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diff --git a/20.02/_deserializer_8cpp_source.xhtml b/20.02/_deserializer_8cpp_source.xhtml new file mode 100644 index 0000000000..1e5d45d095 --- /dev/null +++ b/20.02/_deserializer_8cpp_source.xhtml @@ -0,0 +1,427 @@ +<!-- 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/armnnDeserializer/Deserializer.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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">20.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(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('_deserializer_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">Deserializer.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_deserializer_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="_deserializer_8hpp.xhtml">Deserializer.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_descriptors_8hpp.xhtml">armnn/Descriptors.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_exceptions_8hpp.xhtml">armnn/Exceptions.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_types_utils_8hpp.xhtml">armnn/TypesUtils.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_lstm_params_8hpp.xhtml">armnn/LstmParams.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_quantized_lstm_params_8hpp.xhtml">armnn/QuantizedLstmParams.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 <<a class="code" href="_permute_8hpp.xhtml">armnnUtils/Permute.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_transpose_8hpp.xhtml">armnnUtils/Transpose.hpp</a>></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_ignore_unused_8hpp.xhtml">armnn/utility/IgnoreUnused.hpp</a>></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="preprocessor">#include <<a class="code" href="_parser_helper_8hpp.xhtml">ParserHelper.hpp</a>></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include <<a class="code" href="_verification_helpers_8hpp.xhtml">VerificationHelpers.hpp</a>></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="preprocessor">#include <boost/filesystem.hpp></span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="preprocessor">#include <boost/format.hpp></span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#include <boost/assert.hpp></span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include <boost/format.hpp></span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include <boost/format.hpp></span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include <boost/numeric/conversion/cast.hpp></span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include <boost/polymorphic_cast.hpp></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> <span class="preprocessor">#include <fstream></span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include <algorithm></span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include <limits></span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include <numeric></span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">using</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn_serializer.xhtml">armnnSerializer</a>;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> </div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn_deserializer.xhtml">armnnDeserializer</a></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> {</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="keyword">namespace</span></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> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="keyword">const</span> uint32_t VIRTUAL_LAYER_ID = std::numeric_limits<uint32_t>::max();</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordtype">void</span> CheckGraph(<span class="keyword">const</span> Deserializer::GraphPtr& graph,</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layersIndex,</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_check_location.xhtml">CheckLocation</a>& location)</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>  <span class="keywordflow">if</span> (graph->layers() == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  {</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  boost::str(</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  boost::format(<span class="stringliteral">"%1% was called with invalid (null) graph. "</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="stringliteral">"Possible reason is that the graph is not yet loaded and Unpack(ed). "</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="stringliteral">"layers:%2% at %3%"</span>) %</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#a46e3b4b140e2c550342337b5fcceb9c6">m_Function</a> %</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  layersIndex %</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#ac1184445a1323e07e0da084a54aec535">FileLine</a>()));</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  }</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layersIndex >= graph->layers()->size())</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  {</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  boost::str(</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  boost::format(<span class="stringliteral">"%1% was called with an invalid layers index. "</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="stringliteral">"layers:%2% at %3%"</span>) %</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#a46e3b4b140e2c550342337b5fcceb9c6">m_Function</a> %</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  layersIndex %</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#ac1184445a1323e07e0da084a54aec535">FileLine</a>()));</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> }</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="keywordtype">void</span> <a class="code" href="_optimization_views_tests_8cpp.xhtml#a6c81e7ec0af6eeda194d2bd8cd40eccf">CheckLayers</a>(<span class="keyword">const</span> Deserializer::GraphPtr& graph,</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layersIndex,</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex,</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_check_location.xhtml">CheckLocation</a>& location)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">if</span> (graph->layers() == <span class="keyword">nullptr</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"> 80</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  boost::str(</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  boost::format(<span class="stringliteral">"%1% was called with invalid (null) graph. "</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="stringliteral">"Possible reason is that the graph is not yet loaded and Unpack(ed). "</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="stringliteral">"layers:%2% at %3%"</span>) %</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#a46e3b4b140e2c550342337b5fcceb9c6">m_Function</a> %</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  layersIndex %</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#ac1184445a1323e07e0da084a54aec535">FileLine</a>()));</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="keywordflow">else</span> <span class="keywordflow">if</span> (layersIndex >= graph->layers()->size())</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>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  boost::str(</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  boost::format(<span class="stringliteral">"%1% was called with an invalid layers index. "</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="stringliteral">"layers:%2% at %3%"</span>) %</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#a46e3b4b140e2c550342337b5fcceb9c6">m_Function</a> %</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  layersIndex %</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#ac1184445a1323e07e0da084a54aec535">FileLine</a>()));</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  }</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layerIndex >= graph->layers()[layersIndex].size()</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  && layerIndex != VIRTUAL_LAYER_ID)</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  {</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  boost::str(</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  boost::format(<span class="stringliteral">"%1% was called with an invalid layer index. "</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="stringliteral">"layers:%2% layer:%3% at %4%"</span>) %</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#a46e3b4b140e2c550342337b5fcceb9c6">m_Function</a> %</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  layersIndex %</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  layerIndex %</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#ac1184445a1323e07e0da084a54aec535">FileLine</a>()));</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  }</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> }</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="keywordtype">void</span> CheckTensorPtr(<a class="code" href="_parser_flatbuffers_serialize_fixture_8hpp.xhtml#a15c20a0693cd3fc4d85565e2f920d8ef">Deserializer::TensorRawPtr</a> rawPtr,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_check_location.xhtml">CheckLocation</a>& location)</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> {</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keywordflow">if</span> (rawPtr == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  {</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  boost::str(</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  boost::format(<span class="stringliteral">"%1% was called with a null tensor pointer. "</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="stringliteral">"at %2%"</span>) %</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#a46e3b4b140e2c550342337b5fcceb9c6">m_Function</a> %</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#ac1184445a1323e07e0da084a54aec535">FileLine</a>()));</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </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> }</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="keywordtype">void</span> CheckConstTensorPtr(Deserializer::ConstTensorRawPtr rawPtr,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_check_location.xhtml">CheckLocation</a>& location)</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> {</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">if</span> (rawPtr == <span class="keyword">nullptr</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>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(boost::str(boost::format(<span class="stringliteral">"%1% was called with a null const tensor pointer. at %2%"</span>) %</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#a46e3b4b140e2c550342337b5fcceb9c6">m_Function</a> %</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#ac1184445a1323e07e0da084a54aec535">FileLine</a>()));</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  }</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> }</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="keywordtype">void</span> CheckConstTensorSize(<span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> constTensorSize,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> tensorSize,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_check_location.xhtml">CheckLocation</a>& location)</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>  <span class="keywordflow">if</span> (constTensorSize != tensorSize)</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  {</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(boost::str(boost::format(<span class="stringliteral">"%1% wrong number of components supplied to tensor. at:%2%"</span>) %</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#a46e3b4b140e2c550342337b5fcceb9c6">m_Function</a> %</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#ac1184445a1323e07e0da084a54aec535">FileLine</a>()));</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> }</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div><div class="line"><a name="l00151"></a><span class="lineno"><a class="line" href="_deserializer_8cpp.xhtml#ae38d96fe05581ea025713b3e781c5a43"> 151</a></span> <span class="preprocessor">#define CHECK_TENSOR_PTR(TENSOR_PTR) \</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="preprocessor"> CheckTensorPtr(TENSOR_PTR, CHECK_LOCATION())</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"><a class="line" href="_deserializer_8cpp.xhtml#aa6fd9c6c98bdd08620d75cac3a2e17e6"> 154</a></span> <span class="preprocessor">#define CHECK_CONST_TENSOR_SIZE(CONST_TENSOR_SIZE, TENSOR_SIZE) \</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="preprocessor"> CheckConstTensorSize(CONST_TENSOR_SIZE, TENSOR_SIZE, CHECK_LOCATION())</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"><a class="line" href="_deserializer_8cpp.xhtml#a637ba180b64a3cd1a4f83d048a030772"> 157</a></span> <span class="preprocessor">#define CHECK_CONST_TENSOR_PTR(TENSOR_PTR) \</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="preprocessor"> CheckConstTensorPtr(TENSOR_PTR, CHECK_LOCATION())</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="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d"> 160</a></span> <span class="preprocessor">#define CHECK_LAYERS(GRAPH, LAYERS_INDEX, LAYER_INDEX) \</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="preprocessor"> CheckLayers(GRAPH, LAYERS_INDEX, LAYER_INDEX, CHECK_LOCATION())</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"><a class="line" href="_deserializer_8cpp.xhtml#ab90eef134463f7b44cd4c9cfb2529825"> 163</a></span> <span class="preprocessor">#define CHECK_GRAPH(GRAPH, LAYERS_INDEX) \</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> <span class="preprocessor"> CheckGraph(GRAPH, LAYERS_INDEX, CHECK_LOCATION())</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> }</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.xhtml#a97b50f22cd99f0e09e6e48d20a35f6b2"> 167</a></span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn_deserializer.xhtml#a97b50f22cd99f0e09e6e48d20a35f6b2">CheckShape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& actual, <span class="keyword">const</span> std::vector<uint32_t>& expected)</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> {</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> actualSize = actual.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keywordflow">if</span> (actualSize != expected.size())</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  {</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keywordflow">return</span> <span class="keyword">false</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"> 174</span> </div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < actualSize; i++)</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  {</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keywordflow">if</span> (actual[i] != static_cast<unsigned int>(expected[i]))</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  {</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keywordflow">return</span> <span class="keyword">false</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"> 181</span>  }</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</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> </div><div class="line"><a name="l00186"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#a43e0ec855f3a7ebf9f98fbee5321edcf"> 186</a></span> Deserializer::Deserializer()</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> : m_Network(nullptr, nullptr),</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> <span class="comment">//May require LayerType_Max to be included</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> m_ParserFunctions(Layer_MAX+1, &<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml">Deserializer</a>::ParseUnsupportedLayer)</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> {</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="comment">// register supported layers</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  m_ParserFunctions[Layer_AbsLayer] = &Deserializer::ParseAbs;</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  m_ParserFunctions[Layer_ActivationLayer] = &Deserializer::ParseActivation;</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  m_ParserFunctions[Layer_AdditionLayer] = &Deserializer::ParseAdd;</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  m_ParserFunctions[Layer_ArgMinMaxLayer] = &Deserializer::ParseArgMinMax;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  m_ParserFunctions[Layer_BatchToSpaceNdLayer] = &Deserializer::ParseBatchToSpaceNd;</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  m_ParserFunctions[Layer_BatchNormalizationLayer] = &Deserializer::ParseBatchNormalization;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  m_ParserFunctions[Layer_ComparisonLayer] = &Deserializer::ParseComparison;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  m_ParserFunctions[Layer_ConcatLayer] = &Deserializer::ParseConcat;</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  m_ParserFunctions[Layer_ConstantLayer] = &Deserializer::ParseConstant;</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  m_ParserFunctions[Layer_Convolution2dLayer] = &Deserializer::ParseConvolution2d;</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  m_ParserFunctions[Layer_DepthToSpaceLayer] = &Deserializer::ParseDepthToSpace;</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  m_ParserFunctions[Layer_DepthwiseConvolution2dLayer] = &Deserializer::ParseDepthwiseConvolution2d;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  m_ParserFunctions[Layer_DequantizeLayer] = &Deserializer::ParseDequantize;</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  m_ParserFunctions[Layer_DetectionPostProcessLayer] = &Deserializer::ParseDetectionPostProcess;</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  m_ParserFunctions[Layer_DivisionLayer] = &Deserializer::ParseDivision;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  m_ParserFunctions[Layer_ElementwiseUnaryLayer] = &Deserializer::ParseElementwiseUnary;</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  m_ParserFunctions[Layer_EqualLayer] = &Deserializer::ParseEqual;</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  m_ParserFunctions[Layer_FullyConnectedLayer] = &Deserializer::ParseFullyConnected;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  m_ParserFunctions[Layer_FloorLayer] = &Deserializer::ParseFloor;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  m_ParserFunctions[Layer_GatherLayer] = &Deserializer::ParseGather;</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  m_ParserFunctions[Layer_GreaterLayer] = &Deserializer::ParseGreater;</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  m_ParserFunctions[Layer_InstanceNormalizationLayer] = &Deserializer::ParseInstanceNormalization;</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  m_ParserFunctions[Layer_L2NormalizationLayer] = &Deserializer::ParseL2Normalization;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  m_ParserFunctions[Layer_LogSoftmaxLayer] = &Deserializer::ParseLogSoftmax;</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  m_ParserFunctions[Layer_LstmLayer] = &Deserializer::ParseLstm;</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  m_ParserFunctions[Layer_MaximumLayer] = &Deserializer::ParseMaximum;</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  m_ParserFunctions[Layer_MeanLayer] = &Deserializer::ParseMean;</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  m_ParserFunctions[Layer_MinimumLayer] = &Deserializer::ParseMinimum;</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  m_ParserFunctions[Layer_MergeLayer] = &Deserializer::ParseMerge;</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  m_ParserFunctions[Layer_MergerLayer] = &Deserializer::ParseConcat;</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  m_ParserFunctions[Layer_MultiplicationLayer] = &Deserializer::ParseMultiplication;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  m_ParserFunctions[Layer_NormalizationLayer] = &Deserializer::ParseNormalization;</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  m_ParserFunctions[Layer_PadLayer] = &Deserializer::ParsePad;</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  m_ParserFunctions[Layer_PermuteLayer] = &Deserializer::ParsePermute;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  m_ParserFunctions[Layer_Pooling2dLayer] = &Deserializer::ParsePooling2d;</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  m_ParserFunctions[Layer_PreluLayer] = &Deserializer::ParsePrelu;</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  m_ParserFunctions[Layer_QuantizeLayer] = &Deserializer::ParseQuantize;</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  m_ParserFunctions[Layer_QuantizedLstmLayer] = &Deserializer::ParseQuantizedLstm;</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  m_ParserFunctions[Layer_ReshapeLayer] = &Deserializer::ParseReshape;</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  m_ParserFunctions[Layer_ResizeBilinearLayer] = &Deserializer::ParseResizeBilinear;</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  m_ParserFunctions[Layer_ResizeLayer] = &Deserializer::ParseResize;</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  m_ParserFunctions[Layer_RsqrtLayer] = &Deserializer::ParseRsqrt;</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  m_ParserFunctions[Layer_SliceLayer] = &Deserializer::ParseSlice;</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  m_ParserFunctions[Layer_SoftmaxLayer] = &Deserializer::ParseSoftmax;</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  m_ParserFunctions[Layer_SpaceToBatchNdLayer] = &Deserializer::ParseSpaceToBatchNd;</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  m_ParserFunctions[Layer_SpaceToDepthLayer] = &Deserializer::ParseSpaceToDepth;</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  m_ParserFunctions[Layer_SplitterLayer] = &Deserializer::ParseSplitter;</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  m_ParserFunctions[Layer_StackLayer] = &Deserializer::ParseStack;</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  m_ParserFunctions[Layer_StandInLayer] = &Deserializer::ParseStandIn;</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  m_ParserFunctions[Layer_StridedSliceLayer] = &Deserializer::ParseStridedSlice;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  m_ParserFunctions[Layer_SubtractionLayer] = &Deserializer::ParseSubtraction;</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  m_ParserFunctions[Layer_SwitchLayer] = &Deserializer::ParseSwitch;</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  m_ParserFunctions[Layer_TransposeConvolution2dLayer] = &Deserializer::ParseTransposeConvolution2d;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  m_ParserFunctions[Layer_TransposeLayer] = &Deserializer::ParseTranspose;</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> }</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> </div><div class="line"><a name="l00248"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc"> 248</a></span> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a91ade61b5704e4f2c38c263c2be148ef">Deserializer::LayerBaseRawPtr</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">Deserializer::GetBaseLayer</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</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>  <span class="keyword">auto</span> layerType = graphPtr->layers()->Get(layerIndex)->layer_type();</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> </div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">switch</span>(layerType)</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">case</span> Layer::Layer_AbsLayer:</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_AbsLayer()->base();</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <span class="keywordflow">case</span> Layer::Layer_ActivationLayer:</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ActivationLayer()->base();</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keywordflow">case</span> Layer::Layer_AdditionLayer:</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_AdditionLayer()->base();</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keywordflow">case</span> Layer::Layer_ArgMinMaxLayer:</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ArgMinMaxLayer()->base();</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keywordflow">case</span> Layer::Layer_BatchToSpaceNdLayer:</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_BatchToSpaceNdLayer()->base();</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">case</span> Layer::Layer_BatchNormalizationLayer:</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_BatchNormalizationLayer()->base();</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keywordflow">case</span> Layer::Layer_ComparisonLayer:</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ComparisonLayer()->base();</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <span class="keywordflow">case</span> Layer::Layer_ConcatLayer:</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ConcatLayer()->base();</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="keywordflow">case</span> Layer::Layer_ConstantLayer:</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ConstantLayer()->base();</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keywordflow">case</span> Layer::Layer_Convolution2dLayer:</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_Convolution2dLayer()->base();</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keywordflow">case</span> Layer::Layer_DepthToSpaceLayer:</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DepthToSpaceLayer()->base();</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <span class="keywordflow">case</span> Layer::Layer_DepthwiseConvolution2dLayer:</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DepthwiseConvolution2dLayer()->base();</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="keywordflow">case</span> Layer::Layer_DequantizeLayer:</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DequantizeLayer()->base();</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keywordflow">case</span> Layer::Layer_DetectionPostProcessLayer:</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DetectionPostProcessLayer()->base();</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="keywordflow">case</span> Layer::Layer_DivisionLayer:</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_DivisionLayer()->base();</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="keywordflow">case</span> Layer::Layer_EqualLayer:</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_EqualLayer()->base();</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keywordflow">case</span> Layer::Layer_FullyConnectedLayer:</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_FullyConnectedLayer()->base();</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <span class="keywordflow">case</span> Layer::Layer_FloorLayer:</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_FloorLayer()->base();</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="keywordflow">case</span> Layer::Layer_GatherLayer:</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_GatherLayer()->base();</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keywordflow">case</span> Layer::Layer_GreaterLayer:</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_GreaterLayer()->base();</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keywordflow">case</span> Layer::Layer_InputLayer:</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->base();</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="keywordflow">case</span> Layer::Layer_InstanceNormalizationLayer:</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_InstanceNormalizationLayer()->base();</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordflow">case</span> Layer::Layer_L2NormalizationLayer:</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_L2NormalizationLayer()->base();</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="keywordflow">case</span> Layer::Layer_LogSoftmaxLayer:</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_LogSoftmaxLayer()->base();</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keywordflow">case</span> Layer::Layer_LstmLayer:</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_LstmLayer()->base();</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordflow">case</span> Layer::Layer_MeanLayer:</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MeanLayer()->base();</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keywordflow">case</span> Layer::Layer_MinimumLayer:</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MinimumLayer()->base();</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keywordflow">case</span> Layer::Layer_MaximumLayer:</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MaximumLayer()->base();</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordflow">case</span> Layer::Layer_MergeLayer:</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MergeLayer()->base();</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keywordflow">case</span> Layer::Layer_MergerLayer:</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MergerLayer()->base();</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordflow">case</span> Layer::Layer_MultiplicationLayer:</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_MultiplicationLayer()->base();</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordflow">case</span> Layer::Layer_NormalizationLayer:</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_NormalizationLayer()->base();</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="keywordflow">case</span> Layer::Layer_OutputLayer:</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->base();</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keywordflow">case</span> Layer::Layer_PadLayer:</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_PadLayer()->base();</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keywordflow">case</span> Layer::Layer_PermuteLayer:</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_PermuteLayer()->base();</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordflow">case</span> Layer::Layer_Pooling2dLayer:</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_Pooling2dLayer()->base();</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keywordflow">case</span> Layer::Layer_PreluLayer:</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_PreluLayer()->base();</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keywordflow">case</span> Layer::Layer_QuantizeLayer:</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_QuantizeLayer()->base();</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="keywordflow">case</span> Layer::Layer_QuantizedLstmLayer:</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_QuantizedLstmLayer()->base();</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keywordflow">case</span> Layer::Layer_ReshapeLayer:</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->base();</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">case</span> Layer::Layer_ResizeBilinearLayer:</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ResizeBilinearLayer()->base();</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="keywordflow">case</span> Layer::Layer_ResizeLayer:</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_ResizeLayer()->base();</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordflow">case</span> Layer::Layer_RsqrtLayer:</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_RsqrtLayer()->base();</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">case</span> Layer::Layer_SliceLayer:</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SliceLayer()->base();</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">case</span> Layer::Layer_SoftmaxLayer:</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->base();</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="keywordflow">case</span> Layer::Layer_SpaceToBatchNdLayer:</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToBatchNdLayer()->base();</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keywordflow">case</span> Layer::Layer_SpaceToDepthLayer:</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToDepthLayer()->base();</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordflow">case</span> Layer::Layer_SplitterLayer:</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SplitterLayer()->base();</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">case</span> Layer::Layer_StackLayer:</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_StackLayer()->base();</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keywordflow">case</span> Layer::Layer_StandInLayer:</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_StandInLayer()->base();</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keywordflow">case</span> Layer::Layer_StridedSliceLayer:</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_StridedSliceLayer()->base();</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keywordflow">case</span> Layer::Layer_SubtractionLayer:</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SubtractionLayer()->base();</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordflow">case</span> Layer::Layer_SwitchLayer:</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_SwitchLayer()->base();</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">case</span> Layer::Layer_TransposeConvolution2dLayer:</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_TransposeConvolution2dLayer()->base();</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">case</span> Layer::Layer_TransposeLayer:</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_TransposeLayer()->base();</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keywordflow">case</span> Layer::Layer_NONE:</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(boost::str(</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  boost::format(<span class="stringliteral">"Layer type %1% not recognized"</span>) %</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  layerType));</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  }</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> }</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span> </div><div class="line"><a name="l00372"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2"> 372</a></span> std::string <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">Deserializer::GetLayerName</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index)</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> {</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keyword">auto</span> layer = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graph, index);</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  assert(layer);</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordflow">return</span> layer->layerName()->str();</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> }</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> </div><div class="line"><a name="l00379"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#afcc87bf0e20779861dd5d01a4bedcda9"> 379</a></span> int32_t <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#afcc87bf0e20779861dd5d01a4bedcda9">Deserializer::GetBindingLayerInfo</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> {</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keyword">auto</span> layerType = graphPtr->layers()->Get(layerIndex)->layer_type();</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> </div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keywordflow">if</span> (layerType == Layer::Layer_InputLayer)</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  {</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->layerBindingId();</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  }</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> ( layerType == Layer::Layer_OutputLayer )</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  {</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="keywordflow">return</span> graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->layerBindingId();</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>  <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span> }</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> </div><div class="line"><a name="l00394"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829"> 394</a></span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnnSerializer::DataLayout</a> dataLayout)</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> {</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  {</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keywordflow">case</span> armnnSerializer::DataLayout::DataLayout_NHWC:</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keywordflow">case</span> armnnSerializer::DataLayout::DataLayout_NCHW:</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  }</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> }</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span> </div><div class="line"><a name="l00406"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.xhtml#a2ee1264a9803ff8dc1323a26f1f4c986"> 406</a></span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a> <a class="code" href="namespacearmnn_deserializer.xhtml#a2ee1264a9803ff8dc1323a26f1f4c986">ToActivationFunction</a>(<a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnnSerializer::ActivationFunction</a> <span class="keyword">function</span>)</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span> {</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keywordflow">switch</span> (<span class="keyword">function</span>)</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  {</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Sigmoid:</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a>;</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_TanH:</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e">armnn::ActivationFunction::TanH</a>;</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Linear:</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b">armnn::ActivationFunction::Linear</a>;</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_ReLu:</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559">armnn::ActivationFunction::ReLu</a>;</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_BoundedReLu:</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a>;</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_LeakyReLu:</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaacb7667f5ec2f6e8a5943b781ba6c2735">armnn::ActivationFunction::LeakyReLu</a>;</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Abs:</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">armnn::ActivationFunction::Abs</a>;</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Sqrt:</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">armnn::ActivationFunction::Sqrt</a>;</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Square:</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaceb46ca115d05c51aa5a16a8867c3304">armnn::ActivationFunction::Square</a>;</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_Elu:</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaed67cf7d54c570e4c4891800f085f41d">armnn::ActivationFunction::Elu</a>;</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="keywordflow">case</span> armnnSerializer::ActivationFunction_HardSwish:</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa0877e5b3fbe9d7569df6399609ed0186">armnn::ActivationFunction::HardSwish</a>;</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a>;</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  }</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span> }</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div><div class="line"><a name="l00437"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.xhtml#a8fb47fe218330370a5c9c066ac1571ea"> 437</a></span> <a class="code" href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeae">armnn::ArgMinMaxFunction</a> <a class="code" href="namespacearmnn_deserializer.xhtml#a8fb47fe218330370a5c9c066ac1571ea">ToArgMinMaxFunction</a>(<a class="code" href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeae">armnnSerializer::ArgMinMaxFunction</a> <span class="keyword">function</span>)</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> {</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="keywordflow">switch</span> (<span class="keyword">function</span>)</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>  <span class="keywordflow">case</span> armnnSerializer::ArgMinMaxFunction::ArgMinMaxFunction_Max:</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::ArgMinMaxFunction::Max</a>;</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <span class="keywordflow">case</span> armnnSerializer::ArgMinMaxFunction::ArgMinMaxFunction_Min:</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeaea78d811e98514cd165dda532286610fd2">armnn::ArgMinMaxFunction::Min</a>;</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  }</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span> }</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span> </div><div class="line"><a name="l00449"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.xhtml#a28f896fb78cdf6607b61c196c98b2570"> 449</a></span> <a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58c">armnn::ComparisonOperation</a> <a class="code" href="namespacearmnn_deserializer.xhtml#a28f896fb78cdf6607b61c196c98b2570">ToComparisonOperation</a>(<a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58c">armnnSerializer::ComparisonOperation</a> operation)</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>  <span class="keywordflow">switch</span> (operation)</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  {</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_Equal:</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">armnn::ComparisonOperation::Equal</a>;</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_Greater:</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a">armnn::ComparisonOperation::Greater</a>;</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_GreaterOrEqual:</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca6f2f0aefb3d22da0f3839453add5f937">armnn::ComparisonOperation::GreaterOrEqual</a>;</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_Less:</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca1cfdf0e8d0c87a228c1f40d9bee7888b">armnn::ComparisonOperation::Less</a>;</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_LessOrEqual:</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58caa4cbdbb6070a5abb35fc95ecf1e22c14">armnn::ComparisonOperation::LessOrEqual</a>;</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="keywordflow">case</span> armnnSerializer::ComparisonOperation::ComparisonOperation_NotEqual:</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca19bb0af2c3c530538cb41aff7f235b96">armnn::ComparisonOperation::NotEqual</a>;</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  }</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="namespacearmnn_deserializer.xhtml#a7c8f847778ed77469bd6ddbd5158ae4e"> 469</a></span> <a class="code" href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8">armnn::UnaryOperation</a> <a class="code" href="namespacearmnn_deserializer.xhtml#a7c8f847778ed77469bd6ddbd5158ae4e">ToUnaryOperation</a>(<a class="code" href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8">armnnSerializer::UnaryOperation</a> operation)</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span> {</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keywordflow">switch</span> (operation)</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="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Abs:</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">armnn::UnaryOperation::Abs</a>;</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Rsqrt:</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4">armnn::UnaryOperation::Rsqrt</a>;</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Sqrt:</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">armnn::UnaryOperation::Sqrt</a>;</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Exp:</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8acad39a154bffb61175f674d6eefaf6d0">armnn::UnaryOperation::Exp</a>;</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <span class="keywordflow">case</span> armnnSerializer::UnaryOperation::UnaryOperation_Neg:</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8afb278fa5defd7e699fcbc930c3e76ccd">armnn::UnaryOperation::Neg</a>;</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Unary operation unknown"</span>);</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  }</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span> }</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span> </div><div class="line"><a name="l00488"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.xhtml#a8b51e137fab21d758b965c6c6e3b02f3"> 488</a></span> <a class="code" href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4">armnn::ResizeMethod</a> <a class="code" href="namespacearmnn_deserializer.xhtml#a8b51e137fab21d758b965c6c6e3b02f3">ToResizeMethod</a>(<a class="code" href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4">armnnSerializer::ResizeMethod</a> method)</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> {</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <span class="keywordflow">switch</span> (method)</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>  <span