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diff --git a/20.02/_network_8cpp_source.xhtml b/20.02/_network_8cpp_source.xhtml new file mode 100644 index 0000000000..eabd736be2 --- /dev/null +++ b/20.02/_network_8cpp_source.xhtml @@ -0,0 +1,503 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/armnn/Network.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('_network_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">Network.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_network_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="_network_8hpp.xhtml">Network.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_graph_8hpp.xhtml">Graph.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_layer_8hpp.xhtml">Layer.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_device_spec_8hpp.xhtml">DeviceSpec.hpp</a>"</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include "<a class="code" href="_optimizer_8hpp.xhtml">Optimizer.hpp</a>"</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include "<a class="code" href="_subgraph_view_selector_8hpp.xhtml">SubgraphViewSelector.hpp</a>"</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include "<a class="code" href="_backend_settings_8hpp.xhtml">BackendSettings.hpp</a>"</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include "<a class="code" href="_all_8hpp.xhtml">optimizations/All.hpp</a>"</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_cpu_tensor_handle_8hpp.xhtml">backendsCommon/CpuTensorHandle.hpp</a>></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_workload_factory_8hpp.xhtml">backendsCommon/WorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <<a class="code" href="include_2armnn_2backends_2_i_backend_internal_8hpp.xhtml">armnn/backends/IBackendInternal.hpp</a>></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <<a class="code" href="_tensor_handle_factory_registry_8hpp.xhtml">backendsCommon/TensorHandleFactoryRegistry.hpp</a>></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <<a class="code" href="_exceptions_8hpp.xhtml">armnn/Exceptions.hpp</a>></span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include <<a class="code" href="_utils_8hpp.xhtml">armnn/Utils.hpp</a>></span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="preprocessor">#include <<a class="code" href="_types_utils_8hpp.xhtml">armnn/TypesUtils.hpp</a>></span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#include <<a class="code" href="_backend_registry_8hpp.xhtml">armnn/BackendRegistry.hpp</a>></span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include <<a class="code" href="_logging_8hpp.xhtml">armnn/Logging.hpp</a>></span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</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="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include <<a class="code" href="_profiling_service_8hpp.xhtml">ProfilingService.hpp</a>></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 <fcntl.h></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 <fstream></span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include <memory></span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include <algorithm></span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include <boost/assert.hpp></span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#include <boost/format.hpp></span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#include <boost/numeric/conversion/converter_policies.hpp></span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include <boost/cast.hpp></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><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> {</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00044"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a1ca931603a06e926ca359e52890a6fea"> 44</a></span> <a class="code" href="classarmnn_1_1_i_network.xhtml">armnn::INetwork</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a1ca931603a06e926ca359e52890a6fea">INetwork::CreateRaw</a>()</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="keywordflow">return</span> <span class="keyword">new</span> <a class="code" href="classarmnn_1_1_network.xhtml">Network</a>();</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> }</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a706f7345af3f18f4b16e226a672214c6"> 49</a></span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> <a class="code" href="classarmnn_1_1_i_network.xhtml#a706f7345af3f18f4b16e226a672214c6">INetwork::Create</a>()</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a>(<a class="code" href="classarmnn_1_1_i_network.xhtml#a1ca931603a06e926ca359e52890a6fea">CreateRaw</a>(), &<a class="code" href="classarmnn_1_1_i_network.xhtml#a55bd1bb29076dc45bb335e7322781463">INetwork::Destroy</a>);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> }</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a55bd1bb29076dc45bb335e7322781463"> 54</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a55bd1bb29076dc45bb335e7322781463">INetwork::Destroy</a>(<a class="code" href="classarmnn_1_1_i_network.xhtml">INetwork</a>* network)</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> {</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keyword">delete</span> boost::polymorphic_downcast<Network*>(network);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> }</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_optimized_network.xhtml#a58ee539cf95c1e99fe4f54ef6e8bbd05"> 59</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a58ee539cf95c1e99fe4f54ef6e8bbd05">IOptimizedNetwork::Destroy</a>(<a class="code" href="classarmnn_1_1_i_optimized_network.xhtml">IOptimizedNetwork</a>* network)</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="keyword">delete</span> boost::polymorphic_downcast<OptimizedNetwork*>(network);</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> </div><div class="line"><a name="l00064"></a><span class="lineno"><a class="line" href="classarmnn_1_1_optimized_network.xhtml#a9aa1b214fcaec2371fe4226bd126fb73"> 64</a></span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_optimized_network.xhtml#a9aa1b214fcaec2371fe4226bd126fb73">OptimizedNetwork::PrintGraph</a>()</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> {</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  m_Graph->Print();</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">Status::Success</a>;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> }</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div><div class="line"><a name="l00070"></a><span class="lineno"><a class="line" href="classarmnn_1_1_optimized_network.xhtml#a6201b0b0af2110feee1489a5fe9c7ec2"> 70</a></span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_optimized_network.xhtml#a6201b0b0af2110feee1489a5fe9c7ec2">OptimizedNetwork::SerializeToDot</a>(std::ostream& stream)<span class="keyword"> const</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="keyword"></span>{</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordflow">return</span> m_Graph->SerializeToDot(stream);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> }</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> </div><div class="line"><a