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| author | Jan Eilers <jan.eilers@arm.com> | 2021-02-25 17:44:00 +0000 |
|---|---|---|
| committer | Jan Eilers <jan.eilers@arm.com> | 2021-02-25 18:27:49 +0000 |
| commit | fd627ffaec8fd8801d980b4c91ee7c0607ab6aaf (patch) | |
| tree | eb4bc8f9b411f30c7655616142b5a4bdd3a1acd0 /21.02/_tensor_8cpp_source.xhtml | |
| parent | fb14ebbd68e04876809145296af96f6f41857418 (diff) | |
| download | armnn-fd627ffaec8fd8801d980b4c91ee7c0607ab6aaf.tar.gz | |
IVGCVSW-5687 Update Doxygen Docu
* Update Doxygen Documentation for 21.02 release
Signed-off-by: Jan Eilers <jan.eilers@arm.com>
Change-Id: I9ed2f9caab038836ea99d7b378d7899fe431a4e5
Diffstat (limited to '21.02/_tensor_8cpp_source.xhtml')
| -rw-r--r-- | 21.02/_tensor_8cpp_source.xhtml | 170 |
1 files changed, 170 insertions, 0 deletions
diff --git a/21.02/_tensor_8cpp_source.xhtml b/21.02/_tensor_8cpp_source.xhtml new file mode 100644 index 0000000000..e5d43b166a --- /dev/null +++ b/21.02/_tensor_8cpp_source.xhtml @@ -0,0 +1,170 @@ +<!-- 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 1.8.13"/> +<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> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">21.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_tensor_8cpp_source.xhtml','');}); +</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> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<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> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<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> <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="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> <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="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> <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="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> <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="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>)</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#ae0f1e7addec3daacb5e656e3031e84b2"> 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>  : m_Shape(shape)</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  , m_DataType(dataType)</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> {</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(quantizationScale);</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(quantizationOffset);</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> }</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> </div><div class="line"><a name="l00357"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#ac478f429b6f31e62bc72bdfc9c9ad242"> 357</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="l00358"></a><span class="lineno"> 358</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordtype">float</span> quantizationScale,</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  int32_t quantizationOffset)</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  : m_Shape(numDimensions, dimensionSizes)</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  , m_DataType(dataType)</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span> {</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(quantizationScale);</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(quantizationOffset);</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span> }</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> </div><div class="line"><a name="l00369"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#ac58c3467c7a7998120249cd0b940d221"> 369</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="l00370"></a><span class="lineno"> 370</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim)</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  : m_Shape(shape)</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  , m_DataType(dataType)</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> {</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">SetQuantizationScales</a>(quantizationScales);</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">SetQuantizationDim</a>(MakeOptional<unsigned int>(quantizationDim));</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> }</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> </div><div class="line"><a name="l00380"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a1e546b0233ac93ef3ef0e9ee96117c76"> 380</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="l00381"></a><span class="lineno"> 381</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>* dimensionSizes,</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType,</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keyword">const</span> std::vector<float>& quantizationScales,</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantizationDim)</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  : m_Shape(numDimensions, dimensionSizes)</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  , m_DataType(dataType)</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> {</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332">SetQuantizationScales</a>(quantizationScales);</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e">SetQuantizationDim</a>(MakeOptional<unsigned int>(quantizationDim));</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span> }</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> </div><div class="line"><a name="l00392"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#aef0989e23ab5fc862df9981d3b371f63"> 392</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="l00393"></a><span class="lineno"> 393</span> : m_Shape(other.m_Shape)</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> , m_DataType(other.m_DataType)</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> , m_Quantization(other.m_Quantization)</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#ac45c8c0052476cd66ef732de76dd9bc8"> 398</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="l00399"></a><span class="lineno"> 399</span> {</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  m_Shape = other.m_Shape;</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  m_DataType = other.m_DataType;</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>  <span class="keywordflow">return</span> *<span class="keyword">this</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"> 405</span> </div><div class="line"><a name="l00406"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a586e1eec08e847abfeb3de3a4038c5ce"> 406</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="l00407"></a><span class="lineno"> 407</span> <span class="keyword"></span>{</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keywordflow">return</span> ((m_Shape == other.m_Shape) &&</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  (m_DataType == other.m_DataType) &&</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  (m_Quantization == other.m_Quantization));</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</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"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a2a944e616dc6fdde5287b17f2265307d"> 413</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="l00414"></a><span class="lineno"> 414</span> <span class="keyword"></span>{</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="keywordflow">return</span> !