class="keywordflow">case</span> armnnSerializer::ResizeMethod_NearestNeighbor:</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a>;</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <span class="keywordflow">case</span> armnnSerializer::ResizeMethod_Bilinear:</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a>;</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keywordflow">default</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#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a>;</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> </div><div class="line"><a name="l00501"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1"> 501</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a80888061963ddd18e87105807a035d9a">Deserializer::TensorRawPtr</a> tensorPtr)</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span> {</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> type;</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <a class="code" href="_deserializer_8cpp.xhtml#ae38d96fe05581ea025713b3e781c5a43">CHECK_TENSOR_PTR</a>(tensorPtr);</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span> </div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <span class="keywordflow">switch</span> (tensorPtr->dataType())</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  {</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="keywordflow">case</span> DataType_QAsymmS8:</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  type = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>;</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <span class="keywordflow">case</span> DataType_QuantisedAsymm8:</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <span class="keywordflow">case</span> DataType_QAsymmU8:</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  type = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>;</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <span class="keywordflow">case</span> DataType_QSymmS16:</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  <span class="keywordflow">case</span> DataType_QuantisedSymm16:</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  type = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>;</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="keywordflow">case</span> DataType_Signed32:</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  type = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>;</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <span class="keywordflow">case</span> DataType_Float32:</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  type = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>;</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  <span class="keywordflow">case</span> DataType_Float16:</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  type = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>;</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <span class="keywordflow">case</span> DataType_Boolean:</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  type = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a>;</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  {</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <a class="code" href="structarmnn_1_1_check_location.xhtml">CheckLocation</a> location = <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  boost::str(</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  boost::format(<span class="stringliteral">"Unsupported data type %1% = %2%. %3%"</span>) %</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  tensorPtr->dataType() %</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  EnumNameDataType(tensorPtr->dataType()) %</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#a5e3562cda960da001597e7dd5679b140">AsString</a>()));</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  }</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  }</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  <span class="keywordtype">float</span> quantizationScale = tensorPtr->quantizationScale();</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  int32_t quantizationOffset = tensorPtr->quantizationOffset();</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span> </div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  <span class="keyword">auto</span> dimensions = tensorPtr->dimensions();</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> size = dimensions->size();</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  std::vector<unsigned int> outputDims(dimensions->begin(), dimensions->begin() + size);</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span> </div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <span class="comment">// two statements (on purpose) for easier debugging:</span></div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> result(size,</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  outputDims.data(),</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  type,</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  quantizationScale,</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  quantizationOffset);</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span> }</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span> </div><div class="line"><a name="l00558"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24"> 558</a></span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a68b76ee033fdd629404369171c3d4f90">Deserializer::ConstTensorRawPtr</a> constTensorPtr)</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span> {</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <a class="code" href="_deserializer_8cpp.xhtml#a637ba180b64a3cd1a4f83d048a030772">CHECK_CONST_TENSOR_PTR</a>(constTensorPtr);</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(constTensorPtr->info());</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span> </div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  <span class="keywordflow">switch</span> (constTensorPtr->data_type())</div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  {</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <span class="keywordflow">case</span> ConstTensorData_ByteData:</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  {</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="keyword">auto</span> byteData = constTensorPtr->data_as_ByteData()->data();</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(byteData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(tensorInfo, byteData->data());</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  }</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <span class="keywordflow">case</span> ConstTensorData_ShortData:</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  {</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="keyword">auto</span> shortData = constTensorPtr->data_as_ShortData()->data();</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(shortData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(tensorInfo, shortData->data());</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  }</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  <span class="keywordflow">case</span> ConstTensorData_IntData:</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  {</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  <span class="keyword">auto</span> intData = constTensorPtr->data_as_IntData()->data();</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(intData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(tensorInfo, intData->data());</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  }</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <span class="keywordflow">case</span> ConstTensorData_LongData:</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  {</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  <span class="keyword">auto</span> longData = constTensorPtr->data_as_LongData()->data();</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a>(longData->size(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(tensorInfo, longData->data());</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  }</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  {</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <a class="code" href="structarmnn_1_1_check_location.xhtml">CheckLocation</a> location = <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  boost::str(boost::format(<span class="stringliteral">"Unsupported data type %1% = %2%. %3%"</span>) %</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  constTensorPtr->data_type() %</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  EnumNameConstTensorData(constTensorPtr->data_type()) %</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  location.<a class="code" href="structarmnn_1_1_check_location.xhtml#a5e3562cda960da001597e7dd5679b140">AsString</a>()));</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  }</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  }</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span> }</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span> </div><div class="line"><a name="l00601"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114"> 601</a></span> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">Deserializer::GetInputs</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr,</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span> {</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graphPtr, 0, layerIndex);</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  <span class="keyword">auto</span> layer = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graphPtr, layerIndex);</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& numInputs = layer->inputSlots()->size();</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span> </div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> result(numInputs);</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span> </div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<numInputs; ++i)</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  {</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="keyword">auto</span> inputId = <a class="code" href="_verification_helpers_8hpp.xhtml#aaef93dc9a69f51b59f3cdd0ff0165927">CHECKED_NON_NEGATIVE</a>(static_cast<int32_t></div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  (layer->inputSlots()->Get(i)->connection()->sourceLayerIndex()));</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  result[i] = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graphPtr, inputId)->outputSlots()->Get(0)->tensorInfo();</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  }</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span> }</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span> </div><div class="line"><a name="l00619"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9"> 619</a></span> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">Deserializer::GetOutputs</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a>& graphPtr,</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span> {</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graphPtr, 0, layerIndex);</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <span class="keyword">auto</span> layer = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graphPtr, layerIndex);</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& numOutputs = layer->outputSlots()->size();</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span> </div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">TensorRawPtrVector</a> result(numOutputs);</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span> </div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<numOutputs; ++i)</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  {</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  result[i] = layer->outputSlots()->Get(i)->tensorInfo();</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  }</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span> }</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span> </div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span> <span class="keywordtype">void</span> Deserializer::ParseUnsupportedLayer(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span> {</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graph, layerIndex)->layerName()->c_str();</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  boost::str(</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  boost::format(<span class="stringliteral">"Layer not supported. "</span></div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  <span class="stringliteral">"layerIndex: %1% "</span></div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  <span class="stringliteral">"layerName: %2% / %3%"</span>) %</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  layerIndex %</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  layerName %</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span> }</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span> </div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span> <span class="keywordtype">void</span> Deserializer::ResetParser()</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span> {</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  m_Network = <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a>(<span class="keyword">nullptr</span>, <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  m_InputBindings.clear();</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  m_OutputBindings.clear();</div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span> }</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span> </div><div class="line"><a name="l00656"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer.xhtml#a85f0c438b389992a68adeb6af59f362d"> 656</a></span> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer.xhtml">IDeserializer</a>* <a class="code" href="classarmnn_deserializer_1_1_i_deserializer.xhtml#a85f0c438b389992a68adeb6af59f362d">IDeserializer::CreateRaw</a>()</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span> {</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a43e0ec855f3a7ebf9f98fbee5321edcf">Deserializer</a>();</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span> }</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span> </div><div class="line"><a name="l00661"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer.xhtml#af116abd698a7feb92876ae48917005a4"> 661</a></span> <a class="code" href="namespacearmnn_deserializer.xhtml#ad33c6040680106b9af566d7269d8c949">IDeserializerPtr</a> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer.xhtml#af116abd698a7feb92876ae48917005a4">IDeserializer::Create</a>()</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span> {</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn_deserializer.xhtml#ad33c6040680106b9af566d7269d8c949">IDeserializerPtr</a>(<a class="code" href="classarmnn_deserializer_1_1_i_deserializer.xhtml#a85f0c438b389992a68adeb6af59f362d">CreateRaw</a>(), &<a class="code" href="classarmnn_deserializer_1_1_i_deserializer.xhtml#afe33a6c8701eff4d2f7233ce441e0426">IDeserializer::Destroy</a>);</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span> }</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span> </div><div class="line"><a name="l00666"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_i_deserializer.xhtml#afe33a6c8701eff4d2f7233ce441e0426"> 666</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer.xhtml#afe33a6c8701eff4d2f7233ce441e0426">IDeserializer::Destroy</a>(<a class="code" href="classarmnn_deserializer_1_1_i_deserializer.xhtml">IDeserializer</a>* parser)</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span> {</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  <span class="keyword">delete</span> parser;</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span> }</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span> </div><div class="line"><a name="l00671"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#ae8ee09f5e3e78ecfdf00acfdc37588dc"> 671</a></span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#ae8ee09f5e3e78ecfdf00acfdc37588dc">Deserializer::CreateNetworkFromBinary</a>(<span class="keyword">const</span> std::vector<uint8_t>& binaryContent)</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span> {</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  ResetParser();</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0ba4effa5ee7ef715b1f452365c41f97">LoadGraphFromBinary</a>(binaryContent.data(), binaryContent.size());</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <span class="keywordflow">return</span> CreateNetworkFromGraph(graph);</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span> }</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span> </div><div class="line"><a name="l00678"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#aba8f9e71e60dd58b6e1165b3accd43b8"> 678</a></span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#ae8ee09f5e3e78ecfdf00acfdc37588dc">Deserializer::CreateNetworkFromBinary</a>(std::istream& binaryContent)</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span> {</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  ResetParser();</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  std::vector<uint8_t> content((std::istreambuf_iterator<char>(binaryContent)), std::istreambuf_iterator<char>());</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0ba4effa5ee7ef715b1f452365c41f97">LoadGraphFromBinary</a>(content.data(), content.size());</div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  <span class="keywordflow">return</span> CreateNetworkFromGraph(graph);</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span> }</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span> </div><div class="line"><a name="l00686"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0ba4effa5ee7ef715b1f452365c41f97"> 686</a></span> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">Deserializer::GraphPtr</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0ba4effa5ee7ef715b1f452365c41f97">Deserializer::LoadGraphFromBinary</a>(<span class="keyword">const</span> uint8_t* binaryContent, <span class="keywordtype">size_t</span> len)</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span> {</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  <span class="keywordflow">if</span> (binaryContent == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  {</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(boost::str(boost::format(<span class="stringliteral">"Invalid (null) binary content %1%"</span>) %</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  }</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  flatbuffers::Verifier verifier(binaryContent, len);</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  <span class="keywordflow">if</span> (verifier.VerifyBuffer<SerializedGraph>() == <span class="keyword">false</span>)</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  {</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  boost::str(boost::format(<span class="stringliteral">"Buffer doesn't conform to the expected Armnn "</span></div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  <span class="stringliteral">"flatbuffers format. size:%1% %2%"</span>) %</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  len %</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  }</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keywordflow">return</span> GetSerializedGraph(binaryContent);</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span> }</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span> </div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> Deserializer::CreateNetworkFromGraph(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span> {</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  m_Network = INetwork::Create();</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  BOOST_ASSERT(graph != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex = 0;</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  <span class="keywordflow">for</span> (AnyLayer <span class="keyword">const</span>* layer : *graph->layers())</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  {</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <span class="keywordflow">if</span> (layer->layer_type() != Layer_InputLayer &&</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  layer->layer_type() != Layer_OutputLayer)</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  {</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  <span class="comment">// lookup and call the parser function</span></div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <span class="keyword">auto</span>& parserFunction = m_ParserFunctions[layer->layer_type()];</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  (this->*parserFunction)(graph, layerIndex);</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  }</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  ++layerIndex;</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  }</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span> </div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  SetupInputLayers(graph);</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  SetupOutputLayers(graph);</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span> </div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  <span class="comment">// establish the connections from the layer outputs to the inputs of the subsequent layers</span></div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& graphIt : m_GraphConnections)</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  {</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  Connections& connections = graphIt.second;</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& outputIt : connections.outputSlots)</div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  {</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSlotIndex = outputIt.first;</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  <a class="code" href="classarmnn_1_1_i_output_slot.xhtml">IOutputSlot</a>* outputSlot = outputIt.second;</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  <span class="keywordflow">if</span> (connections.inputSlots.find(outputSlotIndex) != connections.inputSlots.end())</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  {</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  <span class="keywordflow">for</span> (<a class="code" href="classarmnn_1_1_i_input_slot.xhtml">IInputSlot</a>* inputSlot : connections.inputSlots[outputSlotIndex])</div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  {</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  outputSlot-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(*inputSlot);</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  }</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  }</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  }</div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  }</div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span> </div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  <span class="keywordflow">return</span> std::move(m_Network);</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span> }</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span> </div><div class="line"><a name="l00746"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#a66c5e4250559faefd7f0fa35ccbdc9eb"> 746</a></span> <a class="code" href="structarmnn_deserializer_1_1_binding_point_info.xhtml">BindingPointInfo</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a66c5e4250559faefd7f0fa35ccbdc9eb">Deserializer::GetNetworkInputBindingInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex,</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  <span class="keyword">const</span> std::string& name)<span class="keyword"> const</span></div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span> <span class="keyword"></span>{</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> inputBinding : m_InputBindings)</div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  {</div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <span class="keywordflow">if</span> (inputBinding.first == name)</div><div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  {</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  <span class="keywordflow">return</span> inputBinding.second;</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  }</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  }</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  boost::str(</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  boost::format(<span class="stringliteral">"No input binding found for layer:%1% / %2%"</span>) %</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  name %</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span> }</div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span> </div><div class="line"><a name="l00764"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#ae9cf8ca62e8da6d21e08dc130f68dce4"> 764</a></span> <a class="code" href="structarmnn_deserializer_1_1_binding_point_info.xhtml">BindingPointInfo</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#ae9cf8ca62e8da6d21e08dc130f68dce4">Deserializer::GetNetworkOutputBindingInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex,</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  <span class="keyword">const</span> std::string& name)<span class="keyword"> const</span></div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span> <span class="keyword"></span>{</div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> outputBinding : m_OutputBindings)</div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  {</div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  <span class="keywordflow">if</span> (outputBinding.first == name)</div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  {</div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  <span class="keywordflow">return</span> outputBinding.second;</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  }</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  }</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  boost::str(</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  boost::format(<span class="stringliteral">"No output binding found for layer:%1% / %2%"</span>) %</div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  name %</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span> }</div><div class="line"><a name="l00781"></a><span class="lineno"> 781</span> </div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> Deserializer::GetInputLayerInVector(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">int</span> targetId)</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span> {</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < graph->layers()->size(); i++)</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  {</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  <span class="keyword">auto</span> layer = graph->layers()->Get(i);</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  <span class="keywordflow">if</span> (layer->layer_type() == Layer::Layer_InputLayer)</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  {</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  <span class="keyword">auto</span> layerBindingId = layer->layer_as_InputLayer()->base()->layerBindingId();</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <span class="keywordflow">if</span> (layerBindingId == targetId)</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  {</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <span class="keywordflow">return</span> i;</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  }</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  }</div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  }</div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(<span class="stringliteral">"Input layer with given layerBindingId not found"</span>);</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span> }</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span> </div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> Deserializer::GetOutputLayerInVector(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">int</span> targetId)</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span> {</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < graph->layers()->size(); i++)</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  {</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <span class="keyword">auto</span> layer = graph->layers()->Get(i);</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  <span class="keywordflow">if</span> (layer->layer_type() == Layer::Layer_OutputLayer)</div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  {</div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <span class="keyword">auto</span> layerBindingId = layer->layer_as_OutputLayer()->base()->layerBindingId();</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  <span class="keywordflow">if</span> (layerBindingId == targetId)</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  {</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  <span class="keywordflow">return</span> i;</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  }</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  }</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  }</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(<span class="stringliteral">"Output layer with given layerBindingId not found"</span>);</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span> }</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span> </div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> Deserializer::GetLayerIndexInVector(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> targetIndex)</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span> {</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < graph->layers()->size(); i++)</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  {</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> layer = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graph, i);</div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  <span class="keywordflow">if</span> (layer->index() == targetIndex)</div><div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  {</div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  <span class="keywordflow">return</span> i;</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  }</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  }</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(<span class="stringliteral">"Layer with given index not found"</span>);</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span> }</div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span> </div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span> Deserializer::FeatureVersions Deserializer::GetFeatureVersions(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div><div class="line"><a name="l00830"></a><span class="lineno"> 830</span> {</div><div class="line"><a name="l00831"></a><span class="lineno"> 831</span>  Deserializer::FeatureVersions versions;</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span> </div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span>  <span class="keywordflow">if</span> (graph->featureVersions())</div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  {</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  versions.m_BindingIdScheme = graph->featureVersions()->bindingIdsScheme();</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  }</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span> </div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  <span class="keywordflow">return</span> versions;</div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span> }</div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span> </div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span> <span class="keywordtype">void</span> Deserializer::SetupInputLayers(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span> {</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  <a class="code" href="_deserializer_8cpp.xhtml#ab90eef134463f7b44cd4c9cfb2529825">CHECK_GRAPH</a>(graph, 0);</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = graph->inputIds()->size();</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  m_InputBindings.clear();</div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  m_InputBindings.reserve(numInputs);</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span> </div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputs; i++)</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  {</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputLayerIndex = 0xFFFFFFFF;</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <span class="keywordflow">if</span> (GetFeatureVersions(graph).m_BindingIdScheme == 0)</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  {</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputId = <a class="code" href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">boost::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(graph->inputIds()->Get(i));</div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  inputLayerIndex = GetLayerIndexInVector(graph, inputId);</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  }</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  {</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> inputId = graph->inputIds()->Get(i);</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  inputLayerIndex = GetInputLayerInVector(graph, inputId);</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  }</div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span> </div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graph, inputLayerIndex);</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span> </div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  <span class="comment">// GetBindingLayerInfo expect the index to be index in the vector not index property on each layer base</span></div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#afcc87bf0e20779861dd5d01a4bedcda9">GetBindingLayerInfo</a>(graph, inputLayerIndex);</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  BOOST_ASSERT_MSG(baseLayer->layerName()->c_str(), <span class="stringliteral">"Input has no name."</span>);</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span> </div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* inputLayer =</div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  m_Network->AddInputLayer(bindingId, baseLayer->layerName()->c_str());</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span> </div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& tensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(baseLayer->outputSlots()->Get(0)->tensorInfo());</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  RegisterOutputSlots(graph, inputLayerIndex, inputLayer);</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span> </div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  <a class="code" href="structarmnn_deserializer_1_1_binding_point_info.xhtml">BindingPointInfo</a> bindingInfo = {bindingId, tensorInfo};</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  m_InputBindings.push_back(std::make_pair(baseLayer->layerName()->c_str(), bindingInfo));</div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  }</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span> }</div><div class="line"><a name="l00879"></a><span class="lineno"> 879</span> </div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span> <span class="keywordtype">void</span> Deserializer::SetupOutputLayers(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph)</div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span> {</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  <a class="code" href="_deserializer_8cpp.xhtml#ab90eef134463f7b44cd4c9cfb2529825">CHECK_GRAPH</a>(graph, 0);</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputs = graph->outputIds()->size();</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  m_OutputBindings.clear();</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  m_OutputBindings.reserve(numOutputs);</div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span> </div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numOutputs; i++)</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  {</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputLayerIndex = 0xFFFFFFFF;</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  <span class="keywordflow">if</span> (GetFeatureVersions(graph).m_BindingIdScheme == 0)</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  {</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputId = <a class="code" href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">boost::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(graph->outputIds()->Get(i));</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  outputLayerIndex = GetLayerIndexInVector(graph, outputId);</div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  }</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  {</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> outputId = graph->outputIds()->Get(i);</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  outputLayerIndex = GetOutputLayerInVector(graph, outputId);</div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span>  }</div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span> </div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graph, outputLayerIndex);</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span> </div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <span class="comment">// GetBindingLayerInfo expect the index to be index in the vector not index property on each layer base</span></div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> bindingId = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#afcc87bf0e20779861dd5d01a4bedcda9">GetBindingLayerInfo</a>(graph, outputLayerIndex);</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  BOOST_ASSERT_MSG(baseLayer->layerName()->c_str(), <span class="stringliteral">"Input has no name."</span>);</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span> </div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* outputLayer =</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  m_Network->AddOutputLayer(bindingId, baseLayer->layerName()->c_str());</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span> </div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  RegisterInputSlots(graph, outputLayerIndex, outputLayer);</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span> </div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> sourceLayerIndex =</div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  GetLayerIndexInVector(graph, baseLayer->inputSlots()->Get(0)->connection()->sourceLayerIndex());</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> sourceBaseLayer = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graph, sourceLayerIndex);</div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& tensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(sourceBaseLayer->outputSlots()->Get(0)->tensorInfo());</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span> </div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  <a class="code" href="structarmnn_deserializer_1_1_binding_point_info.xhtml">BindingPointInfo</a> bindingInfo = {bindingId, tensorInfo};</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  m_OutputBindings.push_back(std::make_pair(baseLayer->layerName()->c_str(), bindingInfo));</div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  }</div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span> }</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span> </div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span> <span class="keywordtype">void</span> Deserializer::RegisterOutputSlots(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph,</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  uint32_t layerIndex,</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer)</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span> {</div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  BOOST_ASSERT(layer != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graph, layerIndex);</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  <span class="keywordflow">if</span> (baseLayer->outputSlots()->size() != layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>())</div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  {</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  boost::str(boost::format(<span class="stringliteral">"The number of outputslots (%1%) does not match the number expected (%2%)"</span></div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  <span class="stringliteral">" for layer index: %3% %4%"</span>) %</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  baseLayer->outputSlots()->size() %</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>() %</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  layerIndex %</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  }</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span> </div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>(); ++i)</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  {</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> slotIndex = baseLayer->outputSlots()->Get(i)->index();</div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  <a class="code" href="classarmnn_1_1_i_output_slot.xhtml">armnn::IOutputSlot</a>* outputSlot = &(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(slotIndex));</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  <span class="comment">// layerIndex is not necessarily the same as baseLayer->index(). The latter is needed here</span></div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  RegisterOutputSlotOfConnection(baseLayer->index(), slotIndex, outputSlot);</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  }</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span> }</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span> </div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span> <span class="keywordtype">void</span> Deserializer::RegisterInputSlots(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph,</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  uint32_t layerIndex,</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer)</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span> {</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  BOOST_ASSERT(layer != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a91ade61b5704e4f2c38c263c2be148ef">LayerBaseRawPtr</a> baseLayer = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">GetBaseLayer</a>(graph, layerIndex);</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  <span class="keywordflow">if</span> (baseLayer->inputSlots()->size() != layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>())</div><div class="line"><a name="l00957"></a><span class="lineno"> 957</span>  {</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  boost::str(boost::format(<span class="stringliteral">"The number of inputslots (%1%) does not match the number expected (%2%)"</span></div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  <span class="stringliteral">" for layer index:%3% %4%"</span>) %</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  baseLayer->inputSlots()->size() %</div><div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>() %</div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span>  layerIndex %</div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  }</div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span> </div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>(); ++i)</div><div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  {</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  <span class="keyword">auto</span> fbInputSlot = baseLayer->inputSlots()->Get(i);</div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  <span class="keyword">auto</span> fbConnection = fbInputSlot->connection();</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  <a class="code" href="classarmnn_1_1_i_input_slot.xhtml">armnn::IInputSlot</a>* inputSlot = &(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(fbInputSlot->index()));</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  RegisterInputSlotOfConnection(fbConnection->sourceLayerIndex(), fbConnection->outputSlotIndex(), inputSlot);</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  }</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span> }</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span> </div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span> <span class="keywordtype">void</span> Deserializer::RegisterInputSlotOfConnection(uint32_t sourceLayerIndex,</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  uint32_t outputSlotIndex,</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  <a class="code" href="classarmnn_1_1_i_input_slot.xhtml">armnn::IInputSlot</a>* inputSlot)</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span> {</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  <span class="keywordflow">if</span> (m_GraphConnections.find(sourceLayerIndex) == m_GraphConnections.end())</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  {</div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  m_GraphConnections[sourceLayerIndex] = Connections();</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  }</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span> </div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  Connections& connections = m_GraphConnections[sourceLayerIndex];</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  <span class="keywordflow">if</span> (connections.inputSlots.find(outputSlotIndex) == connections.inputSlots.end())</div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  {</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  connections.inputSlots[outputSlotIndex] = {inputSlot};</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  }</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  {</div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  connections.inputSlots[outputSlotIndex].push_back(inputSlot);</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span>  }</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span> }</div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span> </div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span> <span class="keywordtype">void</span> Deserializer::RegisterOutputSlotOfConnection(uint32_t sourceLayerIndex,</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  uint32_t outputSlotIndex,</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  <a class="code" href="classarmnn_1_1_i_output_slot.xhtml">armnn::IOutputSlot</a>* outputSlot)</div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span> {</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  <span class="keywordflow">if</span> (m_GraphConnections.find(sourceLayerIndex) == m_GraphConnections.end())</div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>  {</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  m_GraphConnections[sourceLayerIndex] = Connections();</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>  }</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span> </div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  Connections& connections = m_GraphConnections[sourceLayerIndex];</div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>  <span class="keywordflow">if</span> (connections.outputSlots.find(outputSlotIndex) != connections.outputSlots.end())</div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  {</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(<span class="stringliteral">"Same output slot index processed twice"</span>);</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  }</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span> </div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>  connections.outputSlots[outputSlotIndex] = outputSlot;</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span> }</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span> </div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span> <span class="keywordtype">void</span> Deserializer::ParseAbs(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">armnnDeserializer::Deserializer::GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span> {</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span> </div><div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01023"></a><span class="lineno"> 1023</span> </div><div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01025"></a><span class="lineno"> 1025</span> </div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>  <a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.xhtml">armnn::ElementwiseUnaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">armnn::UnaryOperation::Abs</a>);</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span> </div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01033"></a><span class="lineno"> 1033</span> }</div><div class="line"><a name="l01034"></a><span class="lineno"> 1034</span> </div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span> <span class="keywordtype">void</span> Deserializer::ParseActivation(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01036"></a><span class="lineno"> 1036</span> {</div><div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span> </div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span> </div><div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_ActivationLayer();</div><div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span> </div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a> descriptor;</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#a2ee1264a9803ff8dc1323a26f1f4c986">ToActivationFunction</a>(serializerDescriptor->activationFunction());</div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a017b2990003a014234f13e999dc7c689">m_A</a> = serializerDescriptor->a();</div><div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a28c4c9cb15f6be3499abbc46b356060b">m_B</a> = serializerDescriptor->b();</div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span> </div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddActivationLayer(descriptor,</div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>  layerName.c_str());</div><div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01058"></a><span class="lineno"> 1058</span> </div><div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01061"></a><span class="lineno"> 1061</span> }</div><div class="line"><a name="l01062"></a><span class="lineno"> 1062</span> </div><div class="line"><a name="l01063"></a><span class="lineno"> 1063</span> <span class="keywordtype">void</span> Deserializer::ParseAdd(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01064"></a><span class="lineno"> 1064</span> {</div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</span> </div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01072"></a><span class="lineno"> 1072</span> </div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddAdditionLayer(layerName.c_str());</div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span> </div><div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01078"></a><span class="lineno"> 1078</span> </div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01081"></a><span class="lineno"> 1081</span> }</div><div class="line"><a name="l01082"></a><span class="lineno"> 1082</span> </div><div class="line"><a name="l01083"></a><span class="lineno"> 1083</span> <span class="keywordtype">void</span> Deserializer::ParseArgMinMax(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01084"></a><span class="lineno"> 1084</span> {</div><div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01089"></a><span class="lineno"> 1089</span> </div><div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01092"></a><span class="lineno"> 1092</span> </div><div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_ArgMinMaxLayer();</div><div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span> </div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>  <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a> descriptor;</div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml#ab1ae6f520bb1a4da191a0ae907477f23">m_Function</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#a8fb47fe218330370a5c9c066ac1571ea">ToArgMinMaxFunction</a>(serializerDescriptor->argMinMaxFunction());</div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = serializerDescriptor->axis();</div><div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddArgMinMaxLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</span> </div><div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01104"></a><span class="lineno"> 1104</span> </div><div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01107"></a><span class="lineno"> 1107</span> }</div><div class="line"><a name="l01108"></a><span class="lineno"> 1108</span> </div><div class="line"><a name="l01109"></a><span class="lineno"> 1109</span> <span class="keywordtype">void</span> Deserializer::ParseBatchToSpaceNd(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01110"></a><span class="lineno"> 1110</span> {</div><div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01112"></a><span class="lineno"> 1112</span> </div><div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01115"></a><span class="lineno"> 1115</span> </div><div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01118"></a><span class="lineno"> 1118</span> </div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_BatchToSpaceNdLayer()->descriptor();</div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  <span class="keyword">auto</span> flatBufferCrops = flatBufferDescriptor->crops();</div><div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>  <span class="keyword">auto</span> flatBufferBlockShape = flatBufferDescriptor->blockShape();</div><div class="line"><a name="l01122"></a><span class="lineno"> 1122</span> </div><div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>  <span class="keywordflow">if</span> (flatBufferCrops->Length() % 2 != 0)</div><div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>  {</div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(boost::str(</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>  boost::format(<span class="stringliteral">"The size of crops must be divisible by 2 %1%"</span>) % <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>  }</div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span> </div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>  std::vector<std::pair<unsigned int, unsigned int>> crops;</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>  crops.reserve(flatBufferCrops->Length() / 2);</div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < flatBufferCrops->Length() - 1; i += 2)</div><div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>  {</div><div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>  crops.emplace_back(flatBufferCrops->Get(i), flatBufferCrops->Get(i+1));</div><div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>  }</div><div class="line"><a name="l01135"></a><span class="lineno"> 1135</span> </div><div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>  <a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">armnn::BatchToSpaceNdDescriptor</a> descriptor;</div><div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div><div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> =</div><div class="line"><a name="l01139"></a><span class="lineno"> 1139</span>  std::vector<unsigned int>(flatBufferBlockShape->begin(), flatBufferBlockShape->end());</div><div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a3941f674c071c9503e00d2b59e92e454">m_Crops</a> = crops;</div><div class="line"><a name="l01141"></a><span class="lineno"> 1141</span> </div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddBatchToSpaceNdLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span> </div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01146"></a><span class="lineno"> 1146</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01147"></a><span class="lineno"> 1147</span> </div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01150"></a><span class="lineno"> 1150</span> }</div><div class="line"><a name="l01151"></a><span class="lineno"> 1151</span> </div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span> <span class="keywordtype">void</span> Deserializer::ParseBatchNormalization(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01153"></a><span class="lineno"> 1153</span> {</div><div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01155"></a><span class="lineno"> 1155</span> </div><div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span> </div><div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span> </div><div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span> </div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_BatchNormalizationLayer();</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span> </div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>  <a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml">armnn::BatchNormalizationDescriptor</a> descriptor;</div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a> = serializerDescriptor->eps();</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div><div class="line"><a name="l01171"></a><span class="lineno"> 1171</span> </div><div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> mean = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerLayer->mean());</div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> variance = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerLayer->variance());</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> beta = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerLayer->beta());</div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> gamma = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerLayer->gamma());</div><div class="line"><a name="l01176"></a><span class="lineno"> 1176</span> </div><div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddBatchNormalizationLayer(descriptor,</div><div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>  mean,</div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>  variance,</div><div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  beta,</div><div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>  gamma,</div><div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>  layerName.c_str());</div><div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>  layer->GetOutputSlot(0).SetTensorInfo(outputInfo);</div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span> </div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01187"></a><span class="lineno"> 1187</span> }</div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span> </div><div class="line"><a name="l01189"></a><span class="lineno"> 1189</span> <span class="keywordtype">void</span> Deserializer::ParseConstant(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span> {</div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01193"></a><span class="lineno"> 1193</span> </div><div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span> </div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01198"></a><span class="lineno"> 1198</span> </div><div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_ConstantLayer();</div><div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>  <span class="keyword">auto</span> serializerInput = serializerLayer->input();</div><div class="line"><a name="l01201"></a><span class="lineno"> 1201</span> </div><div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> input = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerInput);</div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span> </div><div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddConstantLayer(input, layerName.c_str());</div><div class="line"><a name="l01205"></a><span class="lineno"> 1205</span> </div><div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span> </div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span> }</div><div class="line"><a name="l01211"></a><span class="lineno"> 1211</span> </div><div class="line"><a name="l01212"></a><span class="lineno"> 1212</span> <span class="keywordtype">void</span> Deserializer::ParseConvolution2d(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01213"></a><span class="lineno"> 1213</span> {</div><div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01216"></a><span class="lineno"> 1216</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01218"></a><span class="lineno"> 1218</span> </div><div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01221"></a><span class="lineno"> 1221</span> </div><div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_Convolution2dLayer();</div><div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div><div class="line"><a name="l01225"></a><span class="lineno"> 1225</span> </div><div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = serializerDescriptor->padLeft();</div><div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = serializerDescriptor->padRight();</div><div class="line"><a name="l01229"></a><span class="lineno"> 1229</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = serializerDescriptor->padTop();</div><div class="line"><a name="l01230"></a><span class="lineno"> 1230</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = serializerDescriptor->padBottom();</div><div class="line"><a name="l01231"></a><span class="lineno"> 1231</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = serializerDescriptor->strideX();</div><div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = serializerDescriptor->strideY();;</div><div class="line"><a name="l01233"></a><span class="lineno"> 1233</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = serializerDescriptor->dilationX();</div><div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = serializerDescriptor->dilationY();;</div><div class="line"><a name="l01235"></a><span class="lineno"> 1235</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = serializerDescriptor->biasEnabled();;</div><div class="line"><a name="l01236"></a><span class="lineno"> 1236</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div><div class="line"><a name="l01237"></a><span class="lineno"> 1237</span> </div><div class="line"><a name="l01238"></a><span class="lineno"> 1238</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerLayer->weights());</div><div class="line"><a name="l01239"></a><span class="lineno"> 1239</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> biases;</div><div class="line"><a name="l01240"></a><span class="lineno"> 1240</span> </div><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<armnn::ConstTensor></a> optionalBiases = <a class="code" href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a>();</div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div><div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>  {</div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>  biases = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerLayer->biases());</div><div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>  optionalBiases = <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<armnn::ConstTensor></a>(biases);</div><div class="line"><a name="l01246"></a><span class="lineno"> 1246</span>  }</div><div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddConvolution2dLayer(descriptor,</div><div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>  weights,</div><div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>  optionalBiases,</div><div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>  layerName.c_str());</div><div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>  layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);</div><div class="line"><a name="l01253"></a><span class="lineno"> 1253</span> </div><div class="line"><a name="l01254"></a><span class="lineno"> 1254</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01256"></a><span class="lineno"> 1256</span> }</div><div class="line"><a name="l01257"></a><span class="lineno"> 1257</span> </div><div class="line"><a name="l01258"></a><span class="lineno"> 1258</span> <span class="keywordtype">void</span> Deserializer::ParseDepthToSpace(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01259"></a><span class="lineno"> 1259</span> {</div><div class="line"><a name="l01260"></a><span class="lineno"> 1260</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01261"></a><span class="lineno"> 1261</span> </div><div class="line"><a name="l01262"></a><span class="lineno"> 1262</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01264"></a><span class="lineno"> 1264</span> </div><div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01267"></a><span class="lineno"> 1267</span> </div><div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>  <span class="keyword">auto</span> fbDescriptor = graph->layers()->Get(layerIndex)->layer_as_DepthToSpaceLayer()->descriptor();</div><div class="line"><a name="l01269"></a><span class="lineno"> 1269</span> </div><div class="line"><a name="l01270"></a><span class="lineno"> 1270</span>  <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml">armnn::DepthToSpaceDescriptor</a> descriptor;</div><div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a> = fbDescriptor->blockSize();</div><div class="line"><a name="l01272"></a><span class="lineno"> 1272</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(fbDescriptor->dataLayout());</div><div class="line"><a name="l01273"></a><span class="lineno"> 1273</span> </div><div class="line"><a name="l01274"></a><span class="lineno"> 1274</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01275"></a><span class="lineno"> 1275</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddDepthToSpaceLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01276"></a><span class="lineno"> 1276</span> </div><div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01278"></a><span class="lineno"> 1278</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01279"></a><span class="lineno"> 1279</span> </div><div class="line"><a name="l01280"></a><span class="lineno"> 1280</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01282"></a><span class="lineno"> 1282</span> }</div><div class="line"><a name="l01283"></a><span class="lineno"> 1283</span> </div><div class="line"><a name="l01284"></a><span class="lineno"> 1284</span> <span class="keywordtype">void</span> Deserializer::ParseDepthwiseConvolution2d(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01285"></a><span class="lineno"> 1285</span> {</div><div class="line"><a name="l01286"></a><span class="lineno"> 1286</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01287"></a><span class="lineno"> 1287</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01288"></a><span class="lineno"> 1288</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01289"></a><span class="lineno"> 1289</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01290"></a><span class="lineno"> 1290</span> </div><div class="line"><a name="l01291"></a><span class="lineno"> 1291</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01292"></a><span class="lineno"> 1292</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01293"></a><span class="lineno"> 1293</span> </div><div class="line"><a name="l01294"></a><span class="lineno"> 1294</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_DepthwiseConvolution2dLayer();</div><div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01296"></a><span class="lineno"> 1296</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div><div class="line"><a name="l01297"></a><span class="lineno"> 1297</span> </div><div class="line"><a name="l01298"></a><span class="lineno"> 1298</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l01299"></a><span class="lineno"> 1299</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = serializerDescriptor->padLeft();</div><div class="line"><a name="l01300"></a><span class="lineno"> 1300</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = serializerDescriptor->padRight();</div><div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = serializerDescriptor->padTop();</div><div class="line"><a name="l01302"></a><span class="lineno"> 1302</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = serializerDescriptor->padBottom();</div><div class="line"><a name="l01303"></a><span class="lineno"> 1303</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = serializerDescriptor->strideX();</div><div class="line"><a name="l01304"></a><span class="lineno"> 1304</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = serializerDescriptor->strideY();</div><div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = serializerDescriptor->dilationX();</div><div class="line"><a name="l01306"></a><span class="lineno"> 1306</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = serializerDescriptor->dilationY();</div><div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = serializerDescriptor->biasEnabled();;</div><div class="line"><a name="l01308"></a><span class="lineno"> 1308</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div><div class="line"><a name="l01309"></a><span class="lineno"> 1309</span> </div><div class="line"><a name="l01310"></a><span class="lineno"> 1310</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerLayer->weights());</div><div class="line"><a name="l01311"></a><span class="lineno"> 1311</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> biases;</div><div class="line"><a name="l01312"></a><span class="lineno"> 1312</span> </div><div class="line"><a name="l01313"></a><span class="lineno"> 1313</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<armnn::ConstTensor></a> optionalBiases = <a class="code" href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a>();</div><div class="line"><a name="l01314"></a><span class="lineno"> 1314</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div><div class="line"><a name="l01315"></a><span class="lineno"> 1315</span>  {</div><div class="line"><a name="l01316"></a><span class="lineno"> 1316</span>  biases = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerLayer->biases());</div><div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>  optionalBiases = <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<armnn::ConstTensor></a>(biases);</div><div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>  }</div><div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddDepthwiseConvolution2dLayer(descriptor,</div><div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>  weights,</div><div class="line"><a name="l01321"></a><span class="lineno"> 1321</span>  optionalBiases,</div><div class="line"><a name="l01322"></a><span class="lineno"> 1322</span>  layerName.c_str());</div><div class="line"><a name="l01323"></a><span class="lineno"> 1323</span> </div><div class="line"><a name="l01324"></a><span class="lineno"> 1324</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>  layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);</div><div class="line"><a name="l01326"></a><span class="lineno"> 1326</span> </div><div class="line"><a name="l01327"></a><span class="lineno"> 1327</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01328"></a><span class="lineno"> 1328</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01329"></a><span class="lineno"> 1329</span> }</div><div class="line"><a name="l01330"></a><span class="lineno"> 1330</span> </div><div class="line"><a name="l01331"></a><span class="lineno"> 1331</span> <span class="keywordtype">void</span> Deserializer::ParseDetectionPostProcess(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01332"></a><span class="lineno"> 1332</span> {</div><div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l01337"></a><span class="lineno"> 1337</span> </div><div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 4);</div><div class="line"><a name="l01340"></a><span class="lineno"> 1340</span> </div><div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_DetectionPostProcessLayer();</div><div class="line"><a name="l01342"></a><span class="lineno"> 1342</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div><div class="line"><a name="l01344"></a><span class="lineno"> 1344</span> </div><div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>  <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a> descriptor;</div><div class="line"><a name="l01346"></a><span class="lineno"> 1346</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">m_MaxDetections</a> = flatBufferDescriptor->maxDetections();</div><div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a9ae2c9796692ebeafe19a4d3f09c8ea8">m_MaxClassesPerDetection</a> = flatBufferDescriptor->maxClassesPerDetection();</div><div class="line"><a name="l01348"></a><span class="lineno"> 1348</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7e2f87544b8bc7e497e1dec8d3ca4055">m_DetectionsPerClass</a> = flatBufferDescriptor->detectionsPerClass();</div><div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a4392dd6b4862cc9cf95ae8f1001ba592">m_NmsScoreThreshold</a> = flatBufferDescriptor->nmsScoreThreshold();</div><div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a53c8a7f33a40e1e240256bcfcf41b101">m_NmsIouThreshold</a> = flatBufferDescriptor->nmsIouThreshold();</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a3a04b0ccee4bb2f21721ee5045e83df4">m_NumClasses</a> = flatBufferDescriptor->numClasses();</div><div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">m_UseRegularNms</a> = flatBufferDescriptor->useRegularNms();</div><div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae64523937ea910030ad66fee6fddd51f">m_ScaleX</a> = flatBufferDescriptor->scaleX();</div><div class="line"><a name="l01354"></a><span class="lineno"> 1354</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7a2156ec7d9c012ce00bbcc6afcb9028">m_ScaleY</a> = flatBufferDescriptor->scaleY();</div><div class="line"><a name="l01355"></a><span class="lineno"> 1355</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ab509802c659de19929f18bad14a35c58">m_ScaleW</a> = flatBufferDescriptor->scaleW();</div><div class="line"><a name="l01356"></a><span class="lineno"> 1356</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#aa61510cbd529870182e918ac6e8b9d72">m_ScaleH</a> = flatBufferDescriptor->scaleH();</div><div class="line"><a name="l01357"></a><span class="lineno"> 1357</span> </div><div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferLayer->anchors());</div><div class="line"><a name="l01359"></a><span class="lineno"> 1359</span> </div><div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddDetectionPostProcessLayer(descriptor,</div><div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>  anchors,</div><div class="line"><a name="l01362"></a><span class="lineno"> 1362</span>  layerName.c_str());</div><div class="line"><a name="l01363"></a><span class="lineno"> 1363</span> </div><div class="line"><a name="l01364"></a><span class="lineno"> 1364</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < 4; i++)</div><div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>  {</div><div class="line"><a name="l01366"></a><span class="lineno"> 1366</span>  layer->GetOutputSlot(i).SetTensorInfo(<a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[i]));</div><div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>  }</div><div class="line"><a name="l01368"></a><span class="lineno"> 1368</span> </div><div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01371"></a><span class="lineno"> 1371</span> }</div><div class="line"><a name="l01372"></a><span class="lineno"> 1372</span> </div><div class="line"><a name="l01373"></a><span class="lineno"> 1373</span> <span class="keywordtype">void</span> Deserializer::ParseDivision(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01374"></a><span class="lineno"> 1374</span> {</div><div class="line"><a name="l01375"></a><span class="lineno"> 1375</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l01379"></a><span class="lineno"> 1379</span> </div><div class="line"><a name="l01380"></a><span class="lineno"> 1380</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01381"></a><span class="lineno"> 1381</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01382"></a><span class="lineno"> 1382</span> </div><div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddDivisionLayer(layerName.c_str());</div><div class="line"><a name="l01385"></a><span class="lineno"> 1385</span> </div><div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01388"></a><span class="lineno"> 1388</span> </div><div class="line"><a name="l01389"></a><span class="lineno"> 1389</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01391"></a><span class="lineno"> 1391</span> }</div><div class="line"><a name="l01392"></a><span class="lineno"> 1392</span> </div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span> <span class="keywordtype">void</span> Deserializer::ParseEqual(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01394"></a><span class="lineno"> 1394</span> {</div><div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l01399"></a><span class="lineno"> 1399</span> </div><div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01402"></a><span class="lineno"> 1402</span> </div><div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>  <a class="code" href="structarmnn_1_1_comparison_descriptor.xhtml">armnn::ComparisonDescriptor</a> descriptor(<a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">armnn::ComparisonOperation::Equal</a>);</div><div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddComparisonLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01406"></a><span class="lineno"> 1406</span> </div><div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01409"></a><span class="lineno"> 1409</span> </div><div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01412"></a><span class="lineno"> 1412</span> }</div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span> </div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span> <span class="keywordtype">void</span> Deserializer::ParseGreater(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span> {</div><div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l01420"></a><span class="lineno"> 1420</span> </div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span> </div><div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>  <a class="code" href="structarmnn_1_1_comparison_descriptor.xhtml">armnn::ComparisonDescriptor</a> descriptor(<a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a">armnn::ComparisonOperation::Greater</a>);</div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddComparisonLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01427"></a><span class="lineno"> 1427</span> </div><div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01430"></a><span class="lineno"> 1430</span> </div><div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01433"></a><span class="lineno"> 1433</span> }</div><div class="line"><a name="l01434"></a><span class="lineno"> 1434</span> </div><div class="line"><a name="l01435"></a><span class="lineno"> 1435</span> <span class="keywordtype">void</span> Deserializer::ParseInstanceNormalization(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01436"></a><span class="lineno"> 1436</span> {</div><div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01438"></a><span class="lineno"> 1438</span> </div><div class="line"><a name="l01439"></a><span class="lineno"> 1439</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01441"></a><span class="lineno"> 1441</span> </div><div class="line"><a name="l01442"></a><span class="lineno"> 1442</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01444"></a><span class="lineno"> 1444</span> </div><div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_InstanceNormalizationLayer();</div><div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div><div class="line"><a name="l01447"></a><span class="lineno"> 1447</span> </div><div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>  <a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml">armnn::InstanceNormalizationDescriptor</a> descriptor;</div><div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a5e078fd505aef7bccaa05c8058e096cc">m_Gamma</a> = fbDescriptor->gamma();</div><div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = fbDescriptor->beta();</div><div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a> = fbDescriptor->eps();</div><div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>  descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(fbDescriptor->dataLayout());</div><div class="line"><a name="l01453"></a><span class="lineno"> 1453</span> </div><div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>  <span class="keyword">const</span> std::string layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01456"></a><span class="lineno"> 1456</span> </div><div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddInstanceNormalizationLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01458"></a><span class="lineno"> 1458</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01459"></a><span class="lineno"> 1459</span> </div><div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01462"></a><span class="lineno"> 1462</span> }</div><div class="line"><a name="l01463"></a><span class="lineno"> 1463</span> </div><div class="line"><a name="l01464"></a><span class="lineno"> 1464</span> <span class="keywordtype">void</span> Deserializer::ParseL2Normalization(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01465"></a><span class="lineno"> 1465</span> {</div><div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01467"></a><span class="lineno"> 1467</span> </div><div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01470"></a><span class="lineno"> 1470</span> </div><div class="line"><a name="l01471"></a><span class="lineno"> 1471</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01474"></a><span class="lineno"> 1474</span> </div><div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_L2NormalizationLayer();</div><div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div><div class="line"><a name="l01477"></a><span class="lineno"> 1477</span> </div><div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>  <a class="code" href="structarmnn_1_1_l2_normalization_descriptor.xhtml">armnn::L2NormalizationDescriptor</a> descriptor;</div><div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>  descriptor.<a class="code" href="structarmnn_1_1_l2_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div><div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>  descriptor.<a class="code" href="structarmnn_1_1_l2_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a> = flatBufferDescriptor->eps();</div><div class="line"><a name="l01482"></a><span class="lineno"> 1482</span> </div><div class="line"><a name="l01483"></a><span class="lineno"> 1483</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddL2NormalizationLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01484"></a><span class="lineno"> 1484</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01485"></a><span class="lineno"> 1485</span> </div><div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01488"></a><span class="lineno"> 1488</span> }</div><div class="line"><a name="l01489"></a><span class="lineno"> 1489</span> </div><div class="line"><a name="l01490"></a><span class="lineno"> 1490</span> <span class="keywordtype">void</span> Deserializer::ParseLogSoftmax(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01491"></a><span class="lineno"> 1491</span> {</div><div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01493"></a><span class="lineno"> 1493</span> </div><div class="line"><a name="l01494"></a><span class="lineno"> 1494</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01496"></a><span class="lineno"> 1496</span> </div><div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01499"></a><span class="lineno"> 1499</span> </div><div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>  <a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml">armnn::LogSoftmaxDescriptor</a> descriptor;</div><div class="line"><a name="l01501"></a><span class="lineno"> 1501</span>  descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = graph->layers()->Get(layerIndex)->layer_as_LogSoftmaxLayer()->descriptor()->beta();</div><div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>  descriptor.m_Axis = graph->layers()->Get(layerIndex)->layer_as_LogSoftmaxLayer()->descriptor()->axis();</div><div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01504"></a><span class="lineno"> 1504</span> </div><div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddLogSoftmaxLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01506"></a><span class="lineno"> 1506</span> </div><div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01509"></a><span class="lineno"> 1509</span> </div><div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01512"></a><span class="lineno"> 1512</span> }</div><div class="line"><a name="l01513"></a><span class="lineno"> 1513</span> </div><div class="line"><a name="l01514"></a><span class="lineno"> 1514</span> <span class="keywordtype">void</span> Deserializer::ParseMinimum(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01515"></a><span class="lineno"> 1515</span> {</div><div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l01520"></a><span class="lineno"> 1520</span> </div><div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01523"></a><span class="lineno"> 1523</span> </div><div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01525"></a><span class="lineno"> 1525</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddMinimumLayer(layerName.c_str());</div><div class="line"><a name="l01526"></a><span class="lineno"> 1526</span> </div><div class="line"><a name="l01527"></a><span class="lineno"> 1527</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01528"></a><span class="lineno"> 1528</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01529"></a><span class="lineno"> 1529</span> </div><div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01532"></a><span class="lineno"> 1532</span> }</div><div class="line"><a name="l01533"></a><span class="lineno"> 1533</span> </div><div class="line"><a name="l01534"></a><span class="lineno"> 1534</span> <span class="keywordtype">void</span> Deserializer::ParseMaximum(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01535"></a><span class="lineno"> 1535</span> {</div><div class="line"><a name="l01536"></a><span class="lineno"> 1536</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l01540"></a><span class="lineno"> 1540</span> </div><div class="line"><a name="l01541"></a><span class="lineno"> 1541</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01542"></a><span class="lineno"> 1542</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01543"></a><span class="lineno"> 1543</span> </div><div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddMaximumLayer(layerName.c_str());</div><div class="line"><a name="l01546"></a><span class="lineno"> 1546</span> </div><div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01549"></a><span class="lineno"> 1549</span> </div><div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01552"></a><span class="lineno"> 1552</span> }</div><div class="line"><a name="l01553"></a><span class="lineno"> 1553</span> </div><div class="line"><a name="l01554"></a><span class="lineno"><a class="line" href="namespacearmnn_deserializer.xhtml#a63d3841a5ebb0a5ce572cfb4cb634376"> 1554</a></span> <span class="keyword">const</span> armnnSerializer::OriginsDescriptor* <a class="code" href="namespacearmnn_deserializer.xhtml#a63d3841a5ebb0a5ce572cfb4cb634376">GetOriginsDescriptor</a>(<span class="keyword">const</span> armnnSerializer::SerializedGraph* graph,</div><div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01556"></a><span class="lineno"> 1556</span> {</div><div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>  <span class="keyword">auto</span> layerType = graph->layers()->Get(layerIndex)->layer_type();</div><div class="line"><a name="l01558"></a><span class="lineno"> 1558</span> </div><div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>  <span class="keywordflow">switch</span> (layerType)</div><div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>  {</div><div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>  <span class="keywordflow">case</span> Layer::Layer_ConcatLayer:</div><div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>  <span class="keywordflow">return</span> graph->layers()->Get(layerIndex)->layer_as_ConcatLayer()->descriptor();</div><div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>  <span class="keywordflow">case</span> Layer::Layer_MergerLayer:</div><div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>  <span class="keywordflow">return</span> graph->layers()->Get(layerIndex)->layer_as_MergerLayer()->descriptor();</div><div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l01566"></a><span class="lineno"> 1566</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>(<span class="stringliteral">"unknown layer type, should be concat or merger"</span>);</div><div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>  }</div><div class="line"><a name="l01568"></a><span class="lineno"> 1568</span> }</div><div class="line"><a name="l01569"></a><span class="lineno"> 1569</span> </div><div class="line"><a name="l01570"></a><span class="lineno"> 1570</span> <span class="keywordtype">void</span> Deserializer::ParseComparison(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01571"></a><span class="lineno"> 1571</span> {</div><div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01574"></a><span class="lineno"> 1574</span> </div><div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l01577"></a><span class="lineno"> 1577</span> </div><div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01580"></a><span class="lineno"> 1580</span> </div><div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_ComparisonLayer();</div><div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div><div class="line"><a name="l01583"></a><span class="lineno"> 1583</span> </div><div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>  <a class="code" href="structarmnn_1_1_comparison_descriptor.xhtml">armnn::ComparisonDescriptor</a> descriptor;</div><div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>  descriptor.