name="l00075"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994"> 75</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994">ReportError</a>(<span class="keyword">const</span> std::string& errorMessage,</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errorMessages)</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>  std::stringstream fullErrorMessage;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  fullErrorMessage << <span class="stringliteral">"ERROR: "</span> << errorMessage;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">warning</a>) << fullErrorMessage.str();</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordflow">if</span> (errorMessages)</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  errorMessages.value().push_back(fullErrorMessage.str());</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  }</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> }</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a38e626422579decc13e3ee37da1a84c9"> 87</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#a38e626422579decc13e3ee37da1a84c9">ReportWarning</a>(<span class="keyword">const</span> std::string& warningMessage,</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> warningMessages)</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> {</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  std::stringstream fullWarningMessage;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  fullWarningMessage << <span class="stringliteral">"WARNING: "</span> << warningMessage;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">warning</a>) << fullWarningMessage.str();</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordflow">if</span> (warningMessages)</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  {</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  warningMessages.value().push_back(fullWarningMessage.str());</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  }</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> }</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#ae50fff9aa2a1ce46392d8641c10aa3bc"> 99</a></span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> <a class="code" href="namespacearmnn.xhtml#ae50fff9aa2a1ce46392d8641c10aa3bc">ReturnWithError</a>(<a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> res,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* layer,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a>& backendSettings,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> {</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  std::stringstream failureMsg;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  failureMsg << <span class="stringliteral">"Layer of type "</span> << <a class="code" href="namespacearmnn.xhtml#a9da573d7a1fc03726fd41f2130cbcf92">GetLayerTypeAsCString</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>())</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  << <span class="stringliteral">" is not supported on any preferred backend "</span> << backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#ae6d0506ac92f9ba9529d019847144aa3">m_PreferredBackends</a>;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <a class="code" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994">ReportError</a>(failureMsg.str(), errMessages);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  res.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a41a657cfacb52a80a73575c5c730ab88">m_Error</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordflow">return</span> res;</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> </div><div class="line"><a name="l00114"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#af002111f64aee648e3258247075cae36"> 114</a></span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn.xhtml#af002111f64aee648e3258247075cae36">CheckScaleSetOnQuantizedType</a>(<a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* layer, <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</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="keywordtype">bool</span> noErrors = <span class="keyword">true</span>;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputs = layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a1594bddc87d6477df300317658f566bb">GetNumOutputSlots</a>();</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</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="l00119"></a><span class="lineno"> 119</span>  <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>& outputSlot = layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(i);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a> == info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()) {</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keywordflow">if</span> (0.f == info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>()) {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  noErrors = <span class="keyword">false</span>;</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  std::stringstream ss;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  ss << <span class="stringliteral">"output "</span> << i << <span class="stringliteral">" of layer "</span> << <a class="code" href="namespacearmnn.xhtml#a9da573d7a1fc03726fd41f2130cbcf92">GetLayerTypeAsCString</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>())</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  << <span class="stringliteral">" ("</span> << layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a9a97cb6d32661a57fc33bd29b8e41ff4">GetNameStr</a>() << <span class="stringliteral">") is of type"</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  << <span class="stringliteral">" Quantized 8 bit but its scale parameter has not been set"</span>;</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994">ReportError</a>(ss.str(), errMessages);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  }</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="comment">// Softmax under QuantisedAsymm8 must always be scale (1.0f/256.0f) and offset 0</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">if</span> ((info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>() != (1.0f / 256.0f) ||</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>() != 0) &&</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a31d953b9d49a6b4378f45097047976d0">armnn::LayerType::Softmax</a>)</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  {</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  std::stringstream ss;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  ss << <span class="stringliteral">"Quantization parameters for Softmax layer (Scale: "</span> <<</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>() << <span class="stringliteral">" and Offset: "</span> << info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>() <<</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="stringliteral">") are incorrect and have been updated to Scale: 0.00390625 and Offset: 0"</span>;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">warning</a>) << ss.str();</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>((1.0f /256.0f));</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(0);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  }</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  }</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  }</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keywordflow">return</span> noErrors;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> }</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a56f168327453ea4461cbc1c0ac7f15b6"> 149</a></span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> <a class="code" href="namespacearmnn.xhtml#a56f168327453ea4461cbc1c0ac7f15b6">AttemptBackendAssignment</a>(<a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a>& backendSettings,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph,</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* layer,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <a class="code" href="classarmnn_1_1_backend_id.xhtml">BackendId</a> backend,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataTypeIn,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataTypeOut,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keyword">const</span> std::vector<BackendId>& availablePreferredBackends,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  std::string& reasonIfUnsupported,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> {</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> result;</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="comment">// Helper lambda to compose meaningful error message before returning with error</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">auto</span> ReturnError = [&](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* layer)</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  {</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ae50fff9aa2a1ce46392d8641c10aa3bc">ReturnWithError</a>(result, layer, backendSettings, errMessages);</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"> 167</span>  <span class="comment">// need to set the compute device on the layer</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="comment">// before we can check if it is supported</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a3f6ad59212fa8a47c9265162fff8a274">SetBackendId</a>(backend);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a74dc9ec1a223eab8b072368b2dacee87">IWorkloadFactory::IsLayerSupported</a>(*layer, <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>(), reasonIfUnsupported))</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">if</span> (dataTypeIn == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a> || dataTypeOut == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>)</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>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a74dc9ec1a223eab8b072368b2dacee87">IWorkloadFactory::IsLayerSupported</a>(*layer, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>, reasonIfUnsupported)</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  && layer-><a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">LayerType::ConvertFp32ToFp16</a></div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  && layer-><a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">LayerType::ConvertFp16ToFp32</a>)</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  {</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="comment">// Insert FP16 -> FP32 conversion layer before current layer</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  std::vector<ConvertFp16ToFp32Layer*> convertFp16ToFp32Layers;</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordflow">if</span> (dataTypeIn == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>)</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>  convertFp16ToFp32Layers =</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="namespacearmnn.xhtml#ad31c56533e4f9f9f51719599fbfcf7bb">InsertConvertFp16ToFp32LayersBefore</a>(graph, *layer);</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"> 186</span>  <span class="comment">// Insert FP32 -> FP16 conversion layer after current layer</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  std::vector<ConvertFp32ToFp16Layer*> convertFp32ToFp16Layers;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordflow">if</span> (dataTypeOut == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>)</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  {</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  convertFp32ToFp16Layers =</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <a class="code" href="namespacearmnn.xhtml#abf625e50a5eaeafce5b39580dc95a9d3">InsertConvertFp32ToFp16LayersAfter</a>(graph, *layer);</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  }</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> </div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="comment">// Assign a supported backend to the newly introduced conversion layers</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keyword">auto</span> AssignFirstSupportedBackend = [&](<a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* layer, <a class="code" href="classarmnn_1_1_backend_id.xhtml">BackendId</a> preferredBackend)</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  {</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keywordtype">bool</span> supportedBackendFound = <span class="keyword">false</span>;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  std::string reasonIfUnsupported;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="comment">// Try preferred backend first</span></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a3f6ad59212fa8a47c9265162fff8a274">SetBackendId</a>(preferredBackend);</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a74dc9ec1a223eab8b072368b2dacee87">IWorkloadFactory::IsLayerSupported</a>(*layer,</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>(),</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  reasonIfUnsupported))</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  {</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  supportedBackendFound = <span class="keyword">true</span>;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  }</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  {</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& backend : availablePreferredBackends)</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  {</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="comment">// Skip preferred backend (we already determined that it is not supported)</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="keywordflow">if</span> (backend == preferredBackend)</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  {</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  }</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> </div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a3f6ad59212fa8a47c9265162fff8a274">SetBackendId</a>(backend);</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a74dc9ec1a223eab8b072368b2dacee87">IWorkloadFactory::IsLayerSupported</a>(*layer,</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>(),</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  reasonIfUnsupported))</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  {</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  supportedBackendFound = <span class="keyword">true</span>;</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  }</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  }</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  }</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> </div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="keywordflow">return</span> supportedBackendFound;</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  };</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> </div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keywordflow">for</span> (<a class="code" href="classarmnn_1_1_convert_fp16_to_fp32_layer.xhtml">ConvertFp16ToFp32Layer</a>* convertLayer : convertFp16ToFp32Layers)</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  {</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <span class="keywordflow">if</span> (!AssignFirstSupportedBackend(convertLayer, backend))</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  {</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="keywordflow">return</span> ReturnError(convertLayer);</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  }</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  }</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> </div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <span class="keywordflow">for</span> (<a class="code" href="classarmnn_1_1_convert_fp32_to_fp16_layer.xhtml">ConvertFp32ToFp16Layer</a>* convertLayer : convertFp32ToFp16Layers)</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  {</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordflow">if</span> (!AssignFirstSupportedBackend(convertLayer, backend))</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  {</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <span class="keywordflow">return</span> ReturnError(convertLayer);</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  }</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"> 248</span>  <span class="keywordflow">return</span> result;</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>  }</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  std::stringstream warningMsg;</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  warningMsg << <span class="stringliteral">"Layer of type "</span> << <a class="code" href="namespacearmnn.xhtml#a9da573d7a1fc03726fd41f2130cbcf92">GetLayerTypeAsCString</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>())</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  << <span class="stringliteral">" is not supported on requested backend "</span> << layer-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>().<a class="code" href="classarmnn_1_1_backend_id.xhtml#af7445617163d3f07c47b92ae56c6cf8b">Get</a>()</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  << <span class="stringliteral">" for input data type "</span> << <a class="code" href="namespacearmnn.xhtml#a81b5ff8545adad19a1c9d4ca076d552c">GetDataTypeName</a>(dataTypeIn)</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  << <span class="stringliteral">" and output data type "</span> << <a class="code" href="namespacearmnn.xhtml#a81b5ff8545adad19a1c9d4ca076d552c">GetDataTypeName</a>(dataTypeOut)</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  << <span class="stringliteral">" (reason: "</span> << reasonIfUnsupported</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  << <span class="stringliteral">"), falling back to the next backend."</span>;</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <a class="code" href="namespacearmnn.xhtml#a38e626422579decc13e3ee37da1a84c9">ReportWarning</a>(warningMsg.str(), errMessages);</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> </div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keywordflow">return</span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a>(<span class="keyword">true</span>, <span class="keyword">false</span>);</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  }</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  {</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  }</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> }</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> </div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> </div><div class="line"><a name="l00269"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a8acab870a91373c720c9822b59ecf3b8"> 269</a></span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> <a class="code" href="namespacearmnn.xhtml#a8acab870a91373c720c9822b59ecf3b8">AssignBackends</a>(<a class="code" href="classarmnn_1_1_optimized_network.xhtml">OptimizedNetwork</a>* optNetObjPtr,</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a>& backendSettings,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a>& firstLayer,</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a>& lastLayer,</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> {</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> result;</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> </div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="comment">// Helper lambda to compose meaningful error message before returning with error</span></div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="keyword">auto</span> ReturnError = [&](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* layer)</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  {</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ae50fff9aa2a1ce46392d8641c10aa3bc">ReturnWithError</a>(result, layer, backendSettings, errMessages);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  };</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> </div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> </div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="keyword">auto</span> availablePreferredBackends = backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#ad4ca579528452c669b45f3f35300fd4e">GetAvailablePreferredBackends</a>();</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keywordflow">if</span> (availablePreferredBackends.empty())</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  {</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  std::stringstream failureMsg;</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  failureMsg << <span class="stringliteral">"No preferred backends are available"</span>;</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <a class="code" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994">ReportError</a>(failureMsg.str(), errMessages);</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> </div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  result.