(*<span class="keyword">this</span> == other);</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span> }</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> </div><div class="line"><a name="l00418"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0"> 418</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="l00419"></a><span class="lineno"> 419</span> <span class="keyword"></span>{</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</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="l00421"></a><span class="lineno"> 421</span> }</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span> </div><div class="line"><a name="l00423"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a22f377fc4e10dc1773a3f979061e85f1"> 423</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="l00424"></a><span class="lineno"> 424</span> <span class="keyword"></span>{</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  <span class="keywordtype">bool</span> match = <span class="keyword">true</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"> 427</span>  match &= m_DataType == other.m_DataType;</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> </div><div class="line"><a name="l00429"></a><span class="lineno"> 429</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="l00430"></a><span class="lineno"> 430</span>  {</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</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="l00432"></a><span class="lineno"> 432</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="l00433"></a><span class="lineno"> 433</span>  }</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="keywordflow">return</span> match;</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> </div><div class="line"><a name="l00437"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#ab85cd8cc10c96a7c99c14042c251fc48"> 437</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="l00438"></a><span class="lineno"> 438</span> <span class="keyword"></span>{</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</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="l00440"></a><span class="lineno"> 440</span> }</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span> </div><div class="line"><a name="l00442"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8bc11f1fa23ef42532f9fdd04d355270"> 442</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="l00443"></a><span class="lineno"> 443</span> <span class="keyword"></span>{</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <span class="keywordflow">return</span> m_Quantization.m_Scales;</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span> }</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span> </div><div class="line"><a name="l00447"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a1a8675f9d64c3fb59e6af15362bb6332"> 447</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="l00448"></a><span class="lineno"> 448</span> {</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  m_Quantization.m_Scales = scales;</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span> }</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> </div><div class="line"><a name="l00452"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0"> 452</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="l00453"></a><span class="lineno"> 453</span> <span class="keyword"></span>{</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <span class="keywordflow">if</span> (m_Quantization.m_Scales.empty())</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  {</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="comment">// NOTE: old default for backward compatibility</span></div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="keywordflow">return</span> 1.0f;</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  }</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>  <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="l00461"></a><span class="lineno"> 461</span>  <span class="keywordflow">return</span> m_Quantization.m_Scales[0];</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span> }</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span> </div><div class="line"><a name="l00464"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6"> 464</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="l00465"></a><span class="lineno"> 465</span> {</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  m_Quantization.m_Scales = { scale };</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"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5"> 469</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="l00470"></a><span class="lineno"> 470</span> <span class="keyword"></span>{</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keywordflow">if</span> (!m_Quantization.m_Offset.has_value())</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  {</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <span class="comment">// NOTE: old default for backward compatibility</span></div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  }</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>  <span class="keywordflow">return</span> m_Quantization.m_Offset.value();</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span> }</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span> </div><div class="line"><a name="l00480"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c"> 480</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="l00481"></a><span class="lineno"> 481</span> {</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  m_Quantization.m_Offset = MakeOptional<int32_t>(offset);</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span> }</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span> </div><div class="line"><a name="l00485"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a8b8fc85ce966c035d789cf22db5088a1"> 485</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="l00486"></a><span class="lineno"> 486</span> <span class="keyword"></span>{</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <span class="keywordflow">return</span> m_Quantization.m_QuantizationDim;</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span> }</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> </div><div class="line"><a name="l00490"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a519efe8ff6dc3aacdfe8a999415e3e4e"> 490</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="l00491"></a><span class="lineno"> 491</span> {</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  m_Quantization.m_QuantizationDim = quantizationDim;</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span> }</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span> </div><div class="line"><a name="l00495"></a><span class="lineno"><a class="line" href="classarmnn_1_1_tensor_info.xhtml#a7c00efeb540198b33b8558c76e5cc2dd"> 495</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="l00496"></a><span class="lineno"> 496</span> <span class="keyword"></span>{</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ad44c007f21af2d0375e3ef9400a1b275">IsQuantizedType</a>(m_DataType);</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span> }</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span> </div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span> <span class="comment">// ---</span></div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span> <span class="comment">// --- BaseTensor</span></div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span> <span class="comment">// ---</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"> 504</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00505"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed"> 505</a></span> <a class="code" href="classarmnn_1_1_base_tensor.xhtml#aca0044508ebeb3b236a777db828910ed">BaseTensor<MemoryType>::BaseTensor</a>()</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  : m_MemoryArea(nullptr)</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"> 509</span> </div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00511"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#aa84008eafa57252bcb4cc4b2d779a6f4"> 511</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="l00512"></a><span class="lineno"> 512</span>  : m_MemoryArea(memoryArea)</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  , m_Info(info)</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span> {</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> </div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00518"></a><span class="lineno"> 518</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="l00519"></a><span class="lineno"> 519</span>  : m_MemoryArea(other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>)</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  , m_Info(other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>())</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</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> </div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span> <span class="keyword">template</span><<span class="keyword">typename</span> MemoryType></div><div class="line"><a name="l00525"></a><span class="lineno"><a class="line" href="classarmnn_1_1_base_tensor.xhtml#a844fc6ba8f5435b5a200072a3ec163af"> 525</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="l00526"></a><span class="lineno"> 526</span> {</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  m_Info = other.m_Info;</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  m_MemoryArea = other.