">Types.hpp:48</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a8b8fc85ce966c035d789cf22db5088a1"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b8fc85ce966c035d789cf22db5088a1">armnn::TensorInfo::GetQuantizationDim</a></div><div class="ttdeci">Optional< unsigned int > GetQuantizationDim() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00494">Tensor.cpp:494</a></div></div>
<div class="ttc" id="a_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_abcbdfb544ece4c31d0b37715ad0f3be0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">armnn::TensorInfo::GetNumBytes</a></div><div class="ttdeci">unsigned int GetNumBytes() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00427">Tensor.cpp:427</a></div></div>
<div class="ttc" id="a_exceptions_8hpp_xhtml"><div class="ttname"><a href="_exceptions_8hpp.xhtml">Exceptions.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional< unsigned int ></a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_af672d1c9e2a120a18926cb645981fbb7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#af672d1c9e2a120a18926cb645981fbb7">armnn::TensorInfo::HasMultipleQuantizationScales</a></div><div class="ttdeci">bool HasMultipleQuantizationScales() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00201">Tensor.hpp:201</a></div></div>
<div class="ttc" id="a_numeric_cast_8hpp_xhtml"><div class="ttname"><a href="_numeric_cast_8hpp.xhtml">NumericCast.hpp</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_a375ca3cff9f1b005d1412dc5f3cf5b6e"><div class="ttname"><a href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00035">NumericCast.hpp:35</a></div></div>
<div class="ttc" id="a_types_utils_8hpp_xhtml"><div class="ttname"><a href="_types_utils_8hpp.xhtml">TypesUtils.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_a34e12ab75d9073354565c2039f92112b"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a34e12ab75d9073354565c2039f92112b">armnn::TensorShape::IsAtLeastOneDimensionSpecified</a></div><div class="ttdeci">bool IsAtLeastOneDimensionSpecified() const</div><div class="ttdoc">Checks if there is at least one dimension specified.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00257">Tensor.cpp:257</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a8bc11f1fa23ef42532f9fdd04d355270"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270">armnn::TensorInfo::GetQuantizationScales</a></div><div class="ttdeci">std::vector< float > GetQuantizationScales() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00451">Tensor.cpp:451</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a21c2ae9fa438faf42669dadda628080c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">armnn::TensorInfo::TensorInfo</a></div><div class="ttdeci">TensorInfo()</div><div class="ttdoc">Empty (invalid) constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00341">Tensor.cpp:341</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_invalid_argument_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00080">Exceptions.hpp:80</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_abdcd184ed3bd648bb31d385040cafd5d"><div class="ttname"><a href="namespacearmnn.xhtml#abdcd184ed3bd648bb31d385040cafd5d">armnn::MaxNumOfTensorDimensions</a></div><div class="ttdeci">constexpr unsigned int MaxNumOfTensorDimensions</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00031">Types.hpp:31</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_ad82b782a8e1a05b6a3756e73c66d5f90"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#ad82b782a8e1a05b6a3756e73c66d5f90">armnn::TensorShape::SetDimensionSize</a></div><div class="ttdeci">void SetDimensionSize(unsigned int i, unsigned int dimensionSize)</div><div class="ttdoc">Sets the size of the indicated dimension and Specificity for that dimension is set to true.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00232">Tensor.cpp:232</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_xhtml_acccb75bd1d68a81f6ddd61687f51c5a1"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#acccb75bd1d68a81f6ddd61687f51c5a1">armnn::TensorShape::AreAllDimensionsSpecified</a></div><div class="ttdeci">bool AreAllDimensionsSpecified() const</div><div class="ttdoc">Checks if there is at least one dimension not specified.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00241">Tensor.cpp:241</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div><div class="ttdeci">@ info</div></div>
<!-- start footer part -->
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_e0a84d05c80a2ef4231141dcbbeac5c8.xhtml">armnn</a></li><li class="navelem"><a class="el" href="_tensor_8cpp.xhtml">Tensor.cpp</a></li>
<li class="footer">Generated on Thu May 18 2023 10:35:40 for ArmNN by
<a href="http://www.doxygen.org/index.html">
<img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.17 </li>
</ul>
</div>
</body>
</html>
|