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a41a657cfacb52a80a73575c5c730ab88">m_Error</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  }</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it = firstLayer; it != lastLayer; ++it)</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  {</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keyword">auto</span> layer = *it;</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataTypeIn = layer->GetNumInputSlots() == 0 ? <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a> :</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  layer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo().GetDataType();</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataTypeOut = layer->GetNumOutputSlots() == 0 ? <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a> :</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  layer->GetOutputSlot(0).GetTensorInfo().GetDataType();</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span> </div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  std::string reasonIfUnsupported;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordtype">bool</span> found = <span class="keyword">false</span>;</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.xhtml#af002111f64aee648e3258247075cae36">CheckScaleSetOnQuantizedType</a>(layer, errMessages))</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  {</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="comment">// don't bomb immediately, find all the quantized outputs</span></div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="comment">// which haven't had a scale set and report them all back.</span></div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  result.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a41a657cfacb52a80a73575c5c730ab88">m_Error</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  }</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="comment">// First try assign layer to hint backend</span></div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordflow">if</span> (layer->GetBackendHint().has_value() &&</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#aa5df3120ee0fbb3321df3133ec9e83ae">IsBackendSupported</a>(layer->GetBackendHint().value()) &&</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <a class="code" href="namespacearmnn.xhtml#a56f168327453ea4461cbc1c0ac7f15b6">AttemptBackendAssignment</a>(backendSettings,</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  optNetObjPtr-><a class="code" href="classarmnn_1_1_optimized_network.xhtml#a49800ad35ea869aa5569519760d3b339">GetGraph</a>(),</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  layer,</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  layer->GetBackendHint().value(),</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  dataTypeIn,</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  dataTypeOut,</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  availablePreferredBackends,</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  reasonIfUnsupported,</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  errMessages).IsOk())</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  {</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  found = <span class="keyword">true</span>;</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#aa09ac75b83067c5ed455f2bb35c7c98d">m_SelectedBackends</a>.insert(layer->GetBackendHint().value());</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  }</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  {</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="comment">// Try assign layer to prefered list of backends</span></div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& backend : availablePreferredBackends)</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  {</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">if</span> (layer->GetBackendHint().has_value() &&</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  layer->GetBackendHint().value() == backend)</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  {</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="keywordflow">continue</span>; <span class="comment">//Don't re-test the backend hint</span></div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  }</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> </div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> res = <a class="code" href="namespacearmnn.xhtml#a56f168327453ea4461cbc1c0ac7f15b6">AttemptBackendAssignment</a>(backendSettings,</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  optNetObjPtr-><a class="code" href="classarmnn_1_1_optimized_network.xhtml#a49800ad35ea869aa5569519760d3b339">GetGraph</a>(),</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  layer,</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  backend,</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  dataTypeIn,</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  dataTypeOut,</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  availablePreferredBackends,</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  reasonIfUnsupported,</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  errMessages);</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> </div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">if</span> (res.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a955b65059e7f9429a5d6041136bc1487">IsOk</a>())</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  {</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  found = <span class="keyword">true</span>;</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#aa09ac75b83067c5ed455f2bb35c7c98d">m_SelectedBackends</a>.insert(backend);</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  }</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (res.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#aca1654c65182fe4e7d5fd45f556fcd57">IsError</a>())</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  {</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordflow">return</span> res; <span class="comment">// Cannot continue.</span></div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="comment">// Note: we don't need to log the error as it would already</span></div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="comment">// be logged in AttemptBackendAssignment().</span></div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  }</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  {</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  BOOST_ASSERT_MSG(res.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a2a35773a5a0e08b180a12205c3e15500">IsWarningOnly</a>(), <span class="stringliteral">"OptimizationResult in unexpected state."</span>);</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  }</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  }</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  }</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> </div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="comment">// If the layer is unsupported by any devices, log and return a null network.