<a class="code" href="structarmnn_1_1_comparison_descriptor.xhtml#a865dc4f43cb0ff01a1dcf78036912fd1">m_Operation</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#a28f896fb78cdf6607b61c196c98b2570">ToComparisonOperation</a>(fbDescriptor->operation());</div><div class="line"><a name="l01586"></a><span class="lineno"> 1586</span> </div><div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>  <span class="keyword">const</span> std::string& layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddComparisonLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01589"></a><span class="lineno"> 1589</span> </div><div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01591"></a><span class="lineno"> 1591</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01592"></a><span class="lineno"> 1592</span> </div><div class="line"><a name="l01593"></a><span class="lineno"> 1593</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01595"></a><span class="lineno"> 1595</span> }</div><div class="line"><a name="l01596"></a><span class="lineno"> 1596</span> </div><div class="line"><a name="l01597"></a><span class="lineno"> 1597</span> <span class="keywordtype">void</span> Deserializer::ParseElementwiseUnary(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01598"></a><span class="lineno"> 1598</span> {</div><div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01601"></a><span class="lineno"> 1601</span> </div><div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01604"></a><span class="lineno"> 1604</span> </div><div class="line"><a name="l01605"></a><span class="lineno"> 1605</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01607"></a><span class="lineno"> 1607</span> </div><div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_ElementwiseUnaryLayer();</div><div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div><div class="line"><a name="l01610"></a><span class="lineno"> 1610</span> </div><div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>  <a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.xhtml">armnn::ElementwiseUnaryDescriptor</a> descriptor;</div><div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>  descriptor.<a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.xhtml#afe768be66897eb3d73284424e3239b23">m_Operation</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#a7c8f847778ed77469bd6ddbd5158ae4e">ToUnaryOperation</a>(fbDescriptor->operation());</div><div class="line"><a name="l01613"></a><span class="lineno"> 1613</span> </div><div class="line"><a name="l01614"></a><span class="lineno"> 1614</span>  <span class="keyword">const</span> std::string& layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01615"></a><span class="lineno"> 1615</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01616"></a><span class="lineno"> 1616</span> </div><div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01619"></a><span class="lineno"> 1619</span> </div><div class="line"><a name="l01620"></a><span class="lineno"> 1620</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01621"></a><span class="lineno"> 1621</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01622"></a><span class="lineno"> 1622</span> }</div><div class="line"><a name="l01623"></a><span class="lineno"> 1623</span> </div><div class="line"><a name="l01624"></a><span class="lineno"> 1624</span> <span class="keywordtype">void</span> Deserializer::ParseConcat(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01625"></a><span class="lineno"> 1625</span> {</div><div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01628"></a><span class="lineno"> 1628</span> </div><div class="line"><a name="l01629"></a><span class="lineno"> 1629</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01630"></a><span class="lineno"> 1630</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01631"></a><span class="lineno"> 1631</span> </div><div class="line"><a name="l01632"></a><span class="lineno"> 1632</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>  <span class="keyword">auto</span> originsDescriptor = <a class="code" href="namespacearmnn_deserializer.xhtml#a63d3841a5ebb0a5ce572cfb4cb634376">GetOriginsDescriptor</a>(graph, layerIndex);</div><div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numViews = originsDescriptor->numViews();</div><div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions = originsDescriptor->numDimensions();</div><div class="line"><a name="l01636"></a><span class="lineno"> 1636</span> </div><div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>  <span class="comment">// can now check the number of inputs == number of views</span></div><div class="line"><a name="l01638"></a><span class="lineno"> 1638</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numViews);</div><div class="line"><a name="l01640"></a><span class="lineno"> 1640</span> </div><div class="line"><a name="l01641"></a><span class="lineno"> 1641</span>  <a class="code" href="structarmnn_1_1_origins_descriptor.xhtml">armnn::OriginsDescriptor</a> descriptor(numViews, numDimensions);</div><div class="line"><a name="l01642"></a><span class="lineno"> 1642</span>  <span class="keyword">auto</span> originsPtr = originsDescriptor->viewOrigins();</div><div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> v = 0; v < numViews; ++v)</div><div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>  {</div><div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>  <span class="keyword">auto</span> originPtr = originsPtr->Get(v);</div><div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> d = 0; d < numDimensions; ++d)</div><div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>  {</div><div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>  uint32_t value = originPtr->data()->Get(d);</div><div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>  descriptor.SetViewOriginCoord(v, d, value);</div><div class="line"><a name="l01650"></a><span class="lineno"> 1650</span>  }</div><div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>  }</div><div class="line"><a name="l01652"></a><span class="lineno"> 1652</span>  descriptor.SetConcatAxis(originsDescriptor->concatAxis());</div><div class="line"><a name="l01653"></a><span class="lineno"> 1653</span> </div><div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddConcatLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01655"></a><span class="lineno"> 1655</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01656"></a><span class="lineno"> 1656</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01657"></a><span class="lineno"> 1657</span> </div><div class="line"><a name="l01658"></a><span class="lineno"> 1658</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01660"></a><span class="lineno"> 1660</span> }</div><div class="line"><a name="l01661"></a><span class="lineno"> 1661</span> </div><div class="line"><a name="l01662"></a><span class="lineno"> 1662</span> <span class="keywordtype">void</span> Deserializer::ParseMultiplication(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01663"></a><span class="lineno"> 1663</span> {</div><div class="line"><a name="l01664"></a><span class="lineno"> 1664</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l01668"></a><span class="lineno"> 1668</span> </div><div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01670"></a><span class="lineno"> 1670</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01671"></a><span class="lineno"> 1671</span> </div><div class="line"><a name="l01672"></a><span class="lineno"> 1672</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01673"></a><span class="lineno"> 1673</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddMultiplicationLayer(layerName.c_str());</div><div class="line"><a name="l01674"></a><span class="lineno"> 1674</span> </div><div class="line"><a name="l01675"></a><span class="lineno"> 1675</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01676"></a><span class="lineno"> 1676</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01677"></a><span class="lineno"> 1677</span> </div><div class="line"><a name="l01678"></a><span class="lineno"> 1678</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01679"></a><span class="lineno"> 1679</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01680"></a><span class="lineno"> 1680</span> }</div><div class="line"><a name="l01681"></a><span class="lineno"> 1681</span> </div><div class="line"><a name="l01682"></a><span class="lineno"> 1682</span> <span class="keywordtype">void</span> Deserializer::ParseFloor(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01683"></a><span class="lineno"> 1683</span> {</div><div class="line"><a name="l01684"></a><span class="lineno"> 1684</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01685"></a><span class="lineno"> 1685</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01686"></a><span class="lineno"> 1686</span> </div><div class="line"><a name="l01687"></a><span class="lineno"> 1687</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01688"></a><span class="lineno"> 1688</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01689"></a><span class="lineno"> 1689</span> </div><div class="line"><a name="l01690"></a><span class="lineno"> 1690</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01691"></a><span class="lineno"> 1691</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01692"></a><span class="lineno"> 1692</span> </div><div class="line"><a name="l01693"></a><span class="lineno"> 1693</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01694"></a><span class="lineno"> 1694</span> </div><div class="line"><a name="l01695"></a><span class="lineno"> 1695</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer;</div><div class="line"><a name="l01696"></a><span class="lineno"> 1696</span> </div><div class="line"><a name="l01697"></a><span class="lineno"> 1697</span>  layer = m_Network->AddFloorLayer(layerName.c_str());</div><div class="line"><a name="l01698"></a><span class="lineno"> 1698</span> </div><div class="line"><a name="l01699"></a><span class="lineno"> 1699</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01700"></a><span class="lineno"> 1700</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01701"></a><span class="lineno"> 1701</span> </div><div class="line"><a name="l01702"></a><span class="lineno"> 1702</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01703"></a><span class="lineno"> 1703</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01704"></a><span class="lineno"> 1704</span> }</div><div class="line"><a name="l01705"></a><span class="lineno"> 1705</span> </div><div class="line"><a name="l01706"></a><span class="lineno"> 1706</span> <span class="keywordtype">void</span> Deserializer::ParseFullyConnected(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01707"></a><span class="lineno"> 1707</span> {</div><div class="line"><a name="l01708"></a><span class="lineno"> 1708</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01709"></a><span class="lineno"> 1709</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01710"></a><span class="lineno"> 1710</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l01711"></a><span class="lineno"> 1711</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01712"></a><span class="lineno"> 1712</span> </div><div class="line"><a name="l01713"></a><span class="lineno"> 1713</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01714"></a><span class="lineno"> 1714</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01715"></a><span class="lineno"> 1715</span> </div><div class="line"><a name="l01716"></a><span class="lineno"> 1716</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_FullyConnectedLayer();</div><div class="line"><a name="l01717"></a><span class="lineno"> 1717</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01718"></a><span class="lineno"> 1718</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div><div class="line"><a name="l01719"></a><span class="lineno"> 1719</span> </div><div class="line"><a name="l01720"></a><span class="lineno"> 1720</span>  <a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">armnn::FullyConnectedDescriptor</a> fullyConnectedDescriptor;</div><div class="line"><a name="l01721"></a><span class="lineno"> 1721</span>  fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = flatBufferDescriptor->biasEnabled();</div><div class="line"><a name="l01722"></a><span class="lineno"> 1722</span>  fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#a281fcaec86e17c97f7b8402633f6b55a">m_TransposeWeightMatrix</a> = flatBufferDescriptor->transposeWeightsMatrix();</div><div class="line"><a name="l01723"></a><span class="lineno"> 1723</span> </div><div class="line"><a name="l01724"></a><span class="lineno"> 1724</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weightsTensor = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferLayer->weights());</div><div class="line"><a name="l01725"></a><span class="lineno"> 1725</span> </div><div class="line"><a name="l01726"></a><span class="lineno"> 1726</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer;</div><div class="line"><a name="l01727"></a><span class="lineno"> 1727</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<armnn::ConstTensor></a> optionalBiases = <a class="code" href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a>();</div><div class="line"><a name="l01728"></a><span class="lineno"> 1728</span>  <span class="keywordflow">if</span> (flatBufferDescriptor->biasEnabled())</div><div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>  {</div><div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> biasTensorData = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferLayer->biases());</div><div class="line"><a name="l01731"></a><span class="lineno"> 1731</span>  optionalBiases = <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<armnn::ConstTensor></a>(biasTensorData);</div><div class="line"><a name="l01732"></a><span class="lineno"> 1732</span>  }</div><div class="line"><a name="l01733"></a><span class="lineno"> 1733</span>  layer = m_Network->AddFullyConnectedLayer(fullyConnectedDescriptor,</div><div class="line"><a name="l01734"></a><span class="lineno"> 1734</span>  weightsTensor,</div><div class="line"><a name="l01735"></a><span class="lineno"> 1735</span>  optionalBiases,</div><div class="line"><a name="l01736"></a><span class="lineno"> 1736</span>  layerName.c_str());</div><div class="line"><a name="l01737"></a><span class="lineno"> 1737</span> </div><div class="line"><a name="l01738"></a><span class="lineno"> 1738</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01739"></a><span class="lineno"> 1739</span>  layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);</div><div class="line"><a name="l01740"></a><span class="lineno"> 1740</span> </div><div class="line"><a name="l01741"></a><span class="lineno"> 1741</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01742"></a><span class="lineno"> 1742</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01743"></a><span class="lineno"> 1743</span> }</div><div class="line"><a name="l01744"></a><span class="lineno"> 1744</span> </div><div class="line"><a name="l01745"></a><span class="lineno"> 1745</span> <span class="keywordtype">void</span> Deserializer::ParsePad(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01746"></a><span class="lineno"> 1746</span> {</div><div class="line"><a name="l01747"></a><span class="lineno"> 1747</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01748"></a><span class="lineno"> 1748</span> </div><div class="line"><a name="l01749"></a><span class="lineno"> 1749</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01750"></a><span class="lineno"> 1750</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01751"></a><span class="lineno"> 1751</span> </div><div class="line"><a name="l01752"></a><span class="lineno"> 1752</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01753"></a><span class="lineno"> 1753</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01754"></a><span class="lineno"> 1754</span> </div><div class="line"><a name="l01755"></a><span class="lineno"> 1755</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_PadLayer()->descriptor();</div><div class="line"><a name="l01756"></a><span class="lineno"> 1756</span>  <span class="keyword">auto</span> flatBufferPadList = flatBufferDescriptor->padList();</div><div class="line"><a name="l01757"></a><span class="lineno"> 1757</span>  <span class="keywordtype">float</span> padValue = flatBufferDescriptor->padValue();</div><div class="line"><a name="l01758"></a><span class="lineno"> 1758</span> </div><div class="line"><a name="l01759"></a><span class="lineno"> 1759</span>  <span class="keywordflow">if</span> (flatBufferPadList->Length() % 2 != 0)</div><div class="line"><a name="l01760"></a><span class="lineno"> 1760</span>  {</div><div class="line"><a name="l01761"></a><span class="lineno"> 1761</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(boost::str(</div><div class="line"><a name="l01762"></a><span class="lineno"> 1762</span>  boost::format(<span class="stringliteral">"The size of the pad list must be divisible by 2 %1%"</span>) % <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l01763"></a><span class="lineno"> 1763</span>  }</div><div class="line"><a name="l01764"></a><span class="lineno"> 1764</span> </div><div class="line"><a name="l01765"></a><span class="lineno"> 1765</span>  std::vector<std::pair<unsigned int, unsigned int>> padList;</div><div class="line"><a name="l01766"></a><span class="lineno"> 1766</span>  padList.reserve(flatBufferPadList->Length() / 2);</div><div class="line"><a name="l01767"></a><span class="lineno"> 1767</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < flatBufferPadList->Length() - 1; i += 2)</div><div class="line"><a name="l01768"></a><span class="lineno"> 1768</span>  {</div><div class="line"><a name="l01769"></a><span class="lineno"> 1769</span>  padList.emplace_back(flatBufferPadList->Get(i), flatBufferPadList->Get(i+1));</div><div class="line"><a name="l01770"></a><span class="lineno"> 1770</span>  }</div><div class="line"><a name="l01771"></a><span class="lineno"> 1771</span> </div><div class="line"><a name="l01772"></a><span class="lineno"> 1772</span>  <a class="code" href="structarmnn_1_1_pad_descriptor.xhtml">armnn::PadDescriptor</a> descriptor(padList, padValue);</div><div class="line"><a name="l01773"></a><span class="lineno"> 1773</span> </div><div class="line"><a name="l01774"></a><span class="lineno"> 1774</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01775"></a><span class="lineno"> 1775</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddPadLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01776"></a><span class="lineno"> 1776</span> </div><div class="line"><a name="l01777"></a><span class="lineno"> 1777</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01778"></a><span class="lineno"> 1778</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01779"></a><span class="lineno"> 1779</span> </div><div class="line"><a name="l01780"></a><span class="lineno"> 1780</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01781"></a><span class="lineno"> 1781</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01782"></a><span class="lineno"> 1782</span> }</div><div class="line"><a name="l01783"></a><span class="lineno"> 1783</span> </div><div class="line"><a name="l01784"></a><span class="lineno"> 1784</span> <span class="keywordtype">void</span> Deserializer::ParsePermute(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01785"></a><span class="lineno"> 1785</span> {</div><div class="line"><a name="l01786"></a><span class="lineno"> 1786</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01787"></a><span class="lineno"> 1787</span> </div><div class="line"><a name="l01788"></a><span class="lineno"> 1788</span>  <span class="keyword">auto</span> dimsMapping =</div><div class="line"><a name="l01789"></a><span class="lineno"> 1789</span>  graph->layers()->Get(layerIndex)->layer_as_PermuteLayer()->descriptor()->dimMappings();</div><div class="line"><a name="l01790"></a><span class="lineno"> 1790</span> </div><div class="line"><a name="l01791"></a><span class="lineno"> 1791</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01792"></a><span class="lineno"> 1792</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01793"></a><span class="lineno"> 1793</span> </div><div class="line"><a name="l01794"></a><span class="lineno"> 1794</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01795"></a><span class="lineno"> 1795</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01796"></a><span class="lineno"> 1796</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01797"></a><span class="lineno"> 1797</span> </div><div class="line"><a name="l01798"></a><span class="lineno"> 1798</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01799"></a><span class="lineno"> 1799</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_permute_descriptor.xhtml">armnn::PermuteDescriptor</a> descriptor(<a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a>(dimsMapping->data(), dimsMapping->Length()));</div><div class="line"><a name="l01800"></a><span class="lineno"> 1800</span> </div><div class="line"><a name="l01801"></a><span class="lineno"> 1801</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddPermuteLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01802"></a><span class="lineno"> 1802</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01803"></a><span class="lineno"> 1803</span> </div><div class="line"><a name="l01804"></a><span class="lineno"> 1804</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01805"></a><span class="lineno"> 1805</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01806"></a><span class="lineno"> 1806</span> }</div><div class="line"><a name="l01807"></a><span class="lineno"> 1807</span> </div><div class="line"><a name="l01808"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#a271f00048f7e48392794c2eee17c1e2c"> 1808</a></span> <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a271f00048f7e48392794c2eee17c1e2c">Deserializer::GetPoolingDescriptor</a>(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0dc66e036f16781886a1ce530e11c2d8">Deserializer::PoolingDescriptor</a> pooling2dDesc,</div><div class="line"><a name="l01809"></a><span class="lineno"> 1809</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01810"></a><span class="lineno"> 1810</span> {</div><div class="line"><a name="l01811"></a><span class="lineno"> 1811</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div><div class="line"><a name="l01812"></a><span class="lineno"> 1812</span>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> desc;</div><div class="line"><a name="l01813"></a><span class="lineno"> 1813</span> </div><div class="line"><a name="l01814"></a><span class="lineno"> 1814</span>  <span class="keywordflow">switch</span> (pooling2dDesc->poolType())</div><div class="line"><a name="l01815"></a><span class="lineno"> 1815</span>  {</div><div class="line"><a name="l01816"></a><span class="lineno"> 1816</span>  <span class="keywordflow">case</span> PoolingAlgorithm_Average:</div><div class="line"><a name="l01817"></a><span class="lineno"> 1817</span>  {</div><div class="line"><a name="l01818"></a><span class="lineno"> 1818</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a>;</div><div class="line"><a name="l01819"></a><span class="lineno"> 1819</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01820"></a><span class="lineno"> 1820</span>  }</div><div class="line"><a name="l01821"></a><span class="lineno"> 1821</span>  <span class="keywordflow">case</span> PoolingAlgorithm_Max:</div><div class="line"><a name="l01822"></a><span class="lineno"> 1822</span>  {</div><div class="line"><a name="l01823"></a><span class="lineno"> 1823</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div><div class="line"><a name="l01824"></a><span class="lineno"> 1824</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01825"></a><span class="lineno"> 1825</span>  }</div><div class="line"><a name="l01826"></a><span class="lineno"> 1826</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l01827"></a><span class="lineno"> 1827</span>  {</div><div class="line"><a name="l01828"></a><span class="lineno"> 1828</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported pooling algorithm"</span>);</div><div class="line"><a name="l01829"></a><span class="lineno"> 1829</span>  }</div><div class="line"><a name="l01830"></a><span class="lineno"> 1830</span>  }</div><div class="line"><a name="l01831"></a><span class="lineno"> 1831</span> </div><div class="line"><a name="l01832"></a><span class="lineno"> 1832</span>  <span class="keywordflow">switch</span> (pooling2dDesc->outputShapeRounding())</div><div class="line"><a name="l01833"></a><span class="lineno"> 1833</span>  {</div><div class="line"><a name="l01834"></a><span class="lineno"> 1834</span>  <span class="keywordflow">case</span> OutputShapeRounding_Floor:</div><div class="line"><a name="l01835"></a><span class="lineno"> 1835</span>  {</div><div class="line"><a name="l01836"></a><span class="lineno"> 1836</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div><div class="line"><a name="l01837"></a><span class="lineno"> 1837</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01838"></a><span class="lineno"> 1838</span>  }</div><div class="line"><a name="l01839"></a><span class="lineno"> 1839</span>  <span class="keywordflow">case</span> OutputShapeRounding_Ceiling:</div><div class="line"><a name="l01840"></a><span class="lineno"> 1840</span>  {</div><div class="line"><a name="l01841"></a><span class="lineno"> 1841</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb">armnn::OutputShapeRounding::Ceiling</a>;</div><div class="line"><a name="l01842"></a><span class="lineno"> 1842</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01843"></a><span class="lineno"> 1843</span>  }</div><div class="line"><a name="l01844"></a><span class="lineno"> 1844</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l01845"></a><span class="lineno"> 1845</span>  {</div><div class="line"><a name="l01846"></a><span class="lineno"> 1846</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported output shape rounding"</span>);</div><div class="line"><a name="l01847"></a><span class="lineno"> 1847</span>  }</div><div class="line"><a name="l01848"></a><span class="lineno"> 1848</span>  }</div><div class="line"><a name="l01849"></a><span class="lineno"> 1849</span> </div><div class="line"><a name="l01850"></a><span class="lineno"> 1850</span>  <span class="keywordflow">switch</span> (pooling2dDesc->paddingMethod())</div><div class="line"><a name="l01851"></a><span class="lineno"> 1851</span>  {</div><div class="line"><a name="l01852"></a><span class="lineno"> 1852</span>  <span class="keywordflow">case</span> PaddingMethod_Exclude:</div><div class="line"><a name="l01853"></a><span class="lineno"> 1853</span>  {</div><div class="line"><a name="l01854"></a><span class="lineno"> 1854</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l01855"></a><span class="lineno"> 1855</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01856"></a><span class="lineno"> 1856</span>  }</div><div class="line"><a name="l01857"></a><span class="lineno"> 1857</span>  <span class="keywordflow">case</span> PaddingMethod_IgnoreValue:</div><div class="line"><a name="l01858"></a><span class="lineno"> 1858</span>  {</div><div class="line"><a name="l01859"></a><span class="lineno"> 1859</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a>;</div><div class="line"><a name="l01860"></a><span class="lineno"> 1860</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01861"></a><span class="lineno"> 1861</span>  }</div><div class="line"><a name="l01862"></a><span class="lineno"> 1862</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l01863"></a><span class="lineno"> 1863</span>  {</div><div class="line"><a name="l01864"></a><span class="lineno"> 1864</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported padding method"</span>);</div><div class="line"><a name="l01865"></a><span class="lineno"> 1865</span>  }</div><div class="line"><a name="l01866"></a><span class="lineno"> 1866</span>  }</div><div class="line"><a name="l01867"></a><span class="lineno"> 1867</span> </div><div class="line"><a name="l01868"></a><span class="lineno"> 1868</span>  <span class="keywordflow">switch</span> (pooling2dDesc->dataLayout())</div><div class="line"><a name="l01869"></a><span class="lineno"> 1869</span>  {</div><div class="line"><a name="l01870"></a><span class="lineno"> 1870</span>  <span class="keywordflow">case</span> DataLayout_NCHW:</div><div class="line"><a name="l01871"></a><span class="lineno"> 1871</span>  {</div><div class="line"><a name="l01872"></a><span class="lineno"> 1872</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div><div class="line"><a name="l01873"></a><span class="lineno"> 1873</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01874"></a><span class="lineno"> 1874</span>  }</div><div class="line"><a name="l01875"></a><span class="lineno"> 1875</span>  <span class="keywordflow">case</span> DataLayout_NHWC:</div><div class="line"><a name="l01876"></a><span class="lineno"> 1876</span>  {</div><div class="line"><a name="l01877"></a><span class="lineno"> 1877</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l01878"></a><span class="lineno"> 1878</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01879"></a><span class="lineno"> 1879</span>  }</div><div class="line"><a name="l01880"></a><span class="lineno"> 1880</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l01881"></a><span class="lineno"> 1881</span>  {</div><div class="line"><a name="l01882"></a><span class="lineno"> 1882</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported data layout"</span>);</div><div class="line"><a name="l01883"></a><span class="lineno"> 1883</span>  }</div><div class="line"><a name="l01884"></a><span class="lineno"> 1884</span>  }</div><div class="line"><a name="l01885"></a><span class="lineno"> 1885</span> </div><div class="line"><a name="l01886"></a><span class="lineno"> 1886</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = pooling2dDesc->padRight();</div><div class="line"><a name="l01887"></a><span class="lineno"> 1887</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = pooling2dDesc->padLeft();</div><div class="line"><a name="l01888"></a><span class="lineno"> 1888</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = pooling2dDesc->padBottom();</div><div class="line"><a name="l01889"></a><span class="lineno"> 1889</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = pooling2dDesc->padTop();</div><div class="line"><a name="l01890"></a><span class="lineno"> 1890</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = pooling2dDesc->strideX();</div><div class="line"><a name="l01891"></a><span class="lineno"> 1891</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = pooling2dDesc->strideY();</div><div class="line"><a name="l01892"></a><span class="lineno"> 1892</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = pooling2dDesc->poolWidth();</div><div class="line"><a name="l01893"></a><span class="lineno"> 1893</span>  desc.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = pooling2dDesc->poolHeight();</div><div class="line"><a name="l01894"></a><span class="lineno"> 1894</span> </div><div class="line"><a name="l01895"></a><span class="lineno"> 1895</span>  <span class="keywordflow">return</span> desc;</div><div class="line"><a name="l01896"></a><span class="lineno"> 1896</span> }</div><div class="line"><a name="l01897"></a><span class="lineno"> 1897</span> </div><div class="line"><a name="l01898"></a><span class="lineno"> 1898</span> <span class="keywordtype">void</span> Deserializer::ParsePooling2d(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01899"></a><span class="lineno"> 1899</span> {</div><div class="line"><a name="l01900"></a><span class="lineno"> 1900</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01901"></a><span class="lineno"> 1901</span> </div><div class="line"><a name="l01902"></a><span class="lineno"> 1902</span>  <span class="keyword">auto</span> pooling2dDes = graph->layers()->Get(layerIndex)->layer_as_Pooling2dLayer()->descriptor();</div><div class="line"><a name="l01903"></a><span class="lineno"> 1903</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01904"></a><span class="lineno"> 1904</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01905"></a><span class="lineno"> 1905</span> </div><div class="line"><a name="l01906"></a><span class="lineno"> 1906</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01907"></a><span class="lineno"> 1907</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01908"></a><span class="lineno"> 1908</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01909"></a><span class="lineno"> 1909</span> </div><div class="line"><a name="l01910"></a><span class="lineno"> 1910</span>  <span class="keyword">auto</span> pooling2dDescriptor = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a271f00048f7e48392794c2eee17c1e2c">GetPoolingDescriptor</a>(pooling2dDes, layerIndex);</div><div class="line"><a name="l01911"></a><span class="lineno"> 1911</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01912"></a><span class="lineno"> 1912</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddPooling2dLayer(pooling2dDescriptor, layerName.c_str());</div><div class="line"><a name="l01913"></a><span class="lineno"> 1913</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01914"></a><span class="lineno"> 1914</span> </div><div class="line"><a name="l01915"></a><span class="lineno"> 1915</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01916"></a><span class="lineno"> 1916</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01917"></a><span class="lineno"> 1917</span> }</div><div class="line"><a name="l01918"></a><span class="lineno"> 1918</span> </div><div class="line"><a name="l01919"></a><span class="lineno"> 1919</span> <span class="keywordtype">void</span> Deserializer::ParseQuantize(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01920"></a><span class="lineno"> 1920</span> {</div><div class="line"><a name="l01921"></a><span class="lineno"> 1921</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01922"></a><span class="lineno"> 1922</span> </div><div class="line"><a name="l01923"></a><span class="lineno"> 1923</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01924"></a><span class="lineno"> 1924</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l01925"></a><span class="lineno"> 1925</span> </div><div class="line"><a name="l01926"></a><span class="lineno"> 1926</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01927"></a><span class="lineno"> 1927</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01928"></a><span class="lineno"> 1928</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01929"></a><span class="lineno"> 1929</span> </div><div class="line"><a name="l01930"></a><span class="lineno"> 1930</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l01931"></a><span class="lineno"> 1931</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddQuantizeLayer(layerName.c_str());</div><div class="line"><a name="l01932"></a><span class="lineno"> 1932</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01933"></a><span class="lineno"> 1933</span> </div><div class="line"><a name="l01934"></a><span class="lineno"> 1934</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01935"></a><span class="lineno"> 1935</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l01936"></a><span class="lineno"> 1936</span> }</div><div class="line"><a name="l01937"></a><span class="lineno"> 1937</span> </div><div class="line"><a name="l01938"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#a8752c2b994619ae67201a297c2c76be2"> 1938</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a8752c2b994619ae67201a297c2c76be2">Deserializer::OutputShapeOfReshape</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& inputTensorInfo,</div><div class="line"><a name="l01939"></a><span class="lineno"> 1939</span>  <span class="keyword">const</span> std::vector<uint32_t>& targetDimsIn)</div><div class="line"><a name="l01940"></a><span class="lineno"> 1940</span> {</div><div class="line"><a name="l01941"></a><span class="lineno"> 1941</span>  std::vector<unsigned int> outputDims(targetDimsIn.begin(), targetDimsIn.end());</div><div class="line"><a name="l01942"></a><span class="lineno"> 1942</span>  <span class="keyword">const</span> <span class="keyword">auto</span> stretchDim = std::find(targetDimsIn.begin(), targetDimsIn.end(), -1);</div><div class="line"><a name="l01943"></a><span class="lineno"> 1943</span> </div><div class="line"><a name="l01944"></a><span class="lineno"> 1944</span>  <span class="keywordflow">if</span> (stretchDim != targetDimsIn.end())</div><div class="line"><a name="l01945"></a><span class="lineno"> 1945</span>  {</div><div class="line"><a name="l01946"></a><span class="lineno"> 1946</span>  <span class="keywordflow">if</span> (std::find(std::next(stretchDim), targetDimsIn.end(), -1) != targetDimsIn.end())</div><div class="line"><a name="l01947"></a><span class="lineno"> 1947</span>  {</div><div class="line"><a name="l01948"></a><span class="lineno"> 1948</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(boost::str(</div><div class="line"><a name="l01949"></a><span class="lineno"> 1949</span>  boost::format(<span class="stringliteral">"At most one component of shape can be -1 %1%"</span>) % <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l01950"></a><span class="lineno"> 1950</span>  }</div><div class="line"><a name="l01951"></a><span class="lineno"> 1951</span> </div><div class="line"><a name="l01952"></a><span class="lineno"> 1952</span>  <span class="keyword">auto</span> targetNumElements =</div><div class="line"><a name="l01953"></a><span class="lineno"> 1953</span>  <a class="code" href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">boost::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(</div><div class="line"><a name="l01954"></a><span class="lineno"> 1954</span>  std::accumulate(targetDimsIn.begin(), targetDimsIn.end(), -1, std::multiplies<int32_t>()));</div><div class="line"><a name="l01955"></a><span class="lineno"> 1955</span> </div><div class="line"><a name="l01956"></a><span class="lineno"> 1956</span>  <span class="keyword">auto</span> stretchIndex = <span class="keyword">static_cast<</span><span class="keywordtype">size_t</span><span class="keyword">></span>(std::distance(targetDimsIn.begin(), stretchDim));</div><div class="line"><a name="l01957"></a><span class="lineno"> 1957</span>  outputDims[stretchIndex] = inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>() / targetNumElements;</div><div class="line"><a name="l01958"></a><span class="lineno"> 1958</span>  }</div><div class="line"><a name="l01959"></a><span class="lineno"> 1959</span> </div><div class="line"><a name="l01960"></a><span class="lineno"> 1960</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(static_cast<unsigned int>(outputDims.size()), outputDims.data());</div><div class="line"><a name="l01961"></a><span class="lineno"> 1961</span> </div><div class="line"><a name="l01962"></a><span class="lineno"> 1962</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> reshapeInfo = inputTensorInfo;</div><div class="line"><a name="l01963"></a><span class="lineno"> 1963</span>  reshapeInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(outputShape);</div><div class="line"><a name="l01964"></a><span class="lineno"> 1964</span> </div><div class="line"><a name="l01965"></a><span class="lineno"> 1965</span>  <span class="keywordflow">return</span> reshapeInfo;</div><div class="line"><a name="l01966"></a><span class="lineno"> 1966</span> }</div><div class="line"><a name="l01967"></a><span class="lineno"> 1967</span> </div><div class="line"><a name="l01968"></a><span class="lineno"> 1968</span> <span class="keywordtype">void</span> Deserializer::ParseReshape(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l01969"></a><span class="lineno"> 1969</span> {</div><div class="line"><a name="l01970"></a><span class="lineno"> 1970</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l01971"></a><span class="lineno"> 1971</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l01972"></a><span class="lineno"> 1972</span> </div><div class="line"><a name="l01973"></a><span class="lineno"> 1973</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l01974"></a><span class="lineno"> 1974</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l01975"></a><span class="lineno"> 1975</span> </div><div class="line"><a name="l01976"></a><span class="lineno"> 1976</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(inputs[0]);</div><div class="line"><a name="l01977"></a><span class="lineno"> 1977</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> actualOutputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l01978"></a><span class="lineno"> 1978</span> </div><div class="line"><a name="l01979"></a><span class="lineno"> 1979</span>  <span class="keyword">const</span> <span class="keyword">auto</span> targetDims = graph->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->descriptor()->targetShape();</div><div class="line"><a name="l01980"></a><span class="lineno"> 1980</span>  std::vector<uint32_t> outputDims(targetDims->begin(), targetDims->begin() + targetDims->size());</div><div class="line"><a name="l01981"></a><span class="lineno"> 1981</span> </div><div class="line"><a name="l01982"></a><span class="lineno"> 1982</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> reshapeOutputTensorInfo = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a8752c2b994619ae67201a297c2c76be2">Deserializer::OutputShapeOfReshape</a>(inputTensorInfo, outputDims);</div><div class="line"><a name="l01983"></a><span class="lineno"> 1983</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& reshapeOutputTensorShape = reshapeOutputTensorInfo.GetShape();</div><div class="line"><a name="l01984"></a><span class="lineno"> 1984</span> </div><div class="line"><a name="l01985"></a><span class="lineno"> 1985</span>  <span class="keyword">const</span> std::vector<uint32_t> expectedDims(outputs[0]->dimensions()->begin(),</div><div class="line"><a name="l01986"></a><span class="lineno"> 1986</span>  outputs[0]->dimensions()->begin() + outputs[0]->dimensions()->size());</div><div class="line"><a name="l01987"></a><span class="lineno"> 1987</span> </div><div class="line"><a name="l01988"></a><span class="lineno"> 1988</span>  <span class="keywordflow">if</span> (inputs.size() > 1 && !<a class="code" href="namespacearmnn_deserializer.xhtml#a97b50f22cd99f0e09e6e48d20a35f6b2">CheckShape</a>(reshapeOutputTensorShape, expectedDims))</div><div class="line"><a name="l01989"></a><span class="lineno"> 1989</span>  {</div><div class="line"><a name="l01990"></a><span class="lineno"> 1990</span>  std::stringstream ss;</div><div class="line"><a name="l01991"></a><span class="lineno"> 1991</span>  ss << <span class="stringliteral">"New shape defined in reshape parameters "</span></div><div class="line"><a name="l01992"></a><span class="lineno"> 1992</span>  << reshapeOutputTensorShape</div><div class="line"><a name="l01993"></a><span class="lineno"> 1993</span>  << <span class="stringliteral">" does not equal output shape "</span></div><div class="line"><a name="l01994"></a><span class="lineno"> 1994</span>  << actualOutputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()</div><div class="line"><a name="l01995"></a><span class="lineno"> 1995</span>  << <span class="stringliteral">": "</span></div><div class="line"><a name="l01996"></a><span class="lineno"> 1996</span>  << <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString();</div><div class="line"><a name="l01997"></a><span class="lineno"> 1997</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(ss.str());</div><div class="line"><a name="l01998"></a><span class="lineno"> 1998</span>  }</div><div class="line"><a name="l01999"></a><span class="lineno"> 1999</span> </div><div class="line"><a name="l02000"></a><span class="lineno"> 2000</span>  <a class="code" href="structarmnn_1_1_reshape_descriptor.xhtml">armnn::ReshapeDescriptor</a> reshapeDesc;</div><div class="line"><a name="l02001"></a><span class="lineno"> 2001</span>  reshapeDesc.