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#aba26e5decca8be8786d8a5faf2e06a49">m_MemoryArea</a>;</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span> }</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span> </div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span> <span class="comment">// Explicit instantiations.</span></div><div class="line"><a name="l00533"></a><span class="lineno"> 533</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="l00534"></a><span class="lineno"> 534</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="l00535"></a><span class="lineno"> 535</span> </div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span> } <span class="comment">// namespace armnn</span></div><div class="ttc" id="classarmnn_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="classarmnn_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="classarmnn_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="classarmnn_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#l00423">Tensor.cpp:423</a></div></div> +<div class="ttc" id="namespacearmnn_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#l00125">Types.hpp:125</a></div></div> +<div class="ttc" id="_tensor_8hpp_xhtml"><div class="ttname"><a href="_tensor_8hpp.xhtml">Tensor.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">armnn::Dimensionality::NotSpecified</a></div></div> +<div class="ttc" id="classarmnn_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="_utils_8hpp_xhtml"><div class="ttname"><a href="_utils_8hpp.xhtml">Utils.hpp</a></div></div> +<div class="ttc" id="classarmnn_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="classarmnn_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="namespacearmnn_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#l00249">TypesUtils.hpp:249</a></div></div> +<div class="ttc" id="classarmnn_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="classarmnn_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#l00437">Tensor.cpp:437</a></div></div> +<div class="ttc" id="classarmnn_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#l00485">Tensor.cpp:485</a></div></div> +<div class="ttc" id="classarmnn_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#l00418">Tensor.cpp:418</a></div></div> +<div class="ttc" id="namespacearmnn_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__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681ab4b379bf7ded74c07595ccb85bc6fdc3">armnn::Dimensionality::Specified</a></div></div> +<div class="ttc" id="classarmnn_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="classarmnn_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#l00442">Tensor.cpp:442</a></div></div> +<div class="ttc" id="classarmnn_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#l00197">Tensor.hpp:197</a></div></div> +<div class="ttc" id="classarmnn_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="_numeric_cast_8hpp_xhtml"><div class="ttname"><a href="_numeric_cast_8hpp.xhtml">NumericCast.hpp</a></div></div> +<div class="ttc" id="classarmnn_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="_types_utils_8hpp_xhtml"><div class="ttname"><a href="_types_utils_8hpp.xhtml">TypesUtils.hpp</a></div></div> +<div class="ttc" id="classarmnn_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="classarmnn_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="namespacearmnn_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#l00032">Types.hpp:32</a></div></div> +<div class="ttc" id="classarmnn_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#l00469">Tensor.cpp:469</a></div></div> +<div class="ttc" id="classarmnn_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#l00452">Tensor.cpp:452</a></div></div> +<div class="ttc" id="classarmnn_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="classarmnn_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#l00464">Tensor.cpp:464</a></div></div> +<div class="ttc" id="_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="classarmnn_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#l00299">Tensor.hpp:299</a></div></div> +<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a8aeddebdcf02e1832b22203c08a6b678"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">armnn::BaseTensor::GetInfo</a></div><div class="ttdeci">const TensorInfo & GetInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00282">Tensor.hpp:282</a></div></div> +<div class="ttc" id="classarmnn_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="_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#l00197">Exceptions.hpp:197</a></div></div> +<div class="ttc" id="classarmnn_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#l00398">Tensor.cpp:398</a></div></div> +<div class="ttc" id="classarmnn_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#l00490">Tensor.cpp:490</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">armnn::Dimensionality::Scalar</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml"><div class="ttname"><a href="_assert_8hpp.xhtml">Assert.hpp</a></div></div> +<div class="ttc" id="classarmnn_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#l00406">Tensor.cpp:406</a></div></div> +<div class="ttc" id="classarmnn_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#l00413">Tensor.cpp:413</a></div></div> +<div class="ttc" id="classarmnn_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#l00505">Tensor.cpp:505</a></div></div> +<div class="ttc" id="_exceptions_8hpp_xhtml"><div class="ttname"><a href="_exceptions_8hpp.xhtml">Exceptions.hpp</a></div></div> +<div class="ttc" id="classarmnn_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="classarmnn_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="classarmnn_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#l00264">Tensor.hpp:264</a></div></div> +<div class="ttc" id="namespacearmnn_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="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_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#l00480">Tensor.cpp:480</a></div></div> +<div class="ttc" id="classarmnn_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#l00447">Tensor.cpp:447</a></div></div> +<div class="ttc" id="classarmnn_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="classarmnn_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#l00495">Tensor.cpp:495</a></div></div> +<div class="ttc" id="namespacearmnn_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#l00018">Types.hpp:18</a></div></div> +<div class="ttc" id="classarmnn_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#l00192">Tensor.hpp:192</a></div></div> +<div class="ttc" id="namespacearmnn_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#l00126">TypesUtils.hpp:126</a></div></div> +</div><!-- fragment --></div><!-- contents --> +</div><!-- doc-content --> +<!-- 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 Feb 25 2021 17:27:29 for 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