</span></div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="keywordflow">if</span> (!found)</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  {</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="comment">// NOTE: if the layer is not an operation queue type AND we have not got CpuRef as a</span></div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="comment">// fallback we should set the compute device on the layer to CpuRef (these are not</span></div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="comment">// available as accelerated operations, or are only available under certain</span></div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="comment">// conditions, currently they comprise MemCopy, Constant, Permute)</span></div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a> layerType = layer->GetType();</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="keywordflow">if</span> (!backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#ae4f9f2c5e3b5cf694315f66cde5b33f0">IsCpuRefUsed</a>() && (layerType == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</a> ||</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  layerType == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</a> ||</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  layerType == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnn::LayerType::Permute</a>))</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>  <a class="code" href="classarmnn_1_1_backend_id.xhtml">BackendId</a> cpuBackendId(<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a>);</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  layer->SetBackendId(cpuBackendId);</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#aa09ac75b83067c5ed455f2bb35c7c98d">m_SelectedBackends</a>.insert(cpuBackendId);</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">else</span></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">return</span> ReturnError(layer);</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>  }</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  }</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> </div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> }</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> </div><div class="line"><a name="l00395"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a76dca645d0d0665f74e171bbc1901469"> 395</a></span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> <a class="code" href="namespacearmnn.xhtml#a8acab870a91373c720c9822b59ecf3b8">AssignBackends</a>(<a class="code" href="classarmnn_1_1_optimized_network.xhtml">OptimizedNetwork</a>* optNetObjPtr,</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a>& backendSettings,</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <a class="code" href="classarmnn_1_1_subgraph_view.xhtml">SubgraphView</a>& subgraph,</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> {</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a> firstLayer = subgraph.<a class="code" href="classarmnn_1_1_subgraph_view.xhtml#a2fc512b3ddb7bb2cdf02f44038ca2500">begin</a>();</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a> lastLayer = subgraph.<a class="code" href="classarmnn_1_1_subgraph_view.xhtml#aaf68d7cca5c48a7f3d398452a5244667">end</a>();</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a8acab870a91373c720c9822b59ecf3b8">AssignBackends</a>(optNetObjPtr,</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  backendSettings,</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  firstLayer,</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  lastLayer,</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  errMessages);</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> </div><div class="line"><a name="l00409"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a1ec6b4c20ed294a96cf94c33c24caaf5"> 409</a></span> <a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a> <a class="code" href="namespacearmnn.xhtml#a1ec6b4c20ed294a96cf94c33c24caaf5">CreateSupportedBackends</a>(<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& handleFactoryRegistry,</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a>& backendSettings)</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> {</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a> backends;</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <span class="keyword">auto</span> <span class="keyword">const</span>& backendRegistry = <a class="code" href="namespacearmnn.xhtml#ac2807505b850738bc8a1991ce669dd47">BackendRegistryInstance</a>();</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& selectedBackend : backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#a0b160952af61b24d88125d66ed6d43c1">m_SupportedBackends</a>)</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  {</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keyword">auto</span> backendFactory = backendRegistry.GetFactory(selectedBackend);</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keyword">auto</span> backendObjPtr = backendFactory();</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  BOOST_ASSERT(backendObjPtr);</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> </div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  backendObjPtr->RegisterTensorHandleFactories(handleFactoryRegistry);</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span> </div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  backends[backendObjPtr->GetId()] = std::move(backendObjPtr);</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  }</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span> </div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  <span class="keywordflow">return</span> backends;</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> }</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> </div><div class="line"><a name="l00428"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#ae97734279fd10b4c754cc15bc8ed9dad"> 428</a></span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> <a class="code" href="namespacearmnn.xhtml#ae97734279fd10b4c754cc15bc8ed9dad">ApplyBackendOptimizations</a>(<a class="code" href="classarmnn_1_1_optimized_network.xhtml">OptimizedNetwork</a>* optNetObjPtr,</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a>& backendSettings,</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a>& backends,</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span> {</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  BOOST_ASSERT(optNetObjPtr);</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>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> result;</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="comment">// Get the optimized graph</span></div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& optGraph = optNetObjPtr-><a class="code" href="classarmnn_1_1_optimized_network.xhtml#a49800ad35ea869aa5569519760d3b339">GetGraph</a>();</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span> </div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <span class="comment">// Run backend specific optimizations</span></div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& selectedBackend : backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#aa09ac75b83067c5ed455f2bb35c7c98d">m_SelectedBackends</a>)</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  {</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <span class="keyword">auto</span> backendObjPtr = backends.find(selectedBackend)->second.get();</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  BOOST_ASSERT(backendObjPtr);</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span> </div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <span class="comment">// Select sub-graphs based on backend</span></div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <a class="code" href="classarmnn_1_1_subgraph_view_selector.xhtml#aaf71a63dbbc776f8961b0f4fdb9da021">SubgraphViewSelector::Subgraphs</a> subgraphs =</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <a class="code" href="classarmnn_1_1_subgraph_view_selector.xhtml#a3730b0a6006f0d87f894a44e01869d90">SubgraphViewSelector::SelectSubgraphs</a>(optGraph,</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <span class="comment">// Select layers assigned to the requested backend</span></div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  [&backendObjPtr](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& layer)</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  {</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="keywordflow">return</span> layer.