<a class="code" href="structarmnn_1_1_reshape_descriptor.xhtml#a1178f4dafdda81f59c15145ec327f7d9">m_TargetShape</a> = reshapeOutputTensorShape;</div><div class="line"><a name="l02002"></a><span class="lineno"> 2002</span> </div><div class="line"><a name="l02003"></a><span class="lineno"> 2003</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02004"></a><span class="lineno"> 2004</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddReshapeLayer(reshapeDesc, layerName.c_str());</div><div class="line"><a name="l02005"></a><span class="lineno"> 2005</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(reshapeOutputTensorInfo);</div><div class="line"><a name="l02006"></a><span class="lineno"> 2006</span> </div><div class="line"><a name="l02007"></a><span class="lineno"> 2007</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02008"></a><span class="lineno"> 2008</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02009"></a><span class="lineno"> 2009</span> }</div><div class="line"><a name="l02010"></a><span class="lineno"> 2010</span> </div><div class="line"><a name="l02011"></a><span class="lineno"> 2011</span> <span class="keywordtype">void</span> Deserializer::ParseResize(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02012"></a><span class="lineno"> 2012</span> {</div><div class="line"><a name="l02013"></a><span class="lineno"> 2013</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02014"></a><span class="lineno"> 2014</span> </div><div class="line"><a name="l02015"></a><span class="lineno"> 2015</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02016"></a><span class="lineno"> 2016</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02017"></a><span class="lineno"> 2017</span> </div><div class="line"><a name="l02018"></a><span class="lineno"> 2018</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02019"></a><span class="lineno"> 2019</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02020"></a><span class="lineno"> 2020</span> </div><div class="line"><a name="l02021"></a><span class="lineno"> 2021</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_ResizeLayer()->descriptor();</div><div class="line"><a name="l02022"></a><span class="lineno"> 2022</span> </div><div class="line"><a name="l02023"></a><span class="lineno"> 2023</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">armnn::ResizeDescriptor</a> descriptor;</div><div class="line"><a name="l02024"></a><span class="lineno"> 2024</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a> = flatBufferDescriptor->targetWidth();</div><div class="line"><a name="l02025"></a><span class="lineno"> 2025</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = flatBufferDescriptor->targetHeight();</div><div class="line"><a name="l02026"></a><span class="lineno"> 2026</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a869254cb56968986a78a79e1d6d4a86b">m_Method</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#a8b51e137fab21d758b965c6c6e3b02f3">ToResizeMethod</a>(flatBufferDescriptor->method());</div><div class="line"><a name="l02027"></a><span class="lineno"> 2027</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div><div class="line"><a name="l02028"></a><span class="lineno"> 2028</span> </div><div class="line"><a name="l02029"></a><span class="lineno"> 2029</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02030"></a><span class="lineno"> 2030</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddResizeLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02031"></a><span class="lineno"> 2031</span> </div><div class="line"><a name="l02032"></a><span class="lineno"> 2032</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02033"></a><span class="lineno"> 2033</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02034"></a><span class="lineno"> 2034</span> </div><div class="line"><a name="l02035"></a><span class="lineno"> 2035</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02036"></a><span class="lineno"> 2036</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02037"></a><span class="lineno"> 2037</span> }</div><div class="line"><a name="l02038"></a><span class="lineno"> 2038</span> </div><div class="line"><a name="l02039"></a><span class="lineno"> 2039</span> <span class="keywordtype">void</span> Deserializer::ParseResizeBilinear(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02040"></a><span class="lineno"> 2040</span> {</div><div class="line"><a name="l02041"></a><span class="lineno"> 2041</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02042"></a><span class="lineno"> 2042</span> </div><div class="line"><a name="l02043"></a><span class="lineno"> 2043</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02044"></a><span class="lineno"> 2044</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02045"></a><span class="lineno"> 2045</span> </div><div class="line"><a name="l02046"></a><span class="lineno"> 2046</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02047"></a><span class="lineno"> 2047</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02048"></a><span class="lineno"> 2048</span> </div><div class="line"><a name="l02049"></a><span class="lineno"> 2049</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_ResizeBilinearLayer()->descriptor();</div><div class="line"><a name="l02050"></a><span class="lineno"> 2050</span> </div><div class="line"><a name="l02051"></a><span class="lineno"> 2051</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">armnn::ResizeDescriptor</a> descriptor;</div><div class="line"><a name="l02052"></a><span class="lineno"> 2052</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a> = flatBufferDescriptor->targetWidth();</div><div class="line"><a name="l02053"></a><span class="lineno"> 2053</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = flatBufferDescriptor->targetHeight();</div><div class="line"><a name="l02054"></a><span class="lineno"> 2054</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a869254cb56968986a78a79e1d6d4a86b">m_Method</a> = <a class="code" href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a>;</div><div class="line"><a name="l02055"></a><span class="lineno"> 2055</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div><div class="line"><a name="l02056"></a><span class="lineno"> 2056</span> </div><div class="line"><a name="l02057"></a><span class="lineno"> 2057</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02058"></a><span class="lineno"> 2058</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddResizeLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02059"></a><span class="lineno"> 2059</span> </div><div class="line"><a name="l02060"></a><span class="lineno"> 2060</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02061"></a><span class="lineno"> 2061</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02062"></a><span class="lineno"> 2062</span> </div><div class="line"><a name="l02063"></a><span class="lineno"> 2063</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02064"></a><span class="lineno"> 2064</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02065"></a><span class="lineno"> 2065</span> }</div><div class="line"><a name="l02066"></a><span class="lineno"> 2066</span> </div><div class="line"><a name="l02067"></a><span class="lineno"> 2067</span> <span class="keywordtype">void</span> Deserializer::ParseSoftmax(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02068"></a><span class="lineno"> 2068</span> {</div><div class="line"><a name="l02069"></a><span class="lineno"> 2069</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02070"></a><span class="lineno"> 2070</span> </div><div class="line"><a name="l02071"></a><span class="lineno"> 2071</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02072"></a><span class="lineno"> 2072</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02073"></a><span class="lineno"> 2073</span> </div><div class="line"><a name="l02074"></a><span class="lineno"> 2074</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02075"></a><span class="lineno"> 2075</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02076"></a><span class="lineno"> 2076</span> </div><div class="line"><a name="l02077"></a><span class="lineno"> 2077</span>  <a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml">armnn::SoftmaxDescriptor</a> descriptor;</div><div class="line"><a name="l02078"></a><span class="lineno"> 2078</span>  descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = graph->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->descriptor()->beta();</div><div class="line"><a name="l02079"></a><span class="lineno"> 2079</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02080"></a><span class="lineno"> 2080</span> </div><div class="line"><a name="l02081"></a><span class="lineno"> 2081</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddSoftmaxLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02082"></a><span class="lineno"> 2082</span> </div><div class="line"><a name="l02083"></a><span class="lineno"> 2083</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02084"></a><span class="lineno"> 2084</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02085"></a><span class="lineno"> 2085</span> </div><div class="line"><a name="l02086"></a><span class="lineno"> 2086</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02087"></a><span class="lineno"> 2087</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02088"></a><span class="lineno"> 2088</span> }</div><div class="line"><a name="l02089"></a><span class="lineno"> 2089</span> </div><div class="line"><a name="l02090"></a><span class="lineno"> 2090</span> <span class="keywordtype">void</span> Deserializer::ParseSpaceToBatchNd(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02091"></a><span class="lineno"> 2091</span> {</div><div class="line"><a name="l02092"></a><span class="lineno"> 2092</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02093"></a><span class="lineno"> 2093</span> </div><div class="line"><a name="l02094"></a><span class="lineno"> 2094</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02095"></a><span class="lineno"> 2095</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02096"></a><span class="lineno"> 2096</span> </div><div class="line"><a name="l02097"></a><span class="lineno"> 2097</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02098"></a><span class="lineno"> 2098</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02099"></a><span class="lineno"> 2099</span> </div><div class="line"><a name="l02100"></a><span class="lineno"> 2100</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_SpaceToBatchNdLayer()->descriptor();</div><div class="line"><a name="l02101"></a><span class="lineno"> 2101</span>  <span class="keyword">auto</span> flatBufferPadList = flatBufferDescriptor->padList();</div><div class="line"><a name="l02102"></a><span class="lineno"> 2102</span>  <span class="keyword">auto</span> flatBufferBlockShape = flatBufferDescriptor->blockShape();</div><div class="line"><a name="l02103"></a><span class="lineno"> 2103</span> </div><div class="line"><a name="l02104"></a><span class="lineno"> 2104</span>  <span class="keywordflow">if</span> (flatBufferPadList->Length() % 2 != 0)</div><div class="line"><a name="l02105"></a><span class="lineno"> 2105</span>  {</div><div class="line"><a name="l02106"></a><span class="lineno"> 2106</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(boost::str(</div><div class="line"><a name="l02107"></a><span class="lineno"> 2107</span>  boost::format(<span class="stringliteral">"The size of the pad list must be divisible by 2 %1%"</span>) % <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l02108"></a><span class="lineno"> 2108</span>  }</div><div class="line"><a name="l02109"></a><span class="lineno"> 2109</span> </div><div class="line"><a name="l02110"></a><span class="lineno"> 2110</span>  std::vector<std::pair<unsigned int, unsigned int>> padList;</div><div class="line"><a name="l02111"></a><span class="lineno"> 2111</span>  padList.reserve(flatBufferPadList->Length() / 2);</div><div class="line"><a name="l02112"></a><span class="lineno"> 2112</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < flatBufferPadList->Length() - 1; i += 2)</div><div class="line"><a name="l02113"></a><span class="lineno"> 2113</span>  {</div><div class="line"><a name="l02114"></a><span class="lineno"> 2114</span>  padList.emplace_back(flatBufferPadList->Get(i), flatBufferPadList->Get(i+1));</div><div class="line"><a name="l02115"></a><span class="lineno"> 2115</span>  }</div><div class="line"><a name="l02116"></a><span class="lineno"> 2116</span> </div><div class="line"><a name="l02117"></a><span class="lineno"> 2117</span>  <a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml">armnn::SpaceToBatchNdDescriptor</a> descriptor;</div><div class="line"><a name="l02118"></a><span class="lineno"> 2118</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div><div class="line"><a name="l02119"></a><span class="lineno"> 2119</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> =</div><div class="line"><a name="l02120"></a><span class="lineno"> 2120</span>  std::vector<unsigned int>(flatBufferBlockShape->begin(), flatBufferBlockShape->end());</div><div class="line"><a name="l02121"></a><span class="lineno"> 2121</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a> = padList;</div><div class="line"><a name="l02122"></a><span class="lineno"> 2122</span> </div><div class="line"><a name="l02123"></a><span class="lineno"> 2123</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02124"></a><span class="lineno"> 2124</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddSpaceToBatchNdLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02125"></a><span class="lineno"> 2125</span> </div><div class="line"><a name="l02126"></a><span class="lineno"> 2126</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02127"></a><span class="lineno"> 2127</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02128"></a><span class="lineno"> 2128</span> </div><div class="line"><a name="l02129"></a><span class="lineno"> 2129</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02130"></a><span class="lineno"> 2130</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02131"></a><span class="lineno"> 2131</span> }</div><div class="line"><a name="l02132"></a><span class="lineno"> 2132</span> </div><div class="line"><a name="l02133"></a><span class="lineno"> 2133</span> <span class="keywordtype">void</span> Deserializer::ParseSpaceToDepth(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02134"></a><span class="lineno"> 2134</span> {</div><div class="line"><a name="l02135"></a><span class="lineno"> 2135</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02136"></a><span class="lineno"> 2136</span> </div><div class="line"><a name="l02137"></a><span class="lineno"> 2137</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02138"></a><span class="lineno"> 2138</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02139"></a><span class="lineno"> 2139</span> </div><div class="line"><a name="l02140"></a><span class="lineno"> 2140</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02141"></a><span class="lineno"> 2141</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02142"></a><span class="lineno"> 2142</span> </div><div class="line"><a name="l02143"></a><span class="lineno"> 2143</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_SpaceToDepthLayer()->descriptor();</div><div class="line"><a name="l02144"></a><span class="lineno"> 2144</span> </div><div class="line"><a name="l02145"></a><span class="lineno"> 2145</span>  <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml">armnn::SpaceToDepthDescriptor</a> descriptor;</div><div class="line"><a name="l02146"></a><span class="lineno"> 2146</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a> = flatBufferDescriptor->blockSize();</div><div class="line"><a name="l02147"></a><span class="lineno"> 2147</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div><div class="line"><a name="l02148"></a><span class="lineno"> 2148</span> </div><div class="line"><a name="l02149"></a><span class="lineno"> 2149</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02150"></a><span class="lineno"> 2150</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddSpaceToDepthLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02151"></a><span class="lineno"> 2151</span> </div><div class="line"><a name="l02152"></a><span class="lineno"> 2152</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02153"></a><span class="lineno"> 2153</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02154"></a><span class="lineno"> 2154</span> </div><div class="line"><a name="l02155"></a><span class="lineno"> 2155</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02156"></a><span class="lineno"> 2156</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02157"></a><span class="lineno"> 2157</span> }</div><div class="line"><a name="l02158"></a><span class="lineno"> 2158</span> </div><div class="line"><a name="l02159"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#a920251d49a8f32085d458ba23f776800"> 2159</a></span> <a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml">armnn::NormalizationDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a920251d49a8f32085d458ba23f776800">Deserializer::GetNormalizationDescriptor</a>(</div><div class="line"><a name="l02160"></a><span class="lineno"> 2160</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a2a282cf18fcfe848b47e946327ca1048">Deserializer::NormalizationDescriptorPtr</a> normalizationDescriptor,</div><div class="line"><a name="l02161"></a><span class="lineno"> 2161</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02162"></a><span class="lineno"> 2162</span> {</div><div class="line"><a name="l02163"></a><span class="lineno"> 2163</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(layerIndex);</div><div class="line"><a name="l02164"></a><span class="lineno"> 2164</span>  <a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml">armnn::NormalizationDescriptor</a> desc;</div><div class="line"><a name="l02165"></a><span class="lineno"> 2165</span> </div><div class="line"><a name="l02166"></a><span class="lineno"> 2166</span>  <span class="keywordflow">switch</span> (normalizationDescriptor->normChannelType())</div><div class="line"><a name="l02167"></a><span class="lineno"> 2167</span>  {</div><div class="line"><a name="l02168"></a><span class="lineno"> 2168</span>  <span class="keywordflow">case</span> NormalizationAlgorithmChannel_Across:</div><div class="line"><a name="l02169"></a><span class="lineno"> 2169</span>  {</div><div class="line"><a name="l02170"></a><span class="lineno"> 2170</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml#afe1f0f09d49ad2befc01f8789187b7dd">m_NormChannelType</a> = <a class="code" href="namespacearmnn.xhtml#abe18a5033f2ab9c0de82c676b48f5437a810f43f3996922151c39b76143faeecc">armnn::NormalizationAlgorithmChannel::Across</a>;</div><div class="line"><a name="l02171"></a><span class="lineno"> 2171</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l02172"></a><span class="lineno"> 2172</span>  }</div><div class="line"><a name="l02173"></a><span class="lineno"> 2173</span>  <span class="keywordflow">case</span> NormalizationAlgorithmChannel_Within:</div><div class="line"><a name="l02174"></a><span class="lineno"> 2174</span>  {</div><div class="line"><a name="l02175"></a><span class="lineno"> 2175</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml#afe1f0f09d49ad2befc01f8789187b7dd">m_NormChannelType</a> = <a class="code" href="namespacearmnn.xhtml#abe18a5033f2ab9c0de82c676b48f5437a37bac6dce4f46277d89bfa3003e2e39b">armnn::NormalizationAlgorithmChannel::Within</a>;</div><div class="line"><a name="l02176"></a><span class="lineno"> 2176</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l02177"></a><span class="lineno"> 2177</span>  }</div><div class="line"><a name="l02178"></a><span class="lineno"> 2178</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l02179"></a><span class="lineno"> 2179</span>  {</div><div class="line"><a name="l02180"></a><span class="lineno"> 2180</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported normalization channel type"</span>);</div><div class="line"><a name="l02181"></a><span class="lineno"> 2181</span>  }</div><div class="line"><a name="l02182"></a><span class="lineno"> 2182</span>  }</div><div class="line"><a name="l02183"></a><span class="lineno"> 2183</span> </div><div class="line"><a name="l02184"></a><span class="lineno"> 2184</span>  <span class="keywordflow">switch</span> (normalizationDescriptor->normMethodType())</div><div class="line"><a name="l02185"></a><span class="lineno"> 2185</span>  {</div><div class="line"><a name="l02186"></a><span class="lineno"> 2186</span>  <span class="keywordflow">case</span> NormalizationAlgorithmMethod_LocalBrightness:</div><div class="line"><a name="l02187"></a><span class="lineno"> 2187</span>  {</div><div class="line"><a name="l02188"></a><span class="lineno"> 2188</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml#a05945f080edf694b631960728b87aadb">m_NormMethodType</a> = <a class="code" href="namespacearmnn.xhtml#ad605d1661fa0d8c7fea651d82fbe11c9ac65d2e51c610dd3853a3c777aa8bfe9d">armnn::NormalizationAlgorithmMethod::LocalBrightness</a>;</div><div class="line"><a name="l02189"></a><span class="lineno"> 2189</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l02190"></a><span class="lineno"> 2190</span>  }</div><div class="line"><a name="l02191"></a><span class="lineno"> 2191</span>  <span class="keywordflow">case</span> NormalizationAlgorithmMethod_LocalContrast:</div><div class="line"><a name="l02192"></a><span class="lineno"> 2192</span>  {</div><div class="line"><a name="l02193"></a><span class="lineno"> 2193</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml#a05945f080edf694b631960728b87aadb">m_NormMethodType</a> = <a class="code" href="namespacearmnn.xhtml#ad605d1661fa0d8c7fea651d82fbe11c9aa94d2fcabc6b001015aeddfa19266e6f">armnn::NormalizationAlgorithmMethod::LocalContrast</a>;</div><div class="line"><a name="l02194"></a><span class="lineno"> 2194</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l02195"></a><span class="lineno"> 2195</span>  }</div><div class="line"><a name="l02196"></a><span class="lineno"> 2196</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l02197"></a><span class="lineno"> 2197</span>  {</div><div class="line"><a name="l02198"></a><span class="lineno"> 2198</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported normalization method type"</span>);</div><div class="line"><a name="l02199"></a><span class="lineno"> 2199</span>  }</div><div class="line"><a name="l02200"></a><span class="lineno"> 2200</span>  }</div><div class="line"><a name="l02201"></a><span class="lineno"> 2201</span> </div><div class="line"><a name="l02202"></a><span class="lineno"> 2202</span>  <span class="keywordflow">switch</span> (normalizationDescriptor->dataLayout())</div><div class="line"><a name="l02203"></a><span class="lineno"> 2203</span>  {</div><div class="line"><a name="l02204"></a><span class="lineno"> 2204</span>  <span class="keywordflow">case</span> DataLayout_NCHW:</div><div class="line"><a name="l02205"></a><span class="lineno"> 2205</span>  {</div><div class="line"><a name="l02206"></a><span class="lineno"> 2206</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div><div class="line"><a name="l02207"></a><span class="lineno"> 2207</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l02208"></a><span class="lineno"> 2208</span>  }</div><div class="line"><a name="l02209"></a><span class="lineno"> 2209</span>  <span class="keywordflow">case</span> DataLayout_NHWC:</div><div class="line"><a name="l02210"></a><span class="lineno"> 2210</span>  {</div><div class="line"><a name="l02211"></a><span class="lineno"> 2211</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l02212"></a><span class="lineno"> 2212</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l02213"></a><span class="lineno"> 2213</span>  }</div><div class="line"><a name="l02214"></a><span class="lineno"> 2214</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l02215"></a><span class="lineno"> 2215</span>  {</div><div class="line"><a name="l02216"></a><span class="lineno"> 2216</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported data layout"</span>);</div><div class="line"><a name="l02217"></a><span class="lineno"> 2217</span>  }</div><div class="line"><a name="l02218"></a><span class="lineno"> 2218</span>  }</div><div class="line"><a name="l02219"></a><span class="lineno"> 2219</span> </div><div class="line"><a name="l02220"></a><span class="lineno"> 2220</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml#a174279be57d7596eeb04c6b7f7510f99">m_Alpha</a> = normalizationDescriptor->alpha();</div><div class="line"><a name="l02221"></a><span class="lineno"> 2221</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = normalizationDescriptor->beta();</div><div class="line"><a name="l02222"></a><span class="lineno"> 2222</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml#a8526ea7cf860d8e7f8340e9f9354f9f0">m_K</a> = normalizationDescriptor->k();</div><div class="line"><a name="l02223"></a><span class="lineno"> 2223</span>  desc.<a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml#aa70c05f1aad12fbd9d9ec43ea4557b03">m_NormSize</a> = normalizationDescriptor->normSize();</div><div class="line"><a name="l02224"></a><span class="lineno"> 2224</span> </div><div class="line"><a name="l02225"></a><span class="lineno"> 2225</span>  <span class="keywordflow">return</span> desc;</div><div class="line"><a name="l02226"></a><span class="lineno"> 2226</span> }</div><div class="line"><a name="l02227"></a><span class="lineno"> 2227</span> </div><div class="line"><a name="l02228"></a><span class="lineno"> 2228</span> <span class="keywordtype">void</span> Deserializer::ParseNormalization(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02229"></a><span class="lineno"> 2229</span> {</div><div class="line"><a name="l02230"></a><span class="lineno"> 2230</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02231"></a><span class="lineno"> 2231</span> </div><div class="line"><a name="l02232"></a><span class="lineno"> 2232</span>  <span class="keyword">auto</span> normalizationDes = graph->layers()->Get(layerIndex)->layer_as_NormalizationLayer()->descriptor();</div><div class="line"><a name="l02233"></a><span class="lineno"> 2233</span> </div><div class="line"><a name="l02234"></a><span class="lineno"> 2234</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02235"></a><span class="lineno"> 2235</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02236"></a><span class="lineno"> 2236</span> </div><div class="line"><a name="l02237"></a><span class="lineno"> 2237</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02238"></a><span class="lineno"> 2238</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02239"></a><span class="lineno"> 2239</span> </div><div class="line"><a name="l02240"></a><span class="lineno"> 2240</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02241"></a><span class="lineno"> 2241</span> </div><div class="line"><a name="l02242"></a><span class="lineno"> 2242</span>  <span class="keyword">auto</span> normalizationDescriptor = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a920251d49a8f32085d458ba23f776800">GetNormalizationDescriptor</a>(normalizationDes, layerIndex);</div><div class="line"><a name="l02243"></a><span class="lineno"> 2243</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02244"></a><span class="lineno"> 2244</span> </div><div class="line"><a name="l02245"></a><span class="lineno"> 2245</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddNormalizationLayer(normalizationDescriptor, layerName.c_str());</div><div class="line"><a name="l02246"></a><span class="lineno"> 2246</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l02247"></a><span class="lineno"> 2247</span> </div><div class="line"><a name="l02248"></a><span class="lineno"> 2248</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02249"></a><span class="lineno"> 2249</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02250"></a><span class="lineno"> 2250</span> }</div><div class="line"><a name="l02251"></a><span class="lineno"> 2251</span> </div><div class="line"><a name="l02252"></a><span class="lineno"> 2252</span> <span class="keywordtype">void</span> Deserializer::ParseRsqrt(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02253"></a><span class="lineno"> 2253</span> {</div><div class="line"><a name="l02254"></a><span class="lineno"> 2254</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02255"></a><span class="lineno"> 2255</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02256"></a><span class="lineno"> 2256</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l02257"></a><span class="lineno"> 2257</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02258"></a><span class="lineno"> 2258</span> </div><div class="line"><a name="l02259"></a><span class="lineno"> 2259</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02260"></a><span class="lineno"> 2260</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02261"></a><span class="lineno"> 2261</span> </div><div class="line"><a name="l02262"></a><span class="lineno"> 2262</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02263"></a><span class="lineno"> 2263</span> </div><div class="line"><a name="l02264"></a><span class="lineno"> 2264</span>  <a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.xhtml">armnn::ElementwiseUnaryDescriptor</a> descriptor(<a class="code" href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4">armnn::UnaryOperation::Rsqrt</a>);</div><div class="line"><a name="l02265"></a><span class="lineno"> 2265</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddElementwiseUnaryLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02266"></a><span class="lineno"> 2266</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02267"></a><span class="lineno"> 2267</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02268"></a><span class="lineno"> 2268</span> </div><div class="line"><a name="l02269"></a><span class="lineno"> 2269</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02270"></a><span class="lineno"> 2270</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02271"></a><span class="lineno"> 2271</span> }</div><div class="line"><a name="l02272"></a><span class="lineno"> 2272</span> </div><div class="line"><a name="l02273"></a><span class="lineno"> 2273</span> <span class="keywordtype">void</span> Deserializer::ParseSlice(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02274"></a><span class="lineno"> 2274</span> {</div><div class="line"><a name="l02275"></a><span class="lineno"> 2275</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02276"></a><span class="lineno"> 2276</span> </div><div class="line"><a name="l02277"></a><span class="lineno"> 2277</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02278"></a><span class="lineno"> 2278</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02279"></a><span class="lineno"> 2279</span> </div><div class="line"><a name="l02280"></a><span class="lineno"> 2280</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02281"></a><span class="lineno"> 2281</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02282"></a><span class="lineno"> 2282</span> </div><div class="line"><a name="l02283"></a><span class="lineno"> 2283</span>  <span class="keyword">auto</span> fbDescriptor = graph->layers()->Get(layerIndex)->layer_as_SliceLayer()->descriptor();</div><div class="line"><a name="l02284"></a><span class="lineno"> 2284</span> </div><div class="line"><a name="l02285"></a><span class="lineno"> 2285</span>  <span class="keyword">auto</span> fbBegin = fbDescriptor->begin();</div><div class="line"><a name="l02286"></a><span class="lineno"> 2286</span>  <span class="keyword">auto</span> fbSize = fbDescriptor->size();</div><div class="line"><a name="l02287"></a><span class="lineno"> 2287</span> </div><div class="line"><a name="l02288"></a><span class="lineno"> 2288</span>  <span class="keywordflow">if</span> (fbBegin->Length() != fbSize->Length())</div><div class="line"><a name="l02289"></a><span class="lineno"> 2289</span>  {</div><div class="line"><a name="l02290"></a><span class="lineno"> 2290</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(boost::str(</div><div class="line"><a name="l02291"></a><span class="lineno"> 2291</span>  boost::format(<span class="stringliteral">"Begin and size descriptors must have the same length %1%"</span>) % <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l02292"></a><span class="lineno"> 2292</span>  }</div><div class="line"><a name="l02293"></a><span class="lineno"> 2293</span> </div><div class="line"><a name="l02294"></a><span class="lineno"> 2294</span>  <a class="code" href="structarmnn_1_1_slice_descriptor.xhtml">armnn::SliceDescriptor</a> descriptor;</div><div class="line"><a name="l02295"></a><span class="lineno"> 2295</span>  descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.xhtml#a4939f00778f08d6c6fec6f74c0a59b7e">m_Begin</a>.insert(descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.xhtml#a4939f00778f08d6c6fec6f74c0a59b7e">m_Begin</a>.end(), fbBegin->begin(), fbBegin->end());</div><div class="line"><a name="l02296"></a><span class="lineno"> 2296</span>  descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.xhtml#ab52cabf19232290fa6b49828ba957ac0">m_Size</a>.insert(descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.xhtml#ab52cabf19232290fa6b49828ba957ac0">m_Size</a>.end(), fbSize->begin(), fbSize->end());</div><div class="line"><a name="l02297"></a><span class="lineno"> 2297</span> </div><div class="line"><a name="l02298"></a><span class="lineno"> 2298</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02299"></a><span class="lineno"> 2299</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddSliceLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02300"></a><span class="lineno"> 2300</span> </div><div class="line"><a name="l02301"></a><span class="lineno"> 2301</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02302"></a><span class="lineno"> 2302</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02303"></a><span class="lineno"> 2303</span> </div><div class="line"><a name="l02304"></a><span class="lineno"> 2304</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02305"></a><span class="lineno"> 2305</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02306"></a><span class="lineno"> 2306</span> }</div><div class="line"><a name="l02307"></a><span class="lineno"> 2307</span> </div><div class="line"><a name="l02308"></a><span class="lineno"> 2308</span> <span class="keywordtype">void</span> Deserializer::ParseStridedSlice(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02309"></a><span class="lineno"> 2309</span> {</div><div class="line"><a name="l02310"></a><span class="lineno"> 2310</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02311"></a><span class="lineno"> 2311</span> </div><div class="line"><a name="l02312"></a><span class="lineno"> 2312</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02313"></a><span class="lineno"> 2313</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02314"></a><span class="lineno"> 2314</span> </div><div class="line"><a name="l02315"></a><span class="lineno"> 2315</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02316"></a><span class="lineno"> 2316</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02317"></a><span class="lineno"> 2317</span> </div><div class="line"><a name="l02318"></a><span class="lineno"> 2318</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_StridedSliceLayer()->descriptor();</div><div class="line"><a name="l02319"></a><span class="lineno"> 2319</span> </div><div class="line"><a name="l02320"></a><span class="lineno"> 2320</span>  <span class="keyword">auto</span> flatBufferBegin = flatBufferDescriptor->begin();</div><div class="line"><a name="l02321"></a><span class="lineno"> 2321</span>  <span class="keyword">auto</span> flatBufferEnd = flatBufferDescriptor->end();</div><div class="line"><a name="l02322"></a><span class="lineno"> 2322</span>  <span class="keyword">auto</span> flatBufferStride = flatBufferDescriptor->stride();</div><div class="line"><a name="l02323"></a><span class="lineno"> 2323</span> </div><div class="line"><a name="l02324"></a><span class="lineno"> 2324</span>  <span class="keywordflow">if</span> (!(flatBufferBegin->Length() == flatBufferEnd->Length() &&</div><div class="line"><a name="l02325"></a><span class="lineno"> 2325</span>  flatBufferBegin->Length() == flatBufferStride->Length()))</div><div class="line"><a name="l02326"></a><span class="lineno"> 2326</span>  {</div><div class="line"><a name="l02327"></a><span class="lineno"> 2327</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(boost::str(</div><div class="line"><a name="l02328"></a><span class="lineno"> 2328</span>  boost::format(<span class="stringliteral">"The size of the begin, end, and stride must be equal %1%"</span>) % <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString()));</div><div class="line"><a name="l02329"></a><span class="lineno"> 2329</span>  }</div><div class="line"><a name="l02330"></a><span class="lineno"> 2330</span> </div><div class="line"><a name="l02331"></a><span class="lineno"> 2331</span>  std::vector<int> begin(flatBufferBegin->begin(), flatBufferBegin->end());</div><div class="line"><a name="l02332"></a><span class="lineno"> 2332</span>  std::vector<int> end(flatBufferEnd->begin(), flatBufferEnd->end());</div><div class="line"><a name="l02333"></a><span class="lineno"> 2333</span>  std::vector<int> stride(flatBufferStride->begin(), flatBufferStride->end());</div><div class="line"><a name="l02334"></a><span class="lineno"> 2334</span> </div><div class="line"><a name="l02335"></a><span class="lineno"> 2335</span>  <a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml">armnn::StridedSliceDescriptor</a> descriptor(begin, end, stride);</div><div class="line"><a name="l02336"></a><span class="lineno"> 2336</span>  descriptor.m_BeginMask = flatBufferDescriptor->beginMask();</div><div class="line"><a name="l02337"></a><span class="lineno"> 2337</span>  descriptor.m_EndMask = flatBufferDescriptor->endMask();</div><div class="line"><a name="l02338"></a><span class="lineno"> 2338</span>  descriptor.m_ShrinkAxisMask = flatBufferDescriptor->shrinkAxisMask();</div><div class="line"><a name="l02339"></a><span class="lineno"> 2339</span>  descriptor.m_EllipsisMask = flatBufferDescriptor->ellipsisMask();</div><div class="line"><a name="l02340"></a><span class="lineno"> 2340</span>  descriptor.m_NewAxisMask = flatBufferDescriptor->newAxisMask();</div><div class="line"><a name="l02341"></a><span class="lineno"> 2341</span>  descriptor.m_DataLayout = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(flatBufferDescriptor->dataLayout());</div><div class="line"><a name="l02342"></a><span class="lineno"> 2342</span> </div><div class="line"><a name="l02343"></a><span class="lineno"> 2343</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02344"></a><span class="lineno"> 2344</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddStridedSliceLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02345"></a><span class="lineno"> 2345</span> </div><div class="line"><a name="l02346"></a><span class="lineno"> 2346</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02347"></a><span class="lineno"> 2347</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02348"></a><span class="lineno"> 2348</span> </div><div class="line"><a name="l02349"></a><span class="lineno"> 2349</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02350"></a><span class="lineno"> 2350</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02351"></a><span class="lineno"> 2351</span> }</div><div class="line"><a name="l02352"></a><span class="lineno"> 2352</span> </div><div class="line"><a name="l02353"></a><span class="lineno"> 2353</span> <span class="keywordtype">void</span> Deserializer::ParseSubtraction(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02354"></a><span class="lineno"> 2354</span> {</div><div class="line"><a name="l02355"></a><span class="lineno"> 2355</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02356"></a><span class="lineno"> 2356</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02357"></a><span class="lineno"> 2357</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l02358"></a><span class="lineno"> 2358</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l02359"></a><span class="lineno"> 2359</span> </div><div class="line"><a name="l02360"></a><span class="lineno"> 2360</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02361"></a><span class="lineno"> 2361</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02362"></a><span class="lineno"> 2362</span> </div><div class="line"><a name="l02363"></a><span class="lineno"> 2363</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02364"></a><span class="lineno"> 2364</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddSubtractionLayer(layerName.c_str());</div><div class="line"><a name="l02365"></a><span class="lineno"> 2365</span> </div><div class="line"><a name="l02366"></a><span class="lineno"> 2366</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02367"></a><span class="lineno"> 2367</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02368"></a><span class="lineno"> 2368</span> </div><div class="line"><a name="l02369"></a><span class="lineno"> 2369</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02370"></a><span class="lineno"> 2370</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02371"></a><span class="lineno"> 2371</span> }</div><div class="line"><a name="l02372"></a><span class="lineno"> 2372</span> </div><div class="line"><a name="l02373"></a><span class="lineno"> 2373</span> <span class="keywordtype">void</span> Deserializer::ParseGather(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02374"></a><span class="lineno"> 2374</span> {</div><div class="line"><a name="l02375"></a><span class="lineno"> 2375</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02376"></a><span class="lineno"> 2376</span> </div><div class="line"><a name="l02377"></a><span class="lineno"> 2377</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02378"></a><span class="lineno"> 2378</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l02379"></a><span class="lineno"> 2379</span> </div><div class="line"><a name="l02380"></a><span class="lineno"> 2380</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02381"></a><span class="lineno"> 2381</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02382"></a><span class="lineno"> 2382</span> </div><div class="line"><a name="l02383"></a><span class="lineno"> 2383</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02384"></a><span class="lineno"> 2384</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddGatherLayer(layerName.c_str());</div><div class="line"><a name="l02385"></a><span class="lineno"> 2385</span> </div><div class="line"><a name="l02386"></a><span class="lineno"> 2386</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02387"></a><span class="lineno"> 2387</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02388"></a><span class="lineno"> 2388</span> </div><div class="line"><a name="l02389"></a><span class="lineno"> 2389</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02390"></a><span class="lineno"> 2390</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02391"></a><span class="lineno"> 2391</span> }</div><div class="line"><a name="l02392"></a><span class="lineno"> 2392</span> </div><div class="line"><a name="l02393"></a><span class="lineno"> 2393</span> <span class="keywordtype">void</span> Deserializer::ParseMean(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02394"></a><span class="lineno"> 2394</span> {</div><div class="line"><a name="l02395"></a><span class="lineno"> 2395</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02396"></a><span class="lineno"> 2396</span> </div><div class="line"><a name="l02397"></a><span class="lineno"> 2397</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02398"></a><span class="lineno"> 2398</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02399"></a><span class="lineno"> 2399</span> </div><div class="line"><a name="l02400"></a><span class="lineno"> 2400</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02401"></a><span class="lineno"> 2401</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02402"></a><span class="lineno"> 2402</span> </div><div class="line"><a name="l02403"></a><span class="lineno"> 2403</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_MeanLayer()->descriptor();</div><div class="line"><a name="l02404"></a><span class="lineno"> 2404</span>  <span class="keyword">auto</span> flatBufferAxis = flatBufferDescriptor->axis();</div><div class="line"><a name="l02405"></a><span class="lineno"> 2405</span>  <span class="keyword">auto</span> flatBufferKeepDims = flatBufferDescriptor->keepDims();</div><div class="line"><a name="l02406"></a><span class="lineno"> 2406</span> </div><div class="line"><a name="l02407"></a><span class="lineno"> 2407</span>  <a class="code" href="structarmnn_1_1_mean_descriptor.xhtml">armnn::MeanDescriptor</a> descriptor;</div><div class="line"><a name="l02408"></a><span class="lineno"> 2408</span>  descriptor.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a> = std::vector<unsigned int>(flatBufferAxis->begin(), flatBufferAxis->end());</div><div class="line"><a name="l02409"></a><span class="lineno"> 2409</span>  descriptor.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a28e0548abfc4e79c48f29a3d11a062e9">m_KeepDims</a> = flatBufferKeepDims;</div><div class="line"><a name="l02410"></a><span class="lineno"> 2410</span> </div><div class="line"><a name="l02411"></a><span class="lineno"> 2411</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02412"></a><span class="lineno"> 2412</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddMeanLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02413"></a><span class="lineno"> 2413</span> </div><div class="line"><a name="l02414"></a><span class="lineno"> 2414</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02415"></a><span class="lineno"> 2415</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02416"></a><span class="lineno"> 2416</span> </div><div class="line"><a name="l02417"></a><span class="lineno"> 2417</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02418"></a><span class="lineno"> 2418</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02419"></a><span class="lineno"> 2419</span> }</div><div class="line"><a name="l02420"></a><span class="lineno"> 2420</span> </div><div class="line"><a name="l02421"></a><span class="lineno"> 2421</span> <span class="keywordtype">void</span> Deserializer::ParseSplitter(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02422"></a><span class="lineno"> 2422</span> {</div><div class="line"><a name="l02423"></a><span class="lineno"> 2423</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02424"></a><span class="lineno"> 2424</span> </div><div class="line"><a name="l02425"></a><span class="lineno"> 2425</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02426"></a><span class="lineno"> 2426</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02427"></a><span class="lineno"> 2427</span> </div><div class="line"><a name="l02428"></a><span class="lineno"> 2428</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02429"></a><span class="lineno"> 2429</span> </div><div class="line"><a name="l02430"></a><span class="lineno"> 2430</span>  <span class="keyword">auto</span> flatBufferViewsDescriptor = graph->layers()->Get(layerIndex)->layer_as_SplitterLayer()->descriptor();</div><div class="line"><a name="l02431"></a><span class="lineno"> 2431</span>  <span class="keyword">auto</span> flatBufferViewSizes = flatBufferViewsDescriptor->viewSizes();</div><div class="line"><a name="l02432"></a><span class="lineno"> 2432</span>  <span class="keyword">auto</span> flatBufferOriginsDescriptor = flatBufferViewsDescriptor->origins();</div><div class="line"><a name="l02433"></a><span class="lineno"> 2433</span>  <span class="keyword">auto</span> flatBufferViewOrigins = flatBufferOriginsDescriptor->viewOrigins();</div><div class="line"><a name="l02434"></a><span class="lineno"> 2434</span>  uint32_t numViews = flatBufferOriginsDescriptor->numViews();</div><div class="line"><a name="l02435"></a><span class="lineno"> 2435</span>  uint32_t numDimensions = flatBufferOriginsDescriptor->numDimensions();</div><div class="line"><a name="l02436"></a><span class="lineno"> 2436</span> </div><div class="line"><a name="l02437"></a><span class="lineno"> 2437</span>  <span class="comment">// Check numViews and numDimensions corresponds to the ones already serialized ...</span></div><div class="line"><a name="l02438"></a><span class="lineno"> 2438</span>  <span class="comment">// numViews == flatBufferViewSizes.size();</span></div><div class="line"><a name="l02439"></a><span class="lineno"> 2439</span>  <span class="comment">// foreach: numDimensions == flatBufferViewSizes[x].size();</span></div><div class="line"><a name="l02440"></a><span class="lineno"> 2440</span> </div><div class="line"><a name="l02441"></a><span class="lineno"> 2441</span>  <a class="code" href="structarmnn_1_1_views_descriptor.xhtml">armnn::ViewsDescriptor</a> viewsDescriptor(numViews, numDimensions);</div><div class="line"><a name="l02442"></a><span class="lineno"> 2442</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> vIdx = 0; vIdx < numViews; ++vIdx)</div><div class="line"><a name="l02443"></a><span class="lineno"> 2443</span>  {</div><div class="line"><a name="l02444"></a><span class="lineno"> 2444</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dIdx = 0; dIdx < numDimensions; ++dIdx)</div><div class="line"><a name="l02445"></a><span class="lineno"> 2445</span>  {</div><div class="line"><a name="l02446"></a><span class="lineno"> 2446</span>  viewsDescriptor.<a class="code" href="structarmnn_1_1_views_descriptor.xhtml#aae0893695f5803a3517985c7cb1ccb2e">SetViewSize</a>(vIdx, dIdx, flatBufferViewSizes->Get(vIdx)->data()->Get(dIdx));</div><div class="line"><a name="l02447"></a><span class="lineno"> 2447</span>  viewsDescriptor.<a class="code" href="structarmnn_1_1_views_descriptor.xhtml#a2b125117aa61f9baf3a9cb8658aa61a2">SetViewOriginCoord</a>(vIdx, dIdx, flatBufferViewOrigins->Get(vIdx)->data()->Get(dIdx));</div><div class="line"><a name="l02448"></a><span class="lineno"> 2448</span>  }</div><div class="line"><a name="l02449"></a><span class="lineno"> 2449</span>  }</div><div class="line"><a name="l02450"></a><span class="lineno"> 2450</span> </div><div class="line"><a name="l02451"></a><span class="lineno"> 2451</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02452"></a><span class="lineno"> 2452</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddSplitterLayer(viewsDescriptor, layerName.c_str());</div><div class="line"><a name="l02453"></a><span class="lineno"> 2453</span> </div><div class="line"><a name="l02454"></a><span class="lineno"> 2454</span>  <span class="comment">// I could have as many outputs as views ...</span></div><div class="line"><a name="l02455"></a><span class="lineno"> 2455</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> vIdx = 0; vIdx < numViews; ++vIdx)</div><div class="line"><a name="l02456"></a><span class="lineno"> 2456</span>  {</div><div class="line"><a name="l02457"></a><span class="lineno"> 2457</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[vIdx]);</div><div class="line"><a name="l02458"></a><span class="lineno"> 2458</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(vIdx).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02459"></a><span class="lineno"> 2459</span>  }</div><div class="line"><a name="l02460"></a><span class="lineno"> 2460</span> </div><div class="line"><a name="l02461"></a><span class="lineno"> 2461</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02462"></a><span class="lineno"> 2462</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02463"></a><span class="lineno"> 2463</span> }</div><div class="line"><a name="l02464"></a><span class="lineno"> 2464</span> </div><div class="line"><a name="l02465"></a><span class="lineno"><a class="line" href="classarmnn_deserializer_1_1_deserializer.xhtml#af7bb02c61c6a5663121da024b7e042e8"> 2465</a></span> <a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml">armnn::LstmDescriptor</a> <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af7bb02c61c6a5663121da024b7e042e8">Deserializer::GetLstmDescriptor</a>(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a15397ee26bc4b7d3a459b05e457be428">Deserializer::LstmDescriptorPtr</a> lstmDescriptor)</div><div class="line"><a name="l02466"></a><span class="lineno"> 2466</span> {</div><div class="line"><a name="l02467"></a><span class="lineno"> 2467</span>  <a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml">armnn::LstmDescriptor</a> desc;</div><div class="line"><a name="l02468"></a><span class="lineno"> 2468</span> </div><div class="line"><a name="l02469"></a><span class="lineno"> 2469</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = lstmDescriptor->activationFunc();</div><div class="line"><a name="l02470"></a><span class="lineno"> 2470</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = lstmDescriptor->clippingThresCell();</div><div class="line"><a name="l02471"></a><span class="lineno"> 2471</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">m_ClippingThresProj</a> = lstmDescriptor->clippingThresProj();</div><div class="line"><a name="l02472"></a><span class="lineno"> 2472</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = lstmDescriptor->cifgEnabled();</div><div class="line"><a name="l02473"></a><span class="lineno"> 2473</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = lstmDescriptor->peepholeEnabled();</div><div class="line"><a name="l02474"></a><span class="lineno"> 2474</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = lstmDescriptor->projectionEnabled();</div><div class="line"><a name="l02475"></a><span class="lineno"> 2475</span>  desc.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = lstmDescriptor->layerNormEnabled();</div><div class="line"><a name="l02476"></a><span class="lineno"> 2476</span> </div><div class="line"><a name="l02477"></a><span class="lineno"> 2477</span>  <span class="keywordflow">return</span> desc;</div><div class="line"><a name="l02478"></a><span class="lineno"> 2478</span> }</div><div class="line"><a name="l02479"></a><span class="lineno"> 2479</span> </div><div class="line"><a name="l02480"></a><span class="lineno"> 2480</span> <span class="keywordtype">void</span> Deserializer::ParseLstm(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02481"></a><span class="lineno"> 2481</span> {</div><div class="line"><a name="l02482"></a><span class="lineno"> 2482</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02483"></a><span class="lineno"> 2483</span> </div><div class="line"><a name="l02484"></a><span class="lineno"> 2484</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02485"></a><span class="lineno"> 2485</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div><div class="line"><a name="l02486"></a><span class="lineno"> 2486</span> </div><div class="line"><a name="l02487"></a><span class="lineno"> 2487</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02488"></a><span class="lineno"> 2488</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 4);</div><div class="line"><a name="l02489"></a><span class="lineno"> 2489</span> </div><div class="line"><a name="l02490"></a><span class="lineno"> 2490</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_LstmLayer();</div><div class="line"><a name="l02491"></a><span class="lineno"> 2491</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02492"></a><span class="lineno"> 2492</span>  <span class="keyword">auto</span> flatBufferDescriptor = flatBufferLayer->descriptor();</div><div class="line"><a name="l02493"></a><span class="lineno"> 2493</span>  <span class="keyword">auto</span> flatBufferInputParams = flatBufferLayer->inputParams();</div><div class="line"><a name="l02494"></a><span class="lineno"> 2494</span> </div><div class="line"><a name="l02495"></a><span class="lineno"> 2495</span>  <span class="keyword">auto</span> lstmDescriptor = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af7bb02c61c6a5663121da024b7e042e8">GetLstmDescriptor</a>(flatBufferDescriptor);</div><div class="line"><a name="l02496"></a><span class="lineno"> 2496</span> </div><div class="line"><a name="l02497"></a><span class="lineno"> 2497</span>  <a class="code" href="structarmnn_1_1_lstm_input_params.xhtml">armnn::LstmInputParams</a> lstmInputParams;</div><div class="line"><a name="l02498"></a><span class="lineno"> 2498</span> </div><div class="line"><a name="l02499"></a><span class="lineno"> 2499</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputToForgetWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputToForgetWeights());</div><div class="line"><a name="l02500"></a><span class="lineno"> 2500</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputToCellWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputToCellWeights());</div><div class="line"><a name="l02501"></a><span class="lineno"> 2501</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputToOutputWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputToOutputWeights());</div><div class="line"><a name="l02502"></a><span class="lineno"> 2502</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> recurrentToForgetWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->recurrentToForgetWeights());</div><div class="line"><a name="l02503"></a><span class="lineno"> 2503</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> recurrentToCellWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->recurrentToCellWeights());</div><div class="line"><a name="l02504"></a><span class="lineno"> 2504</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> recurrentToOutputWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->recurrentToOutputWeights());</div><div class="line"><a name="l02505"></a><span class="lineno"> 2505</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> forgetGateBias = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->forgetGateBias());</div><div class="line"><a name="l02506"></a><span class="lineno"> 2506</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> cellBias = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->cellBias());</div><div class="line"><a name="l02507"></a><span class="lineno"> 2507</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> outputGateBias = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->outputGateBias());</div><div class="line"><a name="l02508"></a><span class="lineno"> 2508</span> </div><div class="line"><a name="l02509"></a><span class="lineno"> 2509</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &inputToForgetWeights;</div><div class="line"><a name="l02510"></a><span class="lineno"> 2510</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &inputToCellWeights;</div><div class="line"><a name="l02511"></a><span class="lineno"> 2511</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &inputToOutputWeights;</div><div class="line"><a name="l02512"></a><span class="lineno"> 2512</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeights;</div><div class="line"><a name="l02513"></a><span class="lineno"> 2513</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &recurrentToCellWeights;</div><div class="line"><a name="l02514"></a><span class="lineno"> 2514</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeights;</div><div class="line"><a name="l02515"></a><span class="lineno"> 2515</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &forgetGateBias;</div><div class="line"><a name="l02516"></a><span class="lineno"> 2516</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &cellBias;</div><div class="line"><a name="l02517"></a><span class="lineno"> 2517</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &outputGateBias;</div><div class="line"><a name="l02518"></a><span class="lineno"> 2518</span> </div><div class="line"><a name="l02519"></a><span class="lineno"> 2519</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputToInputWeights;</div><div class="line"><a name="l02520"></a><span class="lineno"> 2520</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> recurrentToInputWeights;</div><div class="line"><a name="l02521"></a><span class="lineno"> 2521</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> cellToInputWeights;</div><div class="line"><a name="l02522"></a><span class="lineno"> 2522</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputGateBias;</div><div class="line"><a name="l02523"></a><span class="lineno"> 2523</span>  <span class="keywordflow">if</span> (!lstmDescriptor.m_CifgEnabled)</div><div class="line"><a name="l02524"></a><span class="lineno"> 2524</span>  {</div><div class="line"><a name="l02525"></a><span class="lineno"> 2525</span>  inputToInputWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputToInputWeights());</div><div class="line"><a name="l02526"></a><span class="lineno"> 2526</span>  recurrentToInputWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->recurrentToInputWeights());</div><div class="line"><a name="l02527"></a><span class="lineno"> 2527</span>  cellToInputWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->cellToInputWeights());</div><div class="line"><a name="l02528"></a><span class="lineno"> 2528</span>  inputGateBias = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputGateBias());</div><div class="line"><a name="l02529"></a><span class="lineno"> 2529</span> </div><div class="line"><a name="l02530"></a><span class="lineno"> 2530</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &inputToInputWeights;</div><div class="line"><a name="l02531"></a><span class="lineno"> 2531</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &recurrentToInputWeights;</div><div class="line"><a name="l02532"></a><span class="lineno"> 2532</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a> = &cellToInputWeights;</div><div class="line"><a name="l02533"></a><span class="lineno"> 2533</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &inputGateBias;</div><div class="line"><a name="l02534"></a><span class="lineno"> 2534</span>  }</div><div class="line"><a name="l02535"></a><span class="lineno"> 2535</span> </div><div class="line"><a name="l02536"></a><span class="lineno"> 2536</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> projectionWeights;</div><div class="line"><a name="l02537"></a><span class="lineno"> 2537</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> projectionBias;</div><div class="line"><a name="l02538"></a><span class="lineno"> 2538</span>  <span class="keywordflow">if</span> (lstmDescriptor.m_ProjectionEnabled)</div><div class="line"><a name="l02539"></a><span class="lineno"> 2539</span>  {</div><div class="line"><a name="l02540"></a><span class="lineno"> 2540</span>  projectionWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->projectionWeights());</div><div class="line"><a name="l02541"></a><span class="lineno"> 2541</span>  projectionBias = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->projectionBias());</div><div class="line"><a name="l02542"></a><span class="lineno"> 2542</span> </div><div class="line"><a name="l02543"></a><span class="lineno"> 2543</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a> = &projectionWeights;</div><div class="line"><a name="l02544"></a><span class="lineno"> 2544</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a> = &projectionBias;</div><div class="line"><a name="l02545"></a><span class="lineno"> 2545</span>  }</div><div class="line"><a name="l02546"></a><span class="lineno"> 2546</span> </div><div class="line"><a name="l02547"></a><span class="lineno"> 2547</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> cellToForgetWeights;</div><div class="line"><a name="l02548"></a><span class="lineno"> 2548</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> cellToOutputWeights;</div><div class="line"><a name="l02549"></a><span class="lineno"> 2549</span>  <span class="keywordflow">if</span> (lstmDescriptor.m_PeepholeEnabled)</div><div class="line"><a name="l02550"></a><span class="lineno"> 2550</span>  {</div><div class="line"><a name="l02551"></a><span class="lineno"> 2551</span>  cellToForgetWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->cellToForgetWeights());</div><div class="line"><a name="l02552"></a><span class="lineno"> 2552</span>  cellToOutputWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->cellToOutputWeights());</div><div class="line"><a name="l02553"></a><span class="lineno"> 2553</span> </div><div class="line"><a name="l02554"></a><span class="lineno"> 2554</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a> = &cellToForgetWeights;</div><div class="line"><a name="l02555"></a><span class="lineno"> 2555</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a> = &cellToOutputWeights;</div><div class="line"><a name="l02556"></a><span class="lineno"> 2556</span>  }</div><div class="line"><a name="l02557"></a><span class="lineno"> 2557</span> </div><div class="line"><a name="l02558"></a><span class="lineno"> 2558</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputLayerNormWeights;</div><div class="line"><a name="l02559"></a><span class="lineno"> 2559</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> forgetLayerNormWeights;</div><div class="line"><a name="l02560"></a><span class="lineno"> 2560</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> cellLayerNormWeights;</div><div class="line"><a name="l02561"></a><span class="lineno"> 2561</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> outputLayerNormWeights;</div><div class="line"><a name="l02562"></a><span class="lineno"> 2562</span>  <span class="keywordflow">if</span> (lstmDescriptor.m_LayerNormEnabled)</div><div class="line"><a name="l02563"></a><span class="lineno"> 2563</span>  {</div><div class="line"><a name="l02564"></a><span class="lineno"> 2564</span>  <span class="keywordflow">if</span> (!lstmDescriptor.m_CifgEnabled)</div><div class="line"><a name="l02565"></a><span class="lineno"> 2565</span>  {</div><div class="line"><a name="l02566"></a><span class="lineno"> 2566</span>  inputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputLayerNormWeights());</div><div class="line"><a name="l02567"></a><span class="lineno"> 2567</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a0cd848f65ec31778d708852f0042fe37">m_InputLayerNormWeights</a> = &inputLayerNormWeights;</div><div class="line"><a name="l02568"></a><span class="lineno"> 2568</span>  }</div><div class="line"><a name="l02569"></a><span class="lineno"> 2569</span>  forgetLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->forgetLayerNormWeights());</div><div class="line"><a name="l02570"></a><span class="lineno"> 2570</span>  cellLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->cellLayerNormWeights());</div><div class="line"><a name="l02571"></a><span class="lineno"> 2571</span>  outputLayerNormWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->outputLayerNormWeights());</div><div class="line"><a name="l02572"></a><span class="lineno"> 2572</span> </div><div class="line"><a name="l02573"></a><span class="lineno"> 2573</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#af0f796fba1a2be9c56b4c9ee534577ee">m_ForgetLayerNormWeights</a> = &forgetLayerNormWeights;</div><div class="line"><a name="l02574"></a><span class="lineno"> 2574</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ad0b8c32bb5381f4cc999093ba3b98b43">m_CellLayerNormWeights</a> = &cellLayerNormWeights;</div><div class="line"><a name="l02575"></a><span class="lineno"> 2575</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a9b18daea2e9f42386055326fd016519a">m_OutputLayerNormWeights</a> = &outputLayerNormWeights;</div><div class="line"><a name="l02576"></a><span class="lineno"> 2576</span>  }</div><div class="line"><a name="l02577"></a><span class="lineno"> 2577</span> </div><div class="line"><a name="l02578"></a><span class="lineno"> 2578</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddLstmLayer(lstmDescriptor, lstmInputParams, layerName.c_str());</div><div class="line"><a name="l02579"></a><span class="lineno"> 2579</span> </div><div class="line"><a name="l02580"></a><span class="lineno"> 2580</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo1 = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02581"></a><span class="lineno"> 2581</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo1);</div><div class="line"><a name="l02582"></a><span class="lineno"> 2582</span> </div><div class="line"><a name="l02583"></a><span class="lineno"> 2583</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo2 = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[1]);</div><div class="line"><a name="l02584"></a><span class="lineno"> 2584</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo2);</div><div class="line"><a name="l02585"></a><span class="lineno"> 2585</span> </div><div class="line"><a name="l02586"></a><span class="lineno"> 2586</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo3 = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[2]);</div><div class="line"><a name="l02587"></a><span class="lineno"> 2587</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo3);</div><div class="line"><a name="l02588"></a><span class="lineno"> 2588</span> </div><div class="line"><a name="l02589"></a><span class="lineno"> 2589</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo4 = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[3]);</div><div class="line"><a name="l02590"></a><span class="lineno"> 2590</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(3).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo4);</div><div class="line"><a name="l02591"></a><span class="lineno"> 2591</span> </div><div class="line"><a name="l02592"></a><span class="lineno"> 2592</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02593"></a><span class="lineno"> 2593</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02594"></a><span class="lineno"> 2594</span> }</div><div class="line"><a name="l02595"></a><span class="lineno"> 2595</span> </div><div class="line"><a name="l02596"></a><span class="lineno"> 2596</span> <span class="keywordtype">void</span> Deserializer::ParseQuantizedLstm(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02597"></a><span class="lineno"> 2597</span> {</div><div class="line"><a name="l02598"></a><span class="lineno"> 2598</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02599"></a><span class="lineno"> 2599</span> </div><div class="line"><a name="l02600"></a><span class="lineno"> 2600</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02601"></a><span class="lineno"> 2601</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 3);</div><div class="line"><a name="l02602"></a><span class="lineno"> 2602</span> </div><div class="line"><a name="l02603"></a><span class="lineno"> 2603</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02604"></a><span class="lineno"> 2604</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 2);</div><div class="line"><a name="l02605"></a><span class="lineno"> 2605</span> </div><div class="line"><a name="l02606"></a><span class="lineno"> 2606</span>  <span class="keyword">auto</span> flatBufferLayer = graph->layers()->Get(layerIndex)->layer_as_QuantizedLstmLayer();</div><div class="line"><a name="l02607"></a><span class="lineno"> 2607</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02608"></a><span class="lineno"> 2608</span>  <span class="keyword">auto</span> flatBufferInputParams = flatBufferLayer->inputParams();</div><div class="line"><a name="l02609"></a><span class="lineno"> 2609</span> </div><div class="line"><a name="l02610"></a><span class="lineno"> 2610</span>  <a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml">armnn::QuantizedLstmInputParams</a> lstmInputParams;</div><div class="line"><a name="l02611"></a><span class="lineno"> 2611</span> </div><div class="line"><a name="l02612"></a><span class="lineno"> 2612</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputToInputWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputToInputWeights());</div><div class="line"><a name="l02613"></a><span class="lineno"> 2613</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputToForgetWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputToForgetWeights());</div><div class="line"><a name="l02614"></a><span class="lineno"> 2614</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputToCellWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputToCellWeights());</div><div class="line"><a name="l02615"></a><span class="lineno"> 2615</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputToOutputWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputToOutputWeights());</div><div class="line"><a name="l02616"></a><span class="lineno"> 2616</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> recurrentToInputWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->recurrentToInputWeights());</div><div class="line"><a name="l02617"></a><span class="lineno"> 2617</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> recurrentToForgetWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->recurrentToForgetWeights());</div><div class="line"><a name="l02618"></a><span class="lineno"> 2618</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> recurrentToCellWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->recurrentToCellWeights());</div><div class="line"><a name="l02619"></a><span class="lineno"> 2619</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> recurrentToOutputWeights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->recurrentToOutputWeights());</div><div class="line"><a name="l02620"></a><span class="lineno"> 2620</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> inputGateBias = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->inputGateBias());</div><div class="line"><a name="l02621"></a><span class="lineno"> 2621</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> forgetGateBias = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->forgetGateBias());</div><div class="line"><a name="l02622"></a><span class="lineno"> 2622</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> cellBias = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->cellBias());</div><div class="line"><a name="l02623"></a><span class="lineno"> 2623</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> outputGateBias = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(flatBufferInputParams->outputGateBias());</div><div class="line"><a name="l02624"></a><span class="lineno"> 2624</span> </div><div class="line"><a name="l02625"></a><span class="lineno"> 2625</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &inputToInputWeights;</div><div class="line"><a name="l02626"></a><span class="lineno"> 2626</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &inputToForgetWeights;</div><div class="line"><a name="l02627"></a><span class="lineno"> 2627</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &inputToCellWeights;</div><div class="line"><a name="l02628"></a><span class="lineno"> 2628</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &inputToOutputWeights;</div><div class="line"><a name="l02629"></a><span class="lineno"> 2629</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &recurrentToInputWeights;</div><div class="line"><a name="l02630"></a><span class="lineno"> 2630</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeights;</div><div class="line"><a name="l02631"></a><span class="lineno"> 2631</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &recurrentToCellWeights;</div><div class="line"><a name="l02632"></a><span class="lineno"> 2632</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeights;</div><div class="line"><a name="l02633"></a><span class="lineno"> 2633</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &inputGateBias;</div><div class="line"><a name="l02634"></a><span class="lineno"> 2634</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &forgetGateBias;</div><div class="line"><a name="l02635"></a><span class="lineno"> 2635</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &cellBias;</div><div class="line"><a name="l02636"></a><span class="lineno"> 2636</span>  lstmInputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &outputGateBias;</div><div class="line"><a name="l02637"></a><span class="lineno"> 2637</span> </div><div class="line"><a name="l02638"></a><span class="lineno"> 2638</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddQuantizedLstmLayer(lstmInputParams, layerName.c_str());</div><div class="line"><a name="l02639"></a><span class="lineno"> 2639</span> </div><div class="line"><a name="l02640"></a><span class="lineno"> 2640</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo1 = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02641"></a><span class="lineno"> 2641</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo1);</div><div class="line"><a name="l02642"></a><span class="lineno"> 2642</span> </div><div class="line"><a name="l02643"></a><span class="lineno"> 2643</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo2 = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[1]);</div><div class="line"><a name="l02644"></a><span class="lineno"> 2644</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo2);</div><div class="line"><a name="l02645"></a><span class="lineno"> 2645</span> </div><div class="line"><a name="l02646"></a><span class="lineno"> 2646</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02647"></a><span class="lineno"> 2647</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02648"></a><span class="lineno"> 2648</span> }</div><div class="line"><a name="l02649"></a><span class="lineno"> 2649</span> </div><div class="line"><a name="l02650"></a><span class="lineno"> 2650</span> <span class="keywordtype">void</span> Deserializer::ParseDequantize(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02651"></a><span class="lineno"> 2651</span> {</div><div class="line"><a name="l02652"></a><span class="lineno"> 2652</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02653"></a><span class="lineno"> 2653</span> </div><div class="line"><a name="l02654"></a><span class="lineno"> 2654</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02655"></a><span class="lineno"> 2655</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02656"></a><span class="lineno"> 2656</span> </div><div class="line"><a name="l02657"></a><span class="lineno"> 2657</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02658"></a><span class="lineno"> 2658</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02659"></a><span class="lineno"> 2659</span> </div><div class="line"><a name="l02660"></a><span class="lineno"> 2660</span>  <span class="keyword">const</span> std::string layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02661"></a><span class="lineno"> 2661</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddDequantizeLayer(layerName.c_str());</div><div class="line"><a name="l02662"></a><span class="lineno"> 2662</span> </div><div class="line"><a name="l02663"></a><span class="lineno"> 2663</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02664"></a><span class="lineno"> 2664</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02665"></a><span class="lineno"> 2665</span> </div><div class="line"><a name="l02666"></a><span class="lineno"> 2666</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02667"></a><span class="lineno"> 2667</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02668"></a><span class="lineno"> 2668</span> }</div><div class="line"><a name="l02669"></a><span class="lineno"> 2669</span> </div><div class="line"><a name="l02670"></a><span class="lineno"> 2670</span> <span class="keywordtype">void</span> Deserializer::ParseMerge(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02671"></a><span class="lineno"> 2671</span> {</div><div class="line"><a name="l02672"></a><span class="lineno"> 2672</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02673"></a><span class="lineno"> 2673</span> </div><div class="line"><a name="l02674"></a><span class="lineno"> 2674</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02675"></a><span class="lineno"> 2675</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l02676"></a><span class="lineno"> 2676</span> </div><div class="line"><a name="l02677"></a><span class="lineno"> 2677</span>  <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">Deserializer::TensorRawPtrVector</a> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02678"></a><span class="lineno"> 2678</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02679"></a><span class="lineno"> 2679</span> </div><div class="line"><a name="l02680"></a><span class="lineno"> 2680</span>  <span class="keyword">const</span> std::string layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02681"></a><span class="lineno"> 2681</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddMergeLayer(layerName.c_str());</div><div class="line"><a name="l02682"></a><span class="lineno"> 2682</span> </div><div class="line"><a name="l02683"></a><span class="lineno"> 2683</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02684"></a><span class="lineno"> 2684</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02685"></a><span class="lineno"> 2685</span> </div><div class="line"><a name="l02686"></a><span class="lineno"> 2686</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02687"></a><span class="lineno"> 2687</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02688"></a><span class="lineno"> 2688</span> }</div><div class="line"><a name="l02689"></a><span class="lineno"> 2689</span> </div><div class="line"><a name="l02690"></a><span class="lineno"> 2690</span> <span class="keywordtype">void</span> Deserializer::ParseSwitch(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02691"></a><span class="lineno"> 2691</span> {</div><div class="line"><a name="l02692"></a><span class="lineno"> 2692</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02693"></a><span class="lineno"> 2693</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02694"></a><span class="lineno"> 2694</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l02695"></a><span class="lineno"> 2695</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l02696"></a><span class="lineno"> 2696</span> </div><div class="line"><a name="l02697"></a><span class="lineno"> 2697</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02698"></a><span class="lineno"> 2698</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 2);</div><div class="line"><a name="l02699"></a><span class="lineno"> 2699</span> </div><div class="line"><a name="l02700"></a><span class="lineno"> 2700</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02701"></a><span class="lineno"> 2701</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddSwitchLayer(layerName.c_str());</div><div class="line"><a name="l02702"></a><span class="lineno"> 2702</span> </div><div class="line"><a name="l02703"></a><span class="lineno"> 2703</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> output0TensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02704"></a><span class="lineno"> 2704</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(output0TensorInfo);</div><div class="line"><a name="l02705"></a><span class="lineno"> 2705</span> </div><div class="line"><a name="l02706"></a><span class="lineno"> 2706</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> output1TensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[1]);</div><div class="line"><a name="l02707"></a><span class="lineno"> 2707</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(output1TensorInfo);</div><div class="line"><a name="l02708"></a><span class="lineno"> 2708</span> </div><div class="line"><a name="l02709"></a><span class="lineno"> 2709</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02710"></a><span class="lineno"> 2710</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02711"></a><span class="lineno"> 2711</span> }</div><div class="line"><a name="l02712"></a><span class="lineno"> 2712</span> </div><div class="line"><a name="l02713"></a><span class="lineno"> 2713</span> <span class="keywordtype">void</span> Deserializer::ParsePrelu(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02714"></a><span class="lineno"> 2714</span> {</div><div class="line"><a name="l02715"></a><span class="lineno"> 2715</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02716"></a><span class="lineno"> 2716</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02717"></a><span class="lineno"> 2717</span>  <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>();</div><div class="line"><a name="l02718"></a><span class="lineno"> 2718</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 2);</div><div class="line"><a name="l02719"></a><span class="lineno"> 2719</span> </div><div class="line"><a name="l02720"></a><span class="lineno"> 2720</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02721"></a><span class="lineno"> 2721</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02722"></a><span class="lineno"> 2722</span> </div><div class="line"><a name="l02723"></a><span class="lineno"> 2723</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02724"></a><span class="lineno"> 2724</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddPreluLayer(layerName.c_str());</div><div class="line"><a name="l02725"></a><span class="lineno"> 2725</span> </div><div class="line"><a name="l02726"></a><span class="lineno"> 2726</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02727"></a><span class="lineno"> 2727</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02728"></a><span class="lineno"> 2728</span> </div><div class="line"><a name="l02729"></a><span class="lineno"> 2729</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02730"></a><span class="lineno"> 2730</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02731"></a><span class="lineno"> 2731</span> }</div><div class="line"><a name="l02732"></a><span class="lineno"> 2732</span> </div><div class="line"><a name="l02733"></a><span class="lineno"> 2733</span> <span class="keywordtype">void</span> Deserializer::ParseTranspose(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02734"></a><span class="lineno"> 2734</span> {</div><div class="line"><a name="l02735"></a><span class="lineno"> 2735</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02736"></a><span class="lineno"> 2736</span> </div><div class="line"><a name="l02737"></a><span class="lineno"> 2737</span>  <span class="keyword">auto</span> dimsMapping = graph->layers()->Get(layerIndex)->layer_as_TransposeLayer()->descriptor()->dimMappings();</div><div class="line"><a name="l02738"></a><span class="lineno"> 2738</span> </div><div class="line"><a name="l02739"></a><span class="lineno"> 2739</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02740"></a><span class="lineno"> 2740</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02741"></a><span class="lineno"> 2741</span> </div><div class="line"><a name="l02742"></a><span class="lineno"> 2742</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02743"></a><span class="lineno"> 2743</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02744"></a><span class="lineno"> 2744</span>  <span class="keyword">auto</span> outputInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02745"></a><span class="lineno"> 2745</span> </div><div class="line"><a name="l02746"></a><span class="lineno"> 2746</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02747"></a><span class="lineno"> 2747</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_transpose_descriptor.xhtml">armnn::TransposeDescriptor</a> descriptor(<a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a>(dimsMapping->data(), dimsMapping->Length()));</div><div class="line"><a name="l02748"></a><span class="lineno"> 2748</span> </div><div class="line"><a name="l02749"></a><span class="lineno"> 2749</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddTransposeLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02750"></a><span class="lineno"> 2750</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l02751"></a><span class="lineno"> 2751</span> </div><div class="line"><a name="l02752"></a><span class="lineno"> 2752</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02753"></a><span class="lineno"> 2753</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02754"></a><span class="lineno"> 2754</span> }</div><div class="line"><a name="l02755"></a><span class="lineno"> 2755</span> </div><div class="line"><a name="l02756"></a><span class="lineno"> 2756</span> <span class="keywordtype">void</span> Deserializer::ParseTransposeConvolution2d(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02757"></a><span class="lineno"> 2757</span> {</div><div class="line"><a name="l02758"></a><span class="lineno"> 2758</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02759"></a><span class="lineno"> 2759</span> </div><div class="line"><a name="l02760"></a><span class="lineno"> 2760</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02761"></a><span class="lineno"> 2761</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), 1);</div><div class="line"><a name="l02762"></a><span class="lineno"> 2762</span> </div><div class="line"><a name="l02763"></a><span class="lineno"> 2763</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02764"></a><span class="lineno"> 2764</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02765"></a><span class="lineno"> 2765</span> </div><div class="line"><a name="l02766"></a><span class="lineno"> 2766</span>  <span class="keyword">auto</span> serializerLayer = graph->layers()->Get(layerIndex)->layer_as_TransposeConvolution2dLayer();</div><div class="line"><a name="l02767"></a><span class="lineno"> 2767</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02768"></a><span class="lineno"> 2768</span>  <span class="keyword">auto</span> serializerDescriptor = serializerLayer->descriptor();</div><div class="line"><a name="l02769"></a><span class="lineno"> 2769</span> </div><div class="line"><a name="l02770"></a><span class="lineno"> 2770</span>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">armnn::TransposeConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l02771"></a><span class="lineno"> 2771</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = serializerDescriptor->padLeft();</div><div class="line"><a name="l02772"></a><span class="lineno"> 2772</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = serializerDescriptor->padRight();</div><div class="line"><a name="l02773"></a><span class="lineno"> 2773</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = serializerDescriptor->padTop();</div><div class="line"><a name="l02774"></a><span class="lineno"> 2774</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = serializerDescriptor->padBottom();</div><div class="line"><a name="l02775"></a><span class="lineno"> 2775</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = serializerDescriptor->strideX();</div><div class="line"><a name="l02776"></a><span class="lineno"> 2776</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = serializerDescriptor->strideY();;</div><div class="line"><a name="l02777"></a><span class="lineno"> 2777</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = serializerDescriptor->biasEnabled();;</div><div class="line"><a name="l02778"></a><span class="lineno"> 2778</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">ToDataLayout</a>(serializerDescriptor->dataLayout());</div><div class="line"><a name="l02779"></a><span class="lineno"> 2779</span> </div><div class="line"><a name="l02780"></a><span class="lineno"> 2780</span>  <span class="comment">// weights & biases</span></div><div class="line"><a name="l02781"></a><span class="lineno"> 2781</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerLayer->weights());</div><div class="line"><a name="l02782"></a><span class="lineno"> 2782</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<armnn::ConstTensor></a> optionalBiases;</div><div class="line"><a name="l02783"></a><span class="lineno"> 2783</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div><div class="line"><a name="l02784"></a><span class="lineno"> 2784</span>  {</div><div class="line"><a name="l02785"></a><span class="lineno"> 2785</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> biases = <a class="code" href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">ToConstTensor</a>(serializerLayer->biases());</div><div class="line"><a name="l02786"></a><span class="lineno"> 2786</span>  optionalBiases = armnn::MakeOptional<armnn::ConstTensor>(biases);</div><div class="line"><a name="l02787"></a><span class="lineno"> 2787</span>  }</div><div class="line"><a name="l02788"></a><span class="lineno"> 2788</span> </div><div class="line"><a name="l02789"></a><span class="lineno"> 2789</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddTransposeConvolution2dLayer(descriptor,</div><div class="line"><a name="l02790"></a><span class="lineno"> 2790</span>  weights,</div><div class="line"><a name="l02791"></a><span class="lineno"> 2791</span>  optionalBiases,</div><div class="line"><a name="l02792"></a><span class="lineno"> 2792</span>  layerName.c_str());</div><div class="line"><a name="l02793"></a><span class="lineno"> 2793</span> </div><div class="line"><a name="l02794"></a><span class="lineno"> 2794</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02795"></a><span class="lineno"> 2795</span>  layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);</div><div class="line"><a name="l02796"></a><span class="lineno"> 2796</span> </div><div class="line"><a name="l02797"></a><span class="lineno"> 2797</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02798"></a><span class="lineno"> 2798</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02799"></a><span class="lineno"> 2799</span> }</div><div class="line"><a name="l02800"></a><span class="lineno"> 2800</span> </div><div class="line"><a name="l02801"></a><span class="lineno"> 2801</span> <span class="keywordtype">void</span> Deserializer::ParseStack(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02802"></a><span class="lineno"> 2802</span> {</div><div class="line"><a name="l02803"></a><span class="lineno"> 2803</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02804"></a><span class="lineno"> 2804</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02805"></a><span class="lineno"> 2805</span> </div><div class="line"><a name="l02806"></a><span class="lineno"> 2806</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02807"></a><span class="lineno"> 2807</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), 1);</div><div class="line"><a name="l02808"></a><span class="lineno"> 2808</span> </div><div class="line"><a name="l02809"></a><span class="lineno"> 2809</span>  <span class="keyword">auto</span> flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_StackLayer()->descriptor();</div><div class="line"><a name="l02810"></a><span class="lineno"> 2810</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axis = flatBufferDescriptor->axis();</div><div class="line"><a name="l02811"></a><span class="lineno"> 2811</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = flatBufferDescriptor->numInputs();</div><div class="line"><a name="l02812"></a><span class="lineno"> 2812</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), numInputs);</div><div class="line"><a name="l02813"></a><span class="lineno"> 2813</span> </div><div class="line"><a name="l02814"></a><span class="lineno"> 2814</span>  <span class="keyword">auto</span> flatBufferInputShape = flatBufferDescriptor->inputShape();</div><div class="line"><a name="l02815"></a><span class="lineno"> 2815</span>  std::vector<uint32_t> vectorInputShape(flatBufferInputShape->begin(),</div><div class="line"><a name="l02816"></a><span class="lineno"> 2816</span>  flatBufferInputShape->begin() + flatBufferInputShape->size());</div><div class="line"><a name="l02817"></a><span class="lineno"> 2817</span> </div><div class="line"><a name="l02818"></a><span class="lineno"> 2818</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape(static_cast<unsigned int>(vectorInputShape.size()), vectorInputShape.data());</div><div class="line"><a name="l02819"></a><span class="lineno"> 2819</span>  <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a> descriptor(axis, numInputs, inputShape);</div><div class="line"><a name="l02820"></a><span class="lineno"> 2820</span> </div><div class="line"><a name="l02821"></a><span class="lineno"> 2821</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<inputs.size(); ++i)</div><div class="line"><a name="l02822"></a><span class="lineno"> 2822</span>  {</div><div class="line"><a name="l02823"></a><span class="lineno"> 2823</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputShape = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(inputs[i]).