<a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a> &&</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  layer.<a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a> &&</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  layer.<a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() == backendObjPtr->GetId();</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  });</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="keywordflow">if</span> (subgraphs.empty())</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  {</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="comment">// No sub-graphs found, try with next selected backend</span></div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  }</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span> </div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <span class="comment">// Try to optimize each sub-graph</span></div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& subgraph : subgraphs)</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  {</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="comment">// Try to optimize the current sub-graph</span></div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <a class="code" href="classarmnn_1_1_optimization_views.xhtml">OptimizationViews</a> optimizationViews = backendObjPtr->OptimizeSubgraphView(*subgraph);</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  BOOST_ASSERT(optimizationViews.<a class="code" href="classarmnn_1_1_optimization_views.xhtml#a58dc3ea86870112f745b2a1f7dca55e9">Validate</a>(*subgraph));</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span> </div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="comment">// Optimization attempted, check the resulting optimized sub-graph</span></div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& substitution : optimizationViews.<a class="code" href="classarmnn_1_1_optimization_views.xhtml#a9a1555f25af4a0ae2c0a1fc0ed9aded8">GetSubstitutions</a>())</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  {</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <span class="comment">// Sub-graph optimized, substitute the sub-graph with the new optimized one in the main optimized graph</span></div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <a class="code" href="classarmnn_1_1_subgraph_view.xhtml">SubgraphView</a>& replacementSubgraph = substitution.m_ReplacementSubgraph;</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <a class="code" href="classarmnn_1_1_subgraph_view.xhtml">SubgraphView</a>& substitutableSubgraph = substitution.m_SubstitutableSubgraph;</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  optGraph.<a class="code" href="classarmnn_1_1_graph.xhtml#aafbd4b469e47160017f409df8d077184">SubstituteSubgraph</a>(substitutableSubgraph, replacementSubgraph);</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span> </div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  <span class="comment">// Assign the current backend to the optimized sub-graph</span></div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  std::for_each(replacementSubgraph.<a class="code" href="classarmnn_1_1_subgraph_view.xhtml#a2fc512b3ddb7bb2cdf02f44038ca2500">begin</a>(), replacementSubgraph.<a class="code" href="classarmnn_1_1_subgraph_view.xhtml#aaf68d7cca5c48a7f3d398452a5244667">end</a>(), [&selectedBackend](<a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* l)</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  {</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  BOOST_ASSERT(l);</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  l->SetBackendId(selectedBackend);</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  });</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  }</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span> </div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <span class="keywordflow">if</span> (!optimizationViews.<a class="code" href="classarmnn_1_1_optimization_views.xhtml#ad5fee4381bf82ffa37658dddf4d1fa01">GetFailedSubgraphs</a>().empty())</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>  std::stringstream warningMsg;</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  warningMsg << <span class="stringliteral">"Some sub-graph(s) failed to optimized on "</span> << backendObjPtr->GetId() << <span class="stringliteral">" backend."</span>;</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <a class="code" href="namespacearmnn.xhtml#a38e626422579decc13e3ee37da1a84c9">ReportWarning</a>(warningMsg.str(), errMessages);</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span> </div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="comment">// Failed to optimize the given sub-graph, re-assign the sub-graph layers to other available backends</span></div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a> settingsCopy(backendSettings);</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <span class="keywordflow">if</span> (!backendObjPtr->GetId().IsCpuRef())</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  {</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="comment">// Add the current backend to the list of backends to ignore</span></div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  settingsCopy.m_IgnoredBackends.insert(backendObjPtr->GetId());</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  }</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span> </div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <span class="keywordtype">int</span> count=0;</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& failedSubgraph : optimizationViews.