<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div><div class="line"><a name="l02824"></a><span class="lineno"> 2824</span>  <span class="keywordflow">if</span> (descriptor.m_InputShape != inputShape)</div><div class="line"><a name="l02825"></a><span class="lineno"> 2825</span>  {</div><div class="line"><a name="l02826"></a><span class="lineno"> 2826</span>  std::stringstream ss;</div><div class="line"><a name="l02827"></a><span class="lineno"> 2827</span>  ss << <span class="stringliteral">"Shape of input "</span></div><div class="line"><a name="l02828"></a><span class="lineno"> 2828</span>  << i</div><div class="line"><a name="l02829"></a><span class="lineno"> 2829</span>  << <span class="stringliteral">" "</span></div><div class="line"><a name="l02830"></a><span class="lineno"> 2830</span>  << inputShape</div><div class="line"><a name="l02831"></a><span class="lineno"> 2831</span>  << <span class="stringliteral">" does not equal defined input shape "</span></div><div class="line"><a name="l02832"></a><span class="lineno"> 2832</span>  << descriptor.m_InputShape</div><div class="line"><a name="l02833"></a><span class="lineno"> 2833</span>  << <span class="stringliteral">": "</span></div><div class="line"><a name="l02834"></a><span class="lineno"> 2834</span>  << <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>().AsString();</div><div class="line"><a name="l02835"></a><span class="lineno"> 2835</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_parse_exception.xhtml">ParseException</a>(ss.str());</div><div class="line"><a name="l02836"></a><span class="lineno"> 2836</span>  }</div><div class="line"><a name="l02837"></a><span class="lineno"> 2837</span>  }</div><div class="line"><a name="l02838"></a><span class="lineno"> 2838</span> </div><div class="line"><a name="l02839"></a><span class="lineno"> 2839</span>  <span class="keyword">auto</span> layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02840"></a><span class="lineno"> 2840</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* layer = m_Network->AddStackLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02841"></a><span class="lineno"> 2841</span> </div><div class="line"><a name="l02842"></a><span class="lineno"> 2842</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l02843"></a><span class="lineno"> 2843</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02844"></a><span class="lineno"> 2844</span> </div><div class="line"><a name="l02845"></a><span class="lineno"> 2845</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02846"></a><span class="lineno"> 2846</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02847"></a><span class="lineno"> 2847</span> }</div><div class="line"><a name="l02848"></a><span class="lineno"> 2848</span> </div><div class="line"><a name="l02849"></a><span class="lineno"> 2849</span> <span class="keywordtype">void</span> Deserializer::ParseStandIn(<a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">GraphPtr</a> graph, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> layerIndex)</div><div class="line"><a name="l02850"></a><span class="lineno"> 2850</span> {</div><div class="line"><a name="l02851"></a><span class="lineno"> 2851</span>  <a class="code" href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a>(graph, 0, layerIndex);</div><div class="line"><a name="l02852"></a><span class="lineno"> 2852</span> </div><div class="line"><a name="l02853"></a><span class="lineno"> 2853</span>  <span class="keyword">auto</span> inputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">GetInputs</a>(graph, layerIndex);</div><div class="line"><a name="l02854"></a><span class="lineno"> 2854</span>  <span class="keyword">auto</span> outputs = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">GetOutputs</a>(graph, layerIndex);</div><div class="line"><a name="l02855"></a><span class="lineno"> 2855</span> </div><div class="line"><a name="l02856"></a><span class="lineno"> 2856</span>  <span class="keyword">auto</span> fbLayer = graph->layers()->Get(layerIndex)->layer_as_StandInLayer();</div><div class="line"><a name="l02857"></a><span class="lineno"> 2857</span>  <span class="keyword">auto</span> fbDescriptor = fbLayer->descriptor();</div><div class="line"><a name="l02858"></a><span class="lineno"> 2858</span> </div><div class="line"><a name="l02859"></a><span class="lineno"> 2859</span>  <a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml">armnn::StandInDescriptor</a> descriptor;</div><div class="line"><a name="l02860"></a><span class="lineno"> 2860</span>  descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">m_NumInputs</a> = fbDescriptor->numInputs();</div><div class="line"><a name="l02861"></a><span class="lineno"> 2861</span>  descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml#abb8a2d2bb8cc594c26aaa70c820ac5cc">m_NumOutputs</a> = fbDescriptor->numOutputs();</div><div class="line"><a name="l02862"></a><span class="lineno"> 2862</span> </div><div class="line"><a name="l02863"></a><span class="lineno"> 2863</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(inputs.size(), descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">m_NumInputs</a>);</div><div class="line"><a name="l02864"></a><span class="lineno"> 2864</span>  <a class="code" href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a>(outputs.size(), descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml#abb8a2d2bb8cc594c26aaa70c820ac5cc">m_NumOutputs</a>);</div><div class="line"><a name="l02865"></a><span class="lineno"> 2865</span> </div><div class="line"><a name="l02866"></a><span class="lineno"> 2866</span>  <span class="keyword">const</span> std::string layerName = <a class="code" href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">GetLayerName</a>(graph, layerIndex);</div><div class="line"><a name="l02867"></a><span class="lineno"> 2867</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer = m_Network->AddStandInLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02868"></a><span class="lineno"> 2868</span> </div><div class="line"><a name="l02869"></a><span class="lineno"> 2869</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < descriptor.<a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml#abb8a2d2bb8cc594c26aaa70c820ac5cc">m_NumOutputs</a>; ++i)</div><div class="line"><a name="l02870"></a><span class="lineno"> 2870</span>  {</div><div class="line"><a name="l02871"></a><span class="lineno"> 2871</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">ToTensorInfo</a>(outputs[i]);</div><div class="line"><a name="l02872"></a><span class="lineno"> 2872</span>  layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(i).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l02873"></a><span class="lineno"> 2873</span>  }</div><div class="line"><a name="l02874"></a><span class="lineno"> 2874</span> </div><div class="line"><a name="l02875"></a><span class="lineno"> 2875</span>  RegisterInputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02876"></a><span class="lineno"> 2876</span>  RegisterOutputSlots(graph, layerIndex, layer);</div><div class="line"><a name="l02877"></a><span class="lineno"> 2877</span> }</div><div class="line"><a name="l02878"></a><span class="lineno"> 2878</span> </div><div class="line"><a name="l02879"></a><span class="lineno"> 2879</span> } <span class="comment">// namespace armnnDeserializer</span></div><div class="ttc" id="namespacearmnn_deserializer_xhtml_a4acbc36201effcfd40e3a4d45d742b24"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#a4acbc36201effcfd40e3a4d45d742b24">armnnDeserializer::ToConstTensor</a></div><div class="ttdeci">armnn::ConstTensor ToConstTensor(Deserializer::ConstTensorRawPtr constTensorPtr)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00558">Deserializer.cpp:558</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_af7bb02c61c6a5663121da024b7e042e8"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#af7bb02c61c6a5663121da024b7e042e8">armnnDeserializer::Deserializer::GetLstmDescriptor</a></div><div class="ttdeci">static armnn::LstmDescriptor GetLstmDescriptor(LstmDescriptorPtr lstmDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l02465">Deserializer.cpp:2465</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::Convolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00428">Descriptors.hpp:428</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00438">Descriptors.hpp:438</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559">armnn::ActivationFunction::ReLu</a></div></div> +<div class="ttc" id="_ignore_unused_8hpp_xhtml"><div class="ttname"><a href="_ignore_unused_8hpp.xhtml">IgnoreUnused.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_l2_normalization_descriptor_xhtml_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">armnn::L2NormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Used to avoid dividing by zero. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00604">Descriptors.hpp:604</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a"><div class="ttname"><a href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a">armnn::ComparisonOperation::Greater</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_ac2dac3b61c94de52093616be4ab17f8d"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#ac2dac3b61c94de52093616be4ab17f8d">armnn::IConnectableLayer::GetNumOutputSlots</a></div><div class="ttdeci">virtual unsigned int GetNumOutputSlots() const =0</div><div class="ttdoc">Returns the number of connectable output slots. </div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00871">Descriptors.hpp:871</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00440">Descriptors.hpp:440</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_ab03e6e1514f74427916c892f473fe04c"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#ab03e6e1514f74427916c892f473fe04c">armnn::LstmInputParams::m_ProjectionWeights</a></div><div class="ttdeci">const ConstTensor * m_ProjectionWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00055">LstmParams.hpp:55</a></div></div> +<div class="ttc" id="structarmnn_1_1_elementwise_unary_descriptor_xhtml_afe768be66897eb3d73284424e3239b23"><div class="ttname"><a href="structarmnn_1_1_elementwise_unary_descriptor.xhtml#afe768be66897eb3d73284424e3239b23">armnn::ElementwiseUnaryDescriptor::m_Operation</a></div><div class="ttdeci">UnaryOperation m_Operation</div><div class="ttdoc">Specifies the elementwiseUnary operation to execute. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00098">Descriptors.hpp:98</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a49e11acda22742cbaf6f1b259ead0d84"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">armnn::QuantizedLstmInputParams::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00035">QuantizedLstmParams.hpp:35</a></div></div> +<div class="ttc" id="structarmnn_1_1_views_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_views_descriptor.xhtml">armnn::ViewsDescriptor</a></div><div class="ttdoc">A ViewsDescriptor for the SplitterLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00190">Descriptors.hpp:190</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00061">INetwork.hpp:61</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ab509802c659de19929f18bad14a35c58"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ab509802c659de19929f18bad14a35c58">armnn::DetectionPostProcessDescriptor::m_ScaleW</a></div><div class="ttdeci">float m_ScaleW</div><div class="ttdoc">Center size encoding scale weight. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00545">Descriptors.hpp:545</a></div></div> +<div class="ttc" id="_deserializer_8cpp_xhtml_aa6798881c467e8e1a1906303f6d9e26d"><div class="ttname"><a href="_deserializer_8cpp.xhtml#aa6798881c467e8e1a1906303f6d9e26d">CHECK_LAYERS</a></div><div class="ttdeci">#define CHECK_LAYERS(GRAPH, LAYERS_INDEX, LAYER_INDEX)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00160">Deserializer.cpp:160</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a4a9d678146f572808a361dbdc5489f38"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">armnn::LstmInputParams::m_CellBias</a></div><div class="ttdeci">const ConstTensor * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00053">LstmParams.hpp:53</a></div></div> +<div class="ttc" id="_transpose_8hpp_xhtml"><div class="ttname"><a href="_transpose_8hpp.xhtml">Transpose.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::Pooling2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00355">Descriptors.hpp:355</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00490">Descriptors.hpp:490</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a0ba4effa5ee7ef715b1f452365c41f97"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a0ba4effa5ee7ef715b1f452365c41f97">armnnDeserializer::Deserializer::LoadGraphFromBinary</a></div><div class="ttdeci">static GraphPtr LoadGraphFromBinary(const uint8_t *binaryContent, size_t len)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00686">Deserializer.cpp:686</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a9c2cba04b6d7ace4fc2a2436b82a5a63"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a9c2cba04b6d7ace4fc2a2436b82a5a63">armnn::IConnectableLayer::GetNumInputSlots</a></div><div class="ttdeci">virtual unsigned int GetNumInputSlots() const =0</div><div class="ttdoc">Returns the number of connectable input slots. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00049">Types.hpp:49</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml_a8526ea7cf860d8e7f8340e9f9354f9f0"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml#a8526ea7cf860d8e7f8340e9f9354f9f0">armnn::NormalizationDescriptor::m_K</a></div><div class="ttdeci">float m_K</div><div class="ttdoc">Kappa value used for the across channel normalization equation. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00585">Descriptors.hpp:585</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01079">Descriptors.hpp:1079</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a4a9d678146f572808a361dbdc5489f38"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">armnn::QuantizedLstmInputParams::m_CellBias</a></div><div class="ttdeci">const ConstTensor * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00045">QuantizedLstmParams.hpp:45</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00088">Tensor.hpp:88</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a56b81ca8ba4b4937e0787e4951f043fc"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">armnn::QuantizedLstmInputParams::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00041">QuantizedLstmParams.hpp:41</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::DepthwiseConvolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00480">Descriptors.hpp:480</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb"><div class="ttname"><a href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754ea3237fbc8204064c106cb9080088a17cb">armnn::OutputShapeRounding::Ceiling</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Pooling2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00349">Descriptors.hpp:349</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a86e88bef0df4df96df752b4b8955a3af"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">armnn::LstmDescriptor::m_ClippingThresProj</a></div><div class="ttdeci">float m_ClippingThresProj</div><div class="ttdoc">Clipping threshold value for the projection. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00865">Descriptors.hpp:865</a></div></div> +<div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional< armnn::ConstTensor ></a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5"><div class="ttname"><a href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">armnn::ComparisonOperation::Equal</a></div></div> +<div class="ttc" id="structarmnn_1_1_check_location_xhtml_a5e3562cda960da001597e7dd5679b140"><div class="ttname"><a href="structarmnn_1_1_check_location.xhtml#a5e3562cda960da001597e7dd5679b140">armnn::CheckLocation::AsString</a></div><div class="ttdeci">std::string AsString() const</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00029">Exceptions.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a920251d49a8f32085d458ba23f776800"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a920251d49a8f32085d458ba23f776800">armnnDeserializer::Deserializer::GetNormalizationDescriptor</a></div><div class="ttdeci">static armnn::NormalizationDescriptor GetNormalizationDescriptor(NormalizationDescriptorPtr normalizationDescriptor, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l02159">Deserializer.cpp:2159</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3"><div class="ttname"><a href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a></div></div> +<div class="ttc" id="structarmnn_1_1_reshape_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_reshape_descriptor.xhtml">armnn::ReshapeDescriptor</a></div><div class="ttdoc">A ReshapeDescriptor for the ReshapeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00758">Descriptors.hpp:758</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_i_deserializer_xhtml_afe33a6c8701eff4d2f7233ce441e0426"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer.xhtml#afe33a6c8701eff4d2f7233ce441e0426">armnnDeserializer::IDeserializer::Destroy</a></div><div class="ttdeci">static void Destroy(IDeserializer *parser)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00666">Deserializer.cpp:666</a></div></div> +<div class="ttc" id="namespacearmnn_serializer_xhtml"><div class="ttname"><a href="namespacearmnn_serializer.xhtml">armnnSerializer</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_serializer_8hpp_source.xhtml#l00011">ISerializer.hpp:11</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_afe204ca375b74e9a72640c9227918d0a"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#afe204ca375b74e9a72640c9227918d0a">armnn::LstmInputParams::m_CellToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_CellToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00050">LstmParams.hpp:50</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_ae83131e16df1cace69395a5f99bc5ecb"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">armnn::QuantizedLstmInputParams::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00039">QuantizedLstmParams.hpp:39</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00492">Descriptors.hpp:492</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#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="structarmnn_1_1_comparison_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_comparison_descriptor.xhtml">armnn::ComparisonDescriptor</a></div><div class="ttdoc">A ComparisonDescriptor for the ComparisonLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00062">Descriptors.hpp:62</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae64523937ea910030ad66fee6fddd51f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae64523937ea910030ad66fee6fddd51f">armnn::DetectionPostProcessDescriptor::m_ScaleX</a></div><div class="ttdeci">float m_ScaleX</div><div class="ttdoc">Center size encoding scale x. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00541">Descriptors.hpp:541</a></div></div> +<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml_a281fcaec86e17c97f7b8402633f6b55a"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml#a281fcaec86e17c97f7b8402633f6b55a">armnn::FullyConnectedDescriptor::m_TransposeWeightMatrix</a></div><div class="ttdeci">bool m_TransposeWeightMatrix</div><div class="ttdoc">Enable/disable transpose weight matrix. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00388">Descriptors.hpp:388</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">armnn::Pooling2dDescriptor::m_PoolWidth</a></div><div class="ttdeci">uint32_t m_PoolWidth</div><div class="ttdoc">Pooling width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00357">Descriptors.hpp:357</a></div></div> +<div class="ttc" id="_deserializer_8cpp_xhtml_ae38d96fe05581ea025713b3e781c5a43"><div class="ttname"><a href="_deserializer_8cpp.xhtml#ae38d96fe05581ea025713b3e781c5a43">CHECK_TENSOR_PTR</a></div><div class="ttdeci">#define CHECK_TENSOR_PTR(TENSOR_PTR)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00151">Deserializer.cpp:151</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">armnn::ActivationFunction::Sqrt</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00392">Descriptors.hpp:392</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml_a174279be57d7596eeb04c6b7f7510f99"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml#a174279be57d7596eeb04c6b7f7510f99">armnn::NormalizationDescriptor::m_Alpha</a></div><div class="ttdeci">float m_Alpha</div><div class="ttdoc">Alpha value for the normalization equation. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00581">Descriptors.hpp:581</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a80888061963ddd18e87105807a035d9a"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a80888061963ddd18e87105807a035d9a">armnnDeserializer::Deserializer::TensorRawPtr</a></div><div class="ttdeci">const armnnSerializer::TensorInfo * TensorRawPtr</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.xhtml#l00022">Deserializer.hpp:22</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_ace7a1f1f1041b412b7d8ef82b95ff352"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">armnn::QuantizedLstmInputParams::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensor * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00044">QuantizedLstmParams.hpp:44</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a2d299363c9fc33334c571fa29ca4f58ca1cfdf0e8d0c87a228c1f40d9bee7888b"><div class="ttname"><a href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca1cfdf0e8d0c87a228c1f40d9bee7888b">armnn::ComparisonOperation::Less</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a2a282cf18fcfe848b47e946327ca1048"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a2a282cf18fcfe848b47e946327ca1048">armnnDeserializer::Deserializer::NormalizationDescriptorPtr</a></div><div class="ttdeci">const armnnSerializer::NormalizationDescriptor * NormalizationDescriptorPtr</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.xhtml#l00024">Deserializer.hpp:24</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::DepthwiseConvolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00474">Descriptors.hpp:474</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::TransposeConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01117">Descriptors.hpp:1117</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a484bafa2f8453a7c5a4a00b92a61b006"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a484bafa2f8453a7c5a4a00b92a61b006">armnn::LstmInputParams::m_CellToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_CellToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00048">LstmParams.hpp:48</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaacb7667f5ec2f6e8a5943b781ba6c2735"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaacb7667f5ec2f6e8a5943b781ba6c2735">armnn::ActivationFunction::LeakyReLu</a></div></div> +<div class="ttc" id="_quantized_lstm_params_8hpp_xhtml"><div class="ttname"><a href="_quantized_lstm_params_8hpp.xhtml">QuantizedLstmParams.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a869254cb56968986a78a79e1d6d4a86b"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#a869254cb56968986a78a79e1d6d4a86b">armnn::ResizeDescriptor::m_Method</a></div><div class="ttdeci">ResizeMethod m_Method</div><div class="ttdoc">The Interpolation method to use (Bilinear, NearestNeighbor). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00749">Descriptors.hpp:749</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml_a5e078fd505aef7bccaa05c8058e096cc"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a5e078fd505aef7bccaa05c8058e096cc">armnn::InstanceNormalizationDescriptor::m_Gamma</a></div><div class="ttdeci">float m_Gamma</div><div class="ttdoc">Gamma, the scale scalar value applied for the normalized tensor. Defaults to 1.0. ...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00647">Descriptors.hpp:647</a></div></div> +<div class="ttc" id="structarmnn_1_1_softmax_descriptor_xhtml_a8275d51ef9a584feb95726ea0522f6e5"><div class="ttname"><a href="structarmnn_1_1_softmax_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">armnn::SoftmaxDescriptor::m_Beta</a></div><div class="ttdeci">float m_Beta</div><div class="ttdoc">Exponentiation value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00136">Descriptors.hpp:136</a></div></div> +<div class="ttc" id="structarmnn_1_1_slice_descriptor_xhtml_ab52cabf19232290fa6b49828ba957ac0"><div class="ttname"><a href="structarmnn_1_1_slice_descriptor.xhtml#ab52cabf19232290fa6b49828ba957ac0">armnn::SliceDescriptor::m_Size</a></div><div class="ttdeci">std::vector< unsigned int > m_Size</div><div class="ttdoc">Size of the slice in each dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00946">Descriptors.hpp:946</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6"><div class="ttname"><a href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a></div><div class="ttdoc">The padding fields don&#39;t count and are ignored. </div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_xhtml_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">armnn::BatchNormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Value to add to the variance. Used to avoid dividing by zero. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00623">Descriptors.hpp:623</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a9e081a9b94defb30d1558dc912507e0e"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">armnn::LstmInputParams::m_InputGateBias</a></div><div class="ttdeci">const ConstTensor * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00051">LstmParams.hpp:51</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a8c29d6ea9b4186d69aad5961c910939c"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">armnn::Pooling2dDescriptor::m_PaddingMethod</a></div><div class="ttdeci">PaddingMethod m_PaddingMethod</div><div class="ttdoc">The padding method to be used. (Exclude, IgnoreValue). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00367">Descriptors.hpp:367</a></div></div> +<div class="ttc" id="structarmnn_1_1_arg_min_max_descriptor_xhtml_ab1ae6f520bb1a4da191a0ae907477f23"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml#ab1ae6f520bb1a4da191a0ae907477f23">armnn::ArgMinMaxDescriptor::m_Function</a></div><div class="ttdeci">ArgMinMaxFunction m_Function</div><div class="ttdoc">Specify if the function is to find Min or Max. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00056">Descriptors.hpp:56</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7e2f87544b8bc7e497e1dec8d3ca4055"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7e2f87544b8bc7e497e1dec8d3ca4055">armnn::DetectionPostProcessDescriptor::m_DetectionsPerClass</a></div><div class="ttdeci">uint32_t m_DetectionsPerClass</div><div class="ttdoc">Detections per classes, used in Regular NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00531">Descriptors.hpp:531</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::BatchNormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00625">Descriptors.hpp:625</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::BatchToSpaceNdDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00684">Descriptors.hpp:684</a></div></div> +<div class="ttc" id="_optimization_views_tests_8cpp_xhtml_a6c81e7ec0af6eeda194d2bd8cd40eccf"><div class="ttname"><a href="_optimization_views_tests_8cpp.xhtml#a6c81e7ec0af6eeda194d2bd8cd40eccf">CheckLayers</a></div><div class="ttdeci">void CheckLayers(Graph &graph)</div><div class="ttdef"><b>Definition:</b> <a href="_optimization_views_tests_8cpp_source.xhtml#l00018">OptimizationViewsTests.cpp:18</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a9e081a9b94defb30d1558dc912507e0e"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">armnn::QuantizedLstmInputParams::m_InputGateBias</a></div><div class="ttdeci">const ConstTensor * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00043">QuantizedLstmParams.hpp:43</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">armnn::ActivationFunction::Abs</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_i_deserializer_xhtml_af116abd698a7feb92876ae48917005a4"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer.xhtml#af116abd698a7feb92876ae48917005a4">armnnDeserializer::IDeserializer::Create</a></div><div class="ttdeci">static IDeserializerPtr Create()</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00661">Deserializer.cpp:661</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::Pooling2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00353">Descriptors.hpp:353</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a1759754ccb88ecc9af44f3aae6e244ee"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">armnn::LstmInputParams::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00046">LstmParams.hpp:46</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::Convolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00424">Descriptors.hpp:424</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::NormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00587">Descriptors.hpp:587</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_af0f796fba1a2be9c56b4c9ee534577ee"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#af0f796fba1a2be9c56b4c9ee534577ee">armnn::LstmInputParams::m_ForgetLayerNormWeights</a></div><div class="ttdeci">const ConstTensor * m_ForgetLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00058">LstmParams.hpp:58</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a35b112e30c3eb153806a2a8c16d178e3"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a35b112e30c3eb153806a2a8c16d178e3">armnn::LstmInputParams::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00049">LstmParams.hpp:49</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml">armnn::QuantizedLstmInputParams</a></div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00013">QuantizedLstmParams.hpp:13</a></div></div> +<div class="ttc" id="_lstm_params_8hpp_xhtml"><div class="ttname"><a href="_lstm_params_8hpp.xhtml">LstmParams.hpp</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_ae8ee09f5e3e78ecfdf00acfdc37588dc"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#ae8ee09f5e3e78ecfdf00acfdc37588dc">armnnDeserializer::Deserializer::CreateNetworkFromBinary</a></div><div class="ttdeci">armnn::INetworkPtr CreateNetworkFromBinary(const std::vector< uint8_t > &binaryContent) override</div><div class="ttdoc">Create an input network from binary file contents. </div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00671">Deserializer.cpp:671</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a43e0ec855f3a7ebf9f98fbee5321edcf"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a43e0ec855f3a7ebf9f98fbee5321edcf">armnnDeserializer::Deserializer::Deserializer</a></div><div class="ttdeci">Deserializer()</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00186">Deserializer.cpp:186</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::TransposeConvolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01111">Descriptors.hpp:1111</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a1cfaa710db2a54673b21d2ea2da757c8afb278fa5defd7e699fcbc930c3e76ccd"><div class="ttname"><a href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8afb278fa5defd7e699fcbc930c3e76ccd">armnn::UnaryOperation::Neg</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="_deserializer_8cpp_xhtml_ab90eef134463f7b44cd4c9cfb2529825"><div class="ttname"><a href="_deserializer_8cpp.xhtml#ab90eef134463f7b44cd4c9cfb2529825">CHECK_GRAPH</a></div><div class="ttdeci">#define CHECK_GRAPH(GRAPH, LAYERS_INDEX)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00163">Deserializer.cpp:163</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_af2e5b4595b6abc056779ecd12bd271c2"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#af2e5b4595b6abc056779ecd12bd271c2">armnnDeserializer::Deserializer::GetLayerName</a></div><div class="ttdeci">static std::string GetLayerName(const GraphPtr &graph, unsigned int index)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00372">Deserializer.cpp:372</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::Convolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation along y axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00436">Descriptors.hpp:436</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_depth_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml">armnn::SpaceToDepthDescriptor</a></div><div class="ttdoc">A SpaceToDepthDescriptor for the SpaceToDepthLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00810">Descriptors.hpp:810</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_xhtml_a85f98c94e11f65a6b73f831735c040f3"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a85f98c94e11f65a6b73f831735c040f3">armnn::SpaceToBatchNdDescriptor::m_PadList</a></div><div class="ttdeci">std::vector< std::pair< unsigned int, unsigned int > > m_PadList</div><div class="ttdoc">Specifies the padding values for the input dimension: heightPad{top, bottom} widthPad{left, right}. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00804">Descriptors.hpp:804</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::DepthwiseConvolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation factor value for height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00488">Descriptors.hpp:488</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">armnn::BatchToSpaceNdDescriptor</a></div><div class="ttdoc">A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00657">Descriptors.hpp:657</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::Pooling2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00361">Descriptors.hpp:361</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a66c5e4250559faefd7f0fa35ccbdc9eb"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a66c5e4250559faefd7f0fa35ccbdc9eb">armnnDeserializer::Deserializer::GetNetworkInputBindingInfo</a></div><div class="ttdeci">BindingPointInfo GetNetworkInputBindingInfo(unsigned int layerId, const std::string &name) const override</div><div class="ttdoc">Retrieve binding info (layer id and tensor info) for the network input identified by the given layer ...</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00746">Deserializer.cpp:746</a></div></div> +<div class="ttc" id="structarmnn_deserializer_1_1_binding_point_info_xhtml"><div class="ttname"><a href="structarmnn_deserializer_1_1_binding_point_info.xhtml">armnnDeserializer::BindingPointInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_deserializer_8hpp_source.xhtml#l00018">IDeserializer.hpp:18</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a></div><div class="ttdeci">int LayerBindingId</div><div class="ttdoc">Type of identifiers for bindable layers (inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00171">Types.hpp:171</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a8c0f6d48705f40c5590dde09be262222"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">armnn::LstmInputParams::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensor * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00054">LstmParams.hpp:54</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml_a28f896fb78cdf6607b61c196c98b2570"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#a28f896fb78cdf6607b61c196c98b2570">armnnDeserializer::ToComparisonOperation</a></div><div class="ttdeci">armnn::ComparisonOperation ToComparisonOperation(armnnSerializer::ComparisonOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00449">Deserializer.cpp:449</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</div></div> +<div class="ttc" id="structarmnn_1_1_stand_in_descriptor_xhtml_abb8a2d2bb8cc594c26aaa70c820ac5cc"><div class="ttname"><a href="structarmnn_1_1_stand_in_descriptor.xhtml#abb8a2d2bb8cc594c26aaa70c820ac5cc">armnn::StandInDescriptor::m_NumOutputs</a></div><div class="ttdeci">uint32_t m_NumOutputs</div><div class="ttdoc">Number of output tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00998">Descriptors.hpp:998</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml_a05945f080edf694b631960728b87aadb"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml#a05945f080edf694b631960728b87aadb">armnn::NormalizationDescriptor::m_NormMethodType</a></div><div class="ttdeci">NormalizationAlgorithmMethod m_NormMethodType</div><div class="ttdoc">Normalization method algorithm to use (LocalBrightness, LocalContrast). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00577">Descriptors.hpp:577</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_abe8889e8150beef5fd204b2d87b49298"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">armnn::TensorInfo::SetShape</a></div><div class="ttdeci">void SetShape(const TensorShape &newShape)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00090">Tensor.hpp:90</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml">armnn::ResizeDescriptor</a></div><div class="ttdoc">A ResizeDescriptor for the ResizeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00724">Descriptors.hpp:724</a></div></div> +<div class="ttc" id="structarmnn_1_1_l2_normalization_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::L2NormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00606">Descriptors.hpp:606</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a9ae2c9796692ebeafe19a4d3f09c8ea8"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a9ae2c9796692ebeafe19a4d3f09c8ea8">armnn::DetectionPostProcessDescriptor::m_MaxClassesPerDetection</a></div><div class="ttdeci">uint32_t m_MaxClassesPerDetection</div><div class="ttdoc">Maximum numbers of classes per detection, used in Fast NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00529">Descriptors.hpp:529</a></div></div> +<div class="ttc" id="structarmnn_1_1_mean_descriptor_xhtml_a1f0d67b087c491248bd1cde3ff995a95"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">armnn::MeanDescriptor::m_Axis</a></div><div class="ttdeci">std::vector< unsigned int > m_Axis</div><div class="ttdoc">Values for the dimensions to reduce. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00895">Descriptors.hpp:895</a></div></div> +<div class="ttc" id="structarmnn_1_1_stack_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a></div><div class="ttdoc">A StackDescriptor for the StackLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00950">Descriptors.hpp:950</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::SpaceToBatchNdDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00806">Descriptors.hpp:806</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_affcee5f4ab5994a21bee3b78b4e43de3"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">armnn::QuantizedLstmInputParams::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00033">QuantizedLstmParams.hpp:33</a></div></div> +<div class="ttc" id="structarmnn_1_1_reshape_descriptor_xhtml_a1178f4dafdda81f59c15145ec327f7d9"><div class="ttname"><a href="structarmnn_1_1_reshape_descriptor.xhtml#a1178f4dafdda81f59c15145ec327f7d9">armnn::ReshapeDescriptor::m_TargetShape</a></div><div class="ttdeci">TensorShape m_TargetShape</div><div class="ttdoc">Target shape value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00774">Descriptors.hpp:774</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">armnn::Pooling2dDescriptor::m_PoolHeight</a></div><div class="ttdeci">uint32_t m_PoolHeight</div><div class="ttdoc">Pooling height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00359">Descriptors.hpp:359</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::Convolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00426">Descriptors.hpp:426</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae72089bcab60ac175557f4241b16a014"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">armnn::DetectionPostProcessDescriptor::m_MaxDetections</a></div><div class="ttdeci">uint32_t m_MaxDetections</div><div class="ttdoc">Maximum numbers of detections. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00527">Descriptors.hpp:527</a></div></div> +<div class="ttc" id="structarmnn_1_1_pad_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pad_descriptor.xhtml">armnn::PadDescriptor</a></div><div class="ttdoc">A PadDescriptor for the PadLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00901">Descriptors.hpp:901</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_afcc87bf0e20779861dd5d01a4bedcda9"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#afcc87bf0e20779861dd5d01a4bedcda9">armnnDeserializer::Deserializer::GetBindingLayerInfo</a></div><div class="ttdeci">static int32_t GetBindingLayerInfo(const GraphPtr &graphPtr, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00379">Deserializer.cpp:379</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a0dc66e036f16781886a1ce530e11c2d8"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a0dc66e036f16781886a1ce530e11c2d8">armnnDeserializer::Deserializer::PoolingDescriptor</a></div><div class="ttdeci">const armnnSerializer::Pooling2dDescriptor * PoolingDescriptor</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.xhtml#l00023">Deserializer.hpp:23</a></div></div> +<div class="ttc" id="_deserializer_8cpp_xhtml_aa6fd9c6c98bdd08620d75cac3a2e17e6"><div class="ttname"><a href="_deserializer_8cpp.xhtml#aa6fd9c6c98bdd08620d75cac3a2e17e6">CHECK_CONST_TENSOR_SIZE</a></div><div class="ttdeci">#define CHECK_CONST_TENSOR_SIZE(CONST_TENSOR_SIZE, TENSOR_SIZE)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00154">Deserializer.cpp:154</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml_aa28868b7dc87dc4d957db6c775a591c1"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#aa28868b7dc87dc4d957db6c775a591c1">armnnDeserializer::ToTensorInfo</a></div><div class="ttdeci">armnn::TensorInfo ToTensorInfo(Deserializer::TensorRawPtr tensorPtr)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00501">Deserializer.cpp:501</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00430">Descriptors.hpp:430</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a0cd848f65ec31778d708852f0042fe37"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a0cd848f65ec31778d708852f0042fe37">armnn::LstmInputParams::m_InputLayerNormWeights</a></div><div class="ttdeci">const ConstTensor * m_InputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00057">LstmParams.hpp:57</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a2d299363c9fc33334c571fa29ca4f58c"><div class="ttname"><a href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58c">armnn::ComparisonOperation</a></div><div class="ttdeci">ComparisonOperation</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00077">Types.hpp:77</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="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::DepthwiseConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00482">Descriptors.hpp:482</a></div></div> +<div class="ttc" id="_verification_helpers_8hpp_xhtml"><div class="ttname"><a href="_verification_helpers_8hpp.xhtml">VerificationHelpers.hpp</a></div></div> +<div class="ttc" id="_permute_8hpp_xhtml"><div class="ttname"><a href="_permute_8hpp.xhtml">Permute.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml_aede2265569640ae0af1c5520c8a66829"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#aede2265569640ae0af1c5520c8a66829">armnnDeserializer::ToDataLayout</a></div><div class="ttdeci">armnn::DataLayout ToDataLayout(armnnSerializer::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00394">Deserializer.cpp:394</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml_a97b50f22cd99f0e09e6e48d20a35f6b2"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#a97b50f22cd99f0e09e6e48d20a35f6b2">armnnDeserializer::CheckShape</a></div><div class="ttdeci">bool CheckShape(const armnn::TensorShape &actual, const std::vector< uint32_t > &expected)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00167">Deserializer.cpp:167</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="structarmnn_1_1_detection_post_process_descriptor_xhtml_a53c8a7f33a40e1e240256bcfcf41b101"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a53c8a7f33a40e1e240256bcfcf41b101">armnn::DetectionPostProcessDescriptor::m_NmsIouThreshold</a></div><div class="ttdeci">float m_NmsIouThreshold</div><div class="ttdoc">Intersection over union threshold. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00535">Descriptors.hpp:535</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a56b81ca8ba4b4937e0787e4951f043fc"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">armnn::LstmInputParams::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00047">LstmParams.hpp:47</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml">armnn::LstmDescriptor</a></div><div class="ttdoc">An LstmDescriptor for the LstmLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00837">Descriptors.hpp:837</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::Pooling2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00351">Descriptors.hpp:351</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::DepthwiseConvolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation factor value for width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00486">Descriptors.hpp:486</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::DepthwiseConvolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00478">Descriptors.hpp:478</a></div></div> +<div class="ttc" id="structarmnn_1_1_check_location_xhtml_ac1184445a1323e07e0da084a54aec535"><div class="ttname"><a href="structarmnn_1_1_check_location.xhtml#ac1184445a1323e07e0da084a54aec535">armnn::CheckLocation::FileLine</a></div><div class="ttdeci">std::string FileLine() const</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00037">Exceptions.hpp:37</a></div></div> +<div class="ttc" id="structarmnn_1_1_views_descriptor_xhtml_aae0893695f5803a3517985c7cb1ccb2e"><div class="ttname"><a href="structarmnn_1_1_views_descriptor.xhtml#aae0893695f5803a3517985c7cb1ccb2e">armnn::ViewsDescriptor::SetViewSize</a></div><div class="ttdeci">Status SetViewSize(uint32_t view, uint32_t coord, uint32_t value)</div><div class="ttdoc">Set the size of the views. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.xhtml#l00307">Descriptors.cpp:307</a></div></div> +<div class="ttc" id="structarmnn_1_1_slice_descriptor_xhtml_a4939f00778f08d6c6fec6f74c0a59b7e"><div class="ttname"><a href="structarmnn_1_1_slice_descriptor.xhtml#a4939f00778f08d6c6fec6f74c0a59b7e">armnn::SliceDescriptor::m_Begin</a></div><div class="ttdeci">std::vector< unsigned int > m_Begin</div><div class="ttdoc">Beginning indices of the slice in each dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00943">Descriptors.hpp:943</a></div></div> +<div class="ttc" id="structarmnn_1_1_mean_descriptor_xhtml_a28e0548abfc4e79c48f29a3d11a062e9"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml#a28e0548abfc4e79c48f29a3d11a062e9">armnn::MeanDescriptor::m_KeepDims</a></div><div class="ttdeci">bool m_KeepDims</div><div class="ttdoc">Enable/disable keep dimensions. If true, then the reduced dimensions that are of length 1 are kept...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00897">Descriptors.hpp:897</a></div></div> +<div class="ttc" id="_parser_flatbuffers_serialize_fixture_8hpp_xhtml_a15c20a0693cd3fc4d85565e2f920d8ef"><div class="ttname"><a href="_parser_flatbuffers_serialize_fixture_8hpp.xhtml#a15c20a0693cd3fc4d85565e2f920d8ef">TensorRawPtr</a></div><div class="ttdeci">armnnSerializer::TensorInfo * TensorRawPtr</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_serialize_fixture_8hpp_source.xhtml#l00025">ParserFlatbuffersSerializeFixture.hpp:25</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a02e143524aefddd40b485fcf7dea6696"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">armnn::BatchToSpaceNdDescriptor::m_BlockShape</a></div><div class="ttdeci">std::vector< unsigned int > m_BlockShape</div><div class="ttdoc">Block shape values. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00680">Descriptors.hpp:680</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::ArgMinMaxFunction::Max</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">armnn::InstanceNormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Epsilon, small scalar value added to variance to avoid dividing by zero. Defaults to 1e-12f...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00651">Descriptors.hpp:651</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml">armnn::IOutputSlot</a></div><div class="ttdoc">An output connection slot for a layer. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00037">INetwork.hpp:37</a></div></div> +<div class="ttc" id="structarmnn_1_1_l2_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.xhtml">armnn::L2NormalizationDescriptor</a></div><div class="ttdoc">A L2NormalizationDescriptor for the L2NormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00591">Descriptors.hpp:591</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a44b0e6b16708df7f0d2bbab141688aaa"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a44b0e6b16708df7f0d2bbab141688aaa">armnn::LstmInputParams::m_ProjectionBias</a></div><div class="ttdeci">const ConstTensor * m_ProjectionBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00056">LstmParams.hpp:56</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a31da1ead6794dd64571afdd0b6efc771"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">armnn::QuantizedLstmInputParams::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00034">QuantizedLstmParams.hpp:34</a></div></div> +<div class="ttc" id="structarmnn_1_1_arg_min_max_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a></div><div class="ttdoc">An ArgMinMaxDescriptor for ArgMinMaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00043">Descriptors.hpp:43</a></div></div> +<div class="ttc" id="structarmnn_1_1_origins_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_origins_descriptor.xhtml">armnn::OriginsDescriptor</a></div><div class="ttdoc">An OriginsDescriptor for the ConcatLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00147">Descriptors.hpp:147</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a6f332fc8fc6cf6488f8d8e374a4264fc"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a6f332fc8fc6cf6488f8d8e374a4264fc">armnnDeserializer::Deserializer::GetBaseLayer</a></div><div class="ttdeci">static LayerBaseRawPtr GetBaseLayer(const GraphPtr &graphPtr, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00248">Deserializer.cpp:248</a></div></div> +<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml">armnn::FullyConnectedDescriptor</a></div><div class="ttdoc">A FullyConnectedDescriptor for the FullyConnectedLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00373">Descriptors.hpp:373</a></div></div> +<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::FullyConnectedDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00386">Descriptors.hpp:386</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00199">Tensor.hpp:199</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml">armnn::LstmInputParams</a></div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00013">LstmParams.hpp:13</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a8c0f6d48705f40c5590dde09be262222"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">armnn::QuantizedLstmInputParams::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensor * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00046">QuantizedLstmParams.hpp:46</a></div></div> +<div class="ttc" id="structarmnn_1_1_check_location_xhtml"><div class="ttname"><a href="structarmnn_1_1_check_location.xhtml">armnn::CheckLocation</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00014">Exceptions.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_adcf5037208faac36c0788239a073f75c"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">armnn::ResizeDescriptor::m_TargetWidth</a></div><div class="ttdeci">uint32_t m_TargetWidth</div><div class="ttdoc">Target width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00744">Descriptors.hpp:744</a></div></div> +<div class="ttc" id="_verification_helpers_8hpp_xhtml_a479b2821a7a2cbb8fa8eb7f60a47065d"><div class="ttname"><a href="_verification_helpers_8hpp.xhtml#a479b2821a7a2cbb8fa8eb7f60a47065d">CHECK_VALID_SIZE</a></div><div class="ttdeci">#define CHECK_VALID_SIZE(ACTUAL,...)</div><div class="ttdef"><b>Definition:</b> <a href="_verification_helpers_8hpp_source.xhtml#l00032">VerificationHelpers.hpp:32</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00869">Descriptors.hpp:869</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a3a04b0ccee4bb2f21721ee5045e83df4"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a3a04b0ccee4bb2f21721ee5045e83df4">armnn::DetectionPostProcessDescriptor::m_NumClasses</a></div><div class="ttdeci">uint32_t m_NumClasses</div><div class="ttdoc">Number of classes. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00537">Descriptors.hpp:537</a></div></div> +<div class="ttc" id="_verification_helpers_8hpp_xhtml_aaef93dc9a69f51b59f3cdd0ff0165927"><div class="ttname"><a href="_verification_helpers_8hpp.xhtml#aaef93dc9a69f51b59f3cdd0ff0165927">CHECKED_NON_NEGATIVE</a></div><div class="ttdeci">#define CHECKED_NON_NEGATIVE(VALUE)</div><div class="ttdef"><b>Definition:</b> <a href="_verification_helpers_8hpp_source.xhtml#l00035">VerificationHelpers.hpp:35</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a2d299363c9fc33334c571fa29ca4f58ca19bb0af2c3c530538cb41aff7f235b96"><div class="ttname"><a href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca19bb0af2c3c530538cb41aff7f235b96">armnn::ComparisonOperation::NotEqual</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml_ad33c6040680106b9af566d7269d8c949"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#ad33c6040680106b9af566d7269d8c949">armnnDeserializer::IDeserializerPtr</a></div><div class="ttdeci">std::unique_ptr< IDeserializer, void(*)(IDeserializer *parser)> IDeserializerPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_deserializer_8hpp_source.xhtml#l00025">IDeserializer.hpp:25</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml_a2ee1264a9803ff8dc1323a26f1f4c986"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#a2ee1264a9803ff8dc1323a26f1f4c986">armnnDeserializer::ToActivationFunction</a></div><div class="ttdeci">armnn::ActivationFunction ToActivationFunction(armnnSerializer::ActivationFunction function)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00406">Deserializer.cpp:406</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::TransposeConvolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01109">Descriptors.hpp:1109</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml_a7c8f847778ed77469bd6ddbd5158ae4e"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#a7c8f847778ed77469bd6ddbd5158ae4e">armnnDeserializer::ToUnaryOperation</a></div><div class="ttdeci">armnn::UnaryOperation ToUnaryOperation(armnnSerializer::UnaryOperation operation)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00469">Deserializer.cpp:469</a></div></div> +<div class="ttc" id="structarmnn_1_1_stand_in_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stand_in_descriptor.xhtml">armnn::StandInDescriptor</a></div><div class="ttdoc">A StandInDescriptor for the StandIn layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00980">Descriptors.hpp:980</a></div></div> +<div class="ttc" id="_deserializer_8cpp_xhtml_a637ba180b64a3cd1a4f83d048a030772"><div class="ttname"><a href="_deserializer_8cpp.xhtml#a637ba180b64a3cd1a4f83d048a030772">CHECK_CONST_TENSOR_PTR</a></div><div class="ttdeci">#define CHECK_CONST_TENSOR_PTR(TENSOR_PTR)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00157">Deserializer.cpp:157</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a37fa39012e90d568df7f774cd6d1e956"><div class="ttname"><a href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">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#l00033">NumericCast.hpp:33</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7ed9bc7c26df67d274d5dd4cd83adf0f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">armnn::DetectionPostProcessDescriptor::m_UseRegularNms</a></div><div class="ttdeci">bool m_UseRegularNms</div><div class="ttdoc">Use Regular NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00539">Descriptors.hpp:539</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::TransposeConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01119">Descriptors.hpp:1119</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_ae9cf8ca62e8da6d21e08dc130f68dce4"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#ae9cf8ca62e8da6d21e08dc130f68dce4">armnnDeserializer::Deserializer::GetNetworkOutputBindingInfo</a></div><div class="ttdeci">BindingPointInfo GetNetworkOutputBindingInfo(unsigned int layerId, const std::string &name) const override</div><div class="ttdoc">Retrieve binding info (layer id and tensor info) for the network output identified by the given layer...</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00764">Deserializer.cpp:764</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_xhtml_a02e143524aefddd40b485fcf7dea6696"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">armnn::SpaceToBatchNdDescriptor::m_BlockShape</a></div><div class="ttdeci">std::vector< unsigned int > m_BlockShape</div><div class="ttdoc">Block shape value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00801">Descriptors.hpp:801</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00020">Descriptors.hpp:20</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="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a></div><div class="ttdoc">min(a, max(b, input)) ReLu1 & ReLu6. </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#l00192">Exceptions.hpp:192</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_abd8bee7fb9b86485a60bc7ee05114270"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#abd8bee7fb9b86485a60bc7ee05114270">armnnDeserializer::Deserializer::TensorRawPtrVector</a></div><div class="ttdeci">std::vector< TensorRawPtr > TensorRawPtrVector</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.xhtml#l00028">Deserializer.hpp:28</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a46c3fa15c46fb0d1dcdc24d0ea5cb5cd"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">armnn::ResizeDescriptor::m_TargetHeight</a></div><div class="ttdeci">uint32_t m_TargetHeight</div><div class="ttdoc">Target height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00746">Descriptors.hpp:746</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00861">Descriptors.hpp:861</a></div></div> +<div class="ttc" id="structarmnn_1_1_slice_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_slice_descriptor.xhtml">armnn::SliceDescriptor</a></div><div class="ttdoc">A SliceDescriptor for the SliceLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00927">Descriptors.hpp:927</a></div></div> +<div class="ttc" id="classarmnn_1_1_permutation_vector_xhtml"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00173">Types.hpp:173</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00432">Descriptors.hpp:432</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a435d3651482bbfcc11263b4e4e0c900f"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">armnn::QuantizedLstmInputParams::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00038">QuantizedLstmParams.hpp:38</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00863">Descriptors.hpp:863</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_depth_descriptor_xhtml_a6c6b8957f1e176867e5fb05b1a1a1486"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">armnn::SpaceToDepthDescriptor::m_BlockSize</a></div><div class="ttdeci">unsigned int m_BlockSize</div><div class="ttdoc">Scalar specifying the input block size. It must be >= 1. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00827">Descriptors.hpp:827</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::InstanceNormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00653">Descriptors.hpp:653</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a0c9267a47f5d254898c67bc0cb2535b9"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a0c9267a47f5d254898c67bc0cb2535b9">armnnDeserializer::Deserializer::GetOutputs</a></div><div class="ttdeci">static TensorRawPtrVector GetOutputs(const GraphPtr &graph, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00619">Deserializer.cpp:619</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::Pooling2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00369">Descriptors.hpp:369</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml_a8275d51ef9a584feb95726ea0522f6e5"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">armnn::InstanceNormalizationDescriptor::m_Beta</a></div><div class="ttdeci">float m_Beta</div><div class="ttdoc">Beta, the offset scalar value applied for the normalized tensor. Defaults to 1.0. ...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00649">Descriptors.hpp:649</a></div></div> +<div class="ttc" id="_parser_helper_8hpp_xhtml"><div class="ttname"><a href="_parser_helper_8hpp.xhtml">ParserHelper.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml_a8b51e137fab21d758b965c6c6e3b02f3"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#a8b51e137fab21d758b965c6c6e3b02f3">armnnDeserializer::ToResizeMethod</a></div><div class="ttdeci">armnn::ResizeMethod ToResizeMethod(armnnSerializer::ResizeMethod method)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00488">Deserializer.cpp:488</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_aa61510cbd529870182e918ac6e8b9d72"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#aa61510cbd529870182e918ac6e8b9d72">armnn::DetectionPostProcessDescriptor::m_ScaleH</a></div><div class="ttdeci">float m_ScaleH</div><div class="ttdoc">Center size encoding scale height. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00547">Descriptors.hpp:547</a></div></div> +<div class="ttc" id="structarmnn_1_1_comparison_descriptor_xhtml_a865dc4f43cb0ff01a1dcf78036912fd1"><div class="ttname"><a href="structarmnn_1_1_comparison_descriptor.xhtml#a865dc4f43cb0ff01a1dcf78036912fd1">armnn::ComparisonDescriptor::m_Operation</a></div><div class="ttdeci">ComparisonOperation m_Operation</div><div class="ttdoc">Specifies the comparison operation to execute. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00078">Descriptors.hpp:78</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_ad0b8c32bb5381f4cc999093ba3b98b43"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#ad0b8c32bb5381f4cc999093ba3b98b43">armnn::LstmInputParams::m_CellLayerNormWeights</a></div><div class="ttdeci">const ConstTensor * m_CellLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00059">LstmParams.hpp:59</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_ace7a1f1f1041b412b7d8ef82b95ff352"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">armnn::LstmInputParams::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensor * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00052">LstmParams.hpp:52</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml">armnn::SpaceToBatchNdDescriptor</a></div><div class="ttdoc">A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00778">Descriptors.hpp:778</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a49e11acda22742cbaf6f1b259ead0d84"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">armnn::LstmInputParams::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00042">LstmParams.hpp:42</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a6e30c7b3451da3ea9cf4259fb602e6e6"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">armnn::LstmInputParams::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00043">LstmParams.hpp:43</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml_afe1f0f09d49ad2befc01f8789187b7dd"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml#afe1f0f09d49ad2befc01f8789187b7dd">armnn::NormalizationDescriptor::m_NormChannelType</a></div><div class="ttdeci">NormalizationAlgorithmChannel m_NormChannelType</div><div class="ttdoc">Normalization channel algorithm to use (Across, Within). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00575">Descriptors.hpp:575</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaaed67cf7d54c570e4c4891800f085f41d"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaed67cf7d54c570e4c4891800f085f41d">armnn::ActivationFunction::Elu</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_a017b2990003a014234f13e999dc7c689"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#a017b2990003a014234f13e999dc7c689">armnn::ActivationDescriptor::m_A</a></div><div class="ttdeci">float m_A</div><div class="ttdoc">Alpha upper bound value used by the activation functions. (BoundedReLu, Linear, TanH). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00037">Descriptors.hpp:37</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::Convolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation along x axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00434">Descriptors.hpp:434</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_depth_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::SpaceToDepthDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00830">Descriptors.hpp:830</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00867">Descriptors.hpp:867</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml_a8fb47fe218330370a5c9c066ac1571ea"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#a8fb47fe218330370a5c9c066ac1571ea">armnnDeserializer::ToArgMinMaxFunction</a></div><div class="ttdeci">armnn::ArgMinMaxFunction ToArgMinMaxFunction(armnnSerializer::ArgMinMaxFunction function)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00437">Deserializer.cpp:437</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::TransposeConvolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01105">Descriptors.hpp:1105</a></div></div> +<div class="ttc" id="structarmnn_1_1_empty_optional_xhtml"><div class="ttname"><a href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a></div><div class="ttdoc">EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00032">Optional.hpp:32</a></div></div> +<div class="ttc" id="classarmnn_1_1_parse_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00092">Exceptions.hpp:92</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a38c1f8ba8e51364802669c968cf98ff5"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a38c1f8ba8e51364802669c968cf98ff5">armnnDeserializer::Deserializer::GraphPtr</a></div><div class="ttdeci">const armnnSerializer::SerializedGraph * GraphPtr</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.xhtml#l00021">Deserializer.hpp:21</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::TransposeConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01113">Descriptors.hpp:1113</a></div></div> +<div class="ttc" id="structarmnn_1_1_elementwise_unary_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_elementwise_unary_descriptor.xhtml">armnn::ElementwiseUnaryDescriptor</a></div><div class="ttdoc">A ElementwiseUnaryDescriptor for the ElementwiseUnaryLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00082">Descriptors.hpp:82</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a0031997bf43bd2747656c31e4977793a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">armnn::Pooling2dDescriptor::m_PoolType</a></div><div class="ttdeci">PoolingAlgorithm m_PoolType</div><div class="ttdoc">The pooling algorithm to use (Max. Average, L2). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00347">Descriptors.hpp:347</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml">armnnDeserializer</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_deserializer_8hpp_source.xhtml#l00016">IDeserializer.hpp:16</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_ae83131e16df1cace69395a5f99bc5ecb"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">armnn::LstmInputParams::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00045">LstmParams.hpp:45</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::DepthwiseConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00484">Descriptors.hpp:484</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_i_deserializer_xhtml_a85f0c438b389992a68adeb6af59f362d"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer.xhtml#a85f0c438b389992a68adeb6af59f362d">armnnDeserializer::IDeserializer::CreateRaw</a></div><div class="ttdeci">static IDeserializer * CreateRaw()</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00656">Deserializer.cpp:656</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::TransposeConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01115">Descriptors.hpp:1115</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a"><div class="ttname"><a href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::PaddingMethod::IgnoreValue</a></div><div class="ttdoc">The padding fields count, but are ignored. </div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a3941f674c071c9503e00d2b59e92e454"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a3941f674c071c9503e00d2b59e92e454">armnn::BatchToSpaceNdDescriptor::m_Crops</a></div><div class="ttdeci">std::vector< std::pair< unsigned int, unsigned int > > m_Crops</div><div class="ttdoc">The values to crop from the input dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00682">Descriptors.hpp:682</a></div></div> +<div class="ttc" id="classarmnn_1_1_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_exception.xhtml">armnn::Exception</a></div><div class="ttdoc">Base class for all ArmNN exceptions so that users can filter to just those. </div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00046">Exceptions.hpp:46</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a68b76ee033fdd629404369171c3d4f90"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a68b76ee033fdd629404369171c3d4f90">armnnDeserializer::Deserializer::ConstTensorRawPtr</a></div><div class="ttdeci">const armnnSerializer::ConstTensor * ConstTensorRawPtr</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.xhtml#l00020">Deserializer.hpp:20</a></div></div> +<div class="ttc" id="_descriptors_8hpp_xhtml"><div class="ttname"><a href="_descriptors_8hpp.xhtml">Descriptors.hpp</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="namespacearmnn_xhtml_a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f"><div class="ttname"><a href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</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="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00043">Tensor.hpp:43</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad605d1661fa0d8c7fea651d82fbe11c9aa94d2fcabc6b001015aeddfa19266e6f"><div class="ttname"><a href="namespacearmnn.xhtml#ad605d1661fa0d8c7fea651d82fbe11c9aa94d2fcabc6b001015aeddfa19266e6f">armnn::NormalizationAlgorithmMethod::LocalContrast</a></div><div class="ttdoc">Jarret 2009: Local Contrast Normalization. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae7e8cbf71db6a490789ca6dcaa8deeae"><div class="ttname"><a href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeae">armnn::ArgMinMaxFunction</a></div><div class="ttdeci">ArgMinMaxFunction</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00071">Types.hpp:71</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a15397ee26bc4b7d3a459b05e457be428"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a15397ee26bc4b7d3a459b05e457be428">armnnDeserializer::Deserializer::LstmDescriptorPtr</a></div><div class="ttdeci">const armnnSerializer::LstmDescriptor * LstmDescriptorPtr</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.xhtml#l00025">Deserializer.hpp:25</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_affb5b68b3eba3ed45a06c7cde7781962"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#affb5b68b3eba3ed45a06c7cde7781962">armnn::Pooling2dDescriptor::m_OutputShapeRounding</a></div><div class="ttdeci">OutputShapeRounding m_OutputShapeRounding</div><div class="ttdoc">The rounding method for the output shape. (Floor, Ceiling). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00365">Descriptors.hpp:365</a></div></div> +<div class="ttc" id="structarmnn_1_1_stand_in_descriptor_xhtml_aed6086070440ceb94129bef06f70173f"><div class="ttname"><a href="structarmnn_1_1_stand_in_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">armnn::StandInDescriptor::m_NumInputs</a></div><div class="ttdeci">uint32_t m_NumInputs</div><div class="ttdoc">Number of input tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00996">Descriptors.hpp:996</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a271f00048f7e48392794c2eee17c1e2c"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a271f00048f7e48392794c2eee17c1e2c">armnnDeserializer::Deserializer::GetPoolingDescriptor</a></div><div class="ttdeci">static armnn::Pooling2dDescriptor GetPoolingDescriptor(PoolingDescriptor pooling2dDescriptor, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l01808">Deserializer.cpp:1808</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_abe18a5033f2ab9c0de82c676b48f5437a37bac6dce4f46277d89bfa3003e2e39b"><div class="ttname"><a href="namespacearmnn.xhtml#abe18a5033f2ab9c0de82c676b48f5437a37bac6dce4f46277d89bfa3003e2e39b">armnn::NormalizationAlgorithmChannel::Within</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml">armnnDeserializer::Deserializer</a></div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.xhtml#l00016">Deserializer.hpp:16</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a1759754ccb88ecc9af44f3aae6e244ee"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">armnn::QuantizedLstmInputParams::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00040">QuantizedLstmParams.hpp:40</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_a9a2af2f8c4af4f9efa8e79417d505ac4"><div class="ttname"><a href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4">armnn::ResizeMethod</a></div><div class="ttdeci">ResizeMethod</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00103">Types.hpp:103</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a435d3651482bbfcc11263b4e4e0c900f"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">armnn::LstmInputParams::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00044">LstmParams.hpp:44</a></div></div> +<div class="ttc" id="structarmnn_1_1_mean_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml">armnn::MeanDescriptor</a></div><div class="ttdoc">A MeanDescriptor for the MeanLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00877">Descriptors.hpp:877</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a6e30c7b3451da3ea9cf4259fb602e6e6"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">armnn::QuantizedLstmInputParams::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00036">QuantizedLstmParams.hpp:36</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a1cfaa710db2a54673b21d2ea2da757c8"><div class="ttname"><a href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8">armnn::UnaryOperation</a></div><div class="ttdeci">UnaryOperation</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00087">Types.hpp:87</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a0953e42cc1f6bb2a50504b631d68b114"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a0953e42cc1f6bb2a50504b631d68b114">armnnDeserializer::Deserializer::GetInputs</a></div><div class="ttdeci">static TensorRawPtrVector GetInputs(const GraphPtr &graph, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l00601">Deserializer.cpp:601</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a4a8ec49f130084445d44297549254780"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">armnn::LstmDescriptor::m_LayerNormEnabled</a></div><div class="ttdeci">bool m_LayerNormEnabled</div><div class="ttdoc">Enable/disable layer normalization. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00873">Descriptors.hpp:873</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaaceb46ca115d05c51aa5a16a8867c3304"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaceb46ca115d05c51aa5a16a8867c3304">armnn::ActivationFunction::Square</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::TransposeConvolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01107">Descriptors.hpp:1107</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_descriptor.xhtml">armnn::TransposeDescriptor</a></div><div class="ttdoc">A TransposeDescriptor for the TransposeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01123">Descriptors.hpp:1123</a></div></div> +<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml">armnn::StridedSliceDescriptor</a></div><div class="ttdoc">A StridedSliceDescriptor for the StridedSliceLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01002">Descriptors.hpp:1002</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_i_connectable_layer_xhtml_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0</div><div class="ttdoc">Get the const output slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f"><div class="ttname"><a href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a></div></div> +<div class="ttc" id="structarmnn_1_1_arg_min_max_descriptor_xhtml_a214c3636fdf0ea5bac8edb42d0e6c7f0"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml#a214c3636fdf0ea5bac8edb42d0e6c7f0">armnn::ArgMinMaxDescriptor::m_Axis</a></div><div class="ttdeci">int m_Axis</div><div class="ttdoc">Axis to reduce across the input tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00058">Descriptors.hpp:58</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7a2156ec7d9c012ce00bbcc6afcb9028"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7a2156ec7d9c012ce00bbcc6afcb9028">armnn::DetectionPostProcessDescriptor::m_ScaleY</a></div><div class="ttdeci">float m_ScaleY</div><div class="ttdoc">Center size encoding scale y. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00543">Descriptors.hpp:543</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a4392dd6b4862cc9cf95ae8f1001ba592"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a4392dd6b4862cc9cf95ae8f1001ba592">armnn::DetectionPostProcessDescriptor::m_NmsScoreThreshold</a></div><div class="ttdeci">float m_NmsScoreThreshold</div><div class="ttdoc">NMS score threshold. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00533">Descriptors.hpp:533</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00101">INetwork.hpp:101</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_i_deserializer_xhtml"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer.xhtml">armnnDeserializer::IDeserializer</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_deserializer_8hpp_source.xhtml#l00027">IDeserializer.hpp:27</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad605d1661fa0d8c7fea651d82fbe11c9ac65d2e51c610dd3853a3c777aa8bfe9d"><div class="ttname"><a href="namespacearmnn.xhtml#ad605d1661fa0d8c7fea651d82fbe11c9ac65d2e51c610dd3853a3c777aa8bfe9d">armnn::NormalizationAlgorithmMethod::LocalBrightness</a></div><div class="ttdoc">Krichevsky 2012: Local Brightness Normalization. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_a2d299363c9fc33334c571fa29ca4f58caa4cbdbb6070a5abb35fc95ecf1e22c14"><div class="ttname"><a href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58caa4cbdbb6070a5abb35fc95ecf1e22c14">armnn::ComparisonOperation::LessOrEqual</a></div></div> +<div class="ttc" id="structarmnn_1_1_check_location_xhtml_a46e3b4b140e2c550342337b5fcceb9c6"><div class="ttname"><a href="structarmnn_1_1_check_location.xhtml#a46e3b4b140e2c550342337b5fcceb9c6">armnn::CheckLocation::m_Function</a></div><div class="ttdeci">const char * m_Function</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00016">Exceptions.hpp:16</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00313">Descriptors.hpp:313</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_abe18a5033f2ab9c0de82c676b48f5437a810f43f3996922151c39b76143faeecc"><div class="ttname"><a href="namespacearmnn.xhtml#abe18a5033f2ab9c0de82c676b48f5437a810f43f3996922151c39b76143faeecc">armnn::NormalizationAlgorithmChannel::Across</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a1cfaa710db2a54673b21d2ea2da757c8acad39a154bffb61175f674d6eefaf6d0"><div class="ttname"><a href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8acad39a154bffb61175f674d6eefaf6d0">armnn::UnaryOperation::Exp</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a9b18daea2e9f42386055326fd016519a"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a9b18daea2e9f42386055326fd016519a">armnn::LstmInputParams::m_OutputLayerNormWeights</a></div><div class="ttdeci">const ConstTensor * m_OutputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00060">LstmParams.hpp:60</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4"><div class="ttname"><a href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4">armnn::UnaryOperation::Rsqrt</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a91ade61b5704e4f2c38c263c2be148ef"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a91ade61b5704e4f2c38c263c2be148ef">armnnDeserializer::Deserializer::LayerBaseRawPtr</a></div><div class="ttdeci">const armnnSerializer::LayerBase * LayerBaseRawPtr</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8hpp_source.xhtml#l00030">Deserializer.hpp:30</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml">armnn::NormalizationDescriptor</a></div><div class="ttdoc">A NormalizationDescriptor for the NormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00551">Descriptors.hpp:551</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a2d299363c9fc33334c571fa29ca4f58ca6f2f0aefb3d22da0f3839453add5f937"><div class="ttname"><a href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca6f2f0aefb3d22da0f3839453add5f937">armnn::ComparisonOperation::GreaterOrEqual</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::ResizeDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00751">Descriptors.hpp:751</a></div></div> +<div class="ttc" id="_deserializer_8hpp_xhtml"><div class="ttname"><a href="_deserializer_8hpp.xhtml">Deserializer.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00495">Descriptors.hpp:495</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml">armnn::InstanceNormalizationDescriptor</a></div><div class="ttdoc">An InstanceNormalizationDescriptor for InstanceNormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00629">Descriptors.hpp:629</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b">armnn::ActivationFunction::Linear</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa0877e5b3fbe9d7569df6399609ed0186"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa0877e5b3fbe9d7569df6399609ed0186">armnn::ActivationFunction::HardSwish</a></div></div> +<div class="ttc" id="classarmnn_deserializer_1_1_deserializer_xhtml_a8752c2b994619ae67201a297c2c76be2"><div class="ttname"><a href="classarmnn_deserializer_1_1_deserializer.xhtml#a8752c2b994619ae67201a297c2c76be2">armnnDeserializer::Deserializer::OutputShapeOfReshape</a></div><div class="ttdeci">static armnn::TensorInfo OutputShapeOfReshape(const armnn::TensorInfo &inputTensorInfo, const std::vector< uint32_t > &targetDimsIn)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l01938">Deserializer.cpp:1938</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_a28c4c9cb15f6be3499abbc46b356060b"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#a28c4c9cb15f6be3499abbc46b356060b">armnn::ActivationDescriptor::m_B</a></div><div class="ttdeci">float m_B</div><div class="ttdoc">Beta lower bound value used by the activation functions. (BoundedReLu, Linear, TanH). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00039">Descriptors.hpp:39</a></div></div> +<div class="ttc" id="structarmnn_1_1_softmax_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_softmax_descriptor.xhtml">armnn::SoftmaxDescriptor</a></div><div class="ttdoc">A SoftmaxDescriptor for the SoftmaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00123">Descriptors.hpp:123</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml_a8275d51ef9a584feb95726ea0522f6e5"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">armnn::NormalizationDescriptor::m_Beta</a></div><div class="ttdeci">float m_Beta</div><div class="ttdoc">Beta value for the normalization equation. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00583">Descriptors.hpp:583</a></div></div> +<div class="ttc" id="namespacearmnn_deserializer_xhtml_a63d3841a5ebb0a5ce572cfb4cb634376"><div class="ttname"><a href="namespacearmnn_deserializer.xhtml#a63d3841a5ebb0a5ce572cfb4cb634376">armnnDeserializer::GetOriginsDescriptor</a></div><div class="ttdeci">const armnnSerializer::OriginsDescriptor * GetOriginsDescriptor(const armnnSerializer::SerializedGraph *graph, unsigned int layerIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_deserializer_8cpp_source.xhtml#l01554">Deserializer.cpp:1554</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml_aa70c05f1aad12fbd9d9ec43ea4557b03"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml#aa70c05f1aad12fbd9d9ec43ea4557b03">armnn::NormalizationDescriptor::m_NormSize</a></div><div class="ttdeci">uint32_t m_NormSize</div><div class="ttdoc">Depth radius value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00579">Descriptors.hpp:579</a></div></div> +<div class="ttc" id="structarmnn_1_1_views_descriptor_xhtml_a2b125117aa61f9baf3a9cb8658aa61a2"><div class="ttname"><a href="structarmnn_1_1_views_descriptor.xhtml#a2b125117aa61f9baf3a9cb8658aa61a2">armnn::ViewsDescriptor::SetViewOriginCoord</a></div><div class="ttdeci">Status SetViewOriginCoord(uint32_t view, uint32_t coord, uint32_t value)</div><div class="ttdoc">Set the view origin coordinates. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.xhtml#l00302">Descriptors.cpp:302</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_af10fa7883e3579950f477bee92a64844"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">armnn::ActivationDescriptor::m_Function</a></div><div class="ttdeci">ActivationFunction m_Function</div><div class="ttdoc">The activation function to use (Sigmoid, TanH, Linear, ReLu, BoundedReLu, SoftReLu, LeakyReLu, Abs, Sqrt, Square). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00035">Descriptors.hpp:35</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_input_slot_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_input_slot.xhtml">armnn::IInputSlot</a></div><div class="ttdoc">An input connection slot for a layer. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00024">INetwork.hpp:24</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Pooling2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00363">Descriptors.hpp:363</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00444">Descriptors.hpp:444</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml">armnn::BatchNormalizationDescriptor</a></div><div class="ttdoc">A BatchNormalizationDescriptor for the BatchNormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00610">Descriptors.hpp:610</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Convolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00422">Descriptors.hpp:422</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#l00093">Tensor.hpp:93</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a31da1ead6794dd64571afdd0b6efc771"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">armnn::LstmInputParams::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00041">LstmParams.hpp:41</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9ea"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a></div><div class="ttdeci">ActivationFunction</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00055">Types.hpp:55</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae7e8cbf71db6a490789ca6dcaa8deeaea78d811e98514cd165dda532286610fd2"><div class="ttname"><a href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeaea78d811e98514cd165dda532286610fd2">armnn::ArgMinMaxFunction::Min</a></div></div> +<div class="ttc" id="structarmnn_1_1_permute_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_permute_descriptor.xhtml">armnn::PermuteDescriptor</a></div><div class="ttdoc">A PermuteDescriptor for the PermuteLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00102">Descriptors.hpp:102</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::DepthwiseConvolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00476">Descriptors.hpp:476</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e">armnn::ActivationFunction::TanH</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_affcee5f4ab5994a21bee3b78b4e43de3"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">armnn::LstmInputParams::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00040">LstmParams.hpp:40</a></div></div> +<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_ac0981848e4ae57729f14f72bd4caa9f8"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a></div><div class="ttdeci">std::vector< float > anchors({ 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 100.5f, 1.0f, 1.0f })</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_926e64104daaa2ed9ca6061297f76df9.xhtml">armnnDeserializer</a></li><li class="navelem"><a class="el" href="_deserializer_8cpp.xhtml">Deserializer.cpp</a></li> + <li class="footer">Generated on Fri Mar 13 2020 16:09:09 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + </ul> 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