<a class="code" href="classarmnn_1_1_optimization_views.xhtml#ad5fee4381bf82ffa37658dddf4d1fa01">GetFailedSubgraphs</a>())</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  {</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="comment">// An error occurred: the optimization was attempted but not performed, try different backends</span></div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  std::stringstream subgraphMsg;</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  subgraphMsg << <span class="stringliteral">"Re-assigning backends to "</span> << failedSubgraph.GetLayers().size()</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  << <span class="stringliteral">" layers inside sub-graph "</span> << count++;</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <a class="code" href="namespacearmnn.xhtml#a38e626422579decc13e3ee37da1a84c9">ReportWarning</a>(subgraphMsg.str(), errMessages);</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>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> reassignmentResult = <a class="code" href="namespacearmnn.xhtml#a8acab870a91373c720c9822b59ecf3b8">AssignBackends</a>(optNetObjPtr,</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  settingsCopy,</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  *subgraph,</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  errMessages);</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <span class="keywordflow">if</span> (reassignmentResult.m_Error)</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  {</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <span class="comment">// Failed to re-assign one of the remaining backends to each layer of the sub-graph</span></div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  result.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a41a657cfacb52a80a73575c5c730ab88">m_Error</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  }</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  }</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  }</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  }</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  }</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span> </div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span> }</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span> </div><div class="line"><a name="l00526"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a5ee4a1cca55f69b31e625c786655ed1a"> 526</a></span> <span class="keywordtype">bool</span> <a class="code" href="namespacearmnn.xhtml#a5ee4a1cca55f69b31e625c786655ed1a">RequiresCopy</a>(<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> src,</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> dst,</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry)</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span> {</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <span class="keywordflow">if</span> (src != dst)</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  {</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">ITensorHandleFactory</a>* srcFactory = registry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(src);</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">ITensorHandleFactory</a>* dstFactory = registry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(dst);</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span> </div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  <span class="keywordflow">if</span> (srcFactory && dstFactory &&</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  (srcFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9892b82652ffac03f1e4e7ad93906078">GetExportFlags</a>() & dstFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ab17a7eb3afac8667ace153b0fe2f82fe">GetImportFlags</a>()) != 0)</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  {</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  }</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <span class="keywordflow">return</span> <span class="keyword">true</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="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span> }</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="comment">// Find the handle factory for the input layer which results in fewest required copies.</span></div><div class="line"><a name="l00546"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#accb1637c58e1523f740025e0d0e7c6dd"> 546</a></span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> <a class="code" href="namespacearmnn.xhtml#accb1637c58e1523f740025e0d0e7c6dd">CalculateSlotOptionForInput</a>(<a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a>& backends,</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>& slot,</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry)</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span> {</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& layer = slot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7ddaf04177053a536f0e7be83a642bc6">GetOwningLayer</a>();</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  BOOST_ASSERT(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>);</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span> </div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <span class="comment">// Explicitly select the tensorhandle factory for InputLayer because the rules for it are slightly different. It</span></div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <span class="comment">// doesn't matter which backend it is assigned to because they all use the same implementation, which</span></div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <span class="comment">// requires Map/Unmap support. This means that, so long as the handle type supports map/unmap semantics, we can</span></div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  <span class="comment">// select a factory with maximum compatibility with the layers connected to the InputLayer.</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"> 558</span>  <span class="comment">// First ensure the from backends can support the TensorHandeAPI</span></div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  <span class="keyword">auto</span> frmBackend = backends.find(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>());</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <span class="keywordflow">if</span> (frmBackend == backends.end() ||</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  !frmBackend->second->SupportsTensorAllocatorAPI())</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">return</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9c95f90eb40e31f629e0e2947b8bc6f9">ITensorHandleFactory::LegacyFactoryId</a>;</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> </div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <span class="comment">// Go through all connections to the output slot and determine the TensorHandleFactory which results in the</span></div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="comment">// fewest copies.</span></div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  std::map<ITensorHandleFactory::FactoryId, int> factoryScores;</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  <span class="keywordtype">int</span> topScore = 0;</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> topChoice = <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9c95f90eb40e31f629e0e2947b8bc6f9">ITensorHandleFactory::LegacyFactoryId</a>;</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span> </div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& connection : slot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#a50b562d4a4edc64d7d8abcca056f0b8c">GetConnections</a>())</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  {</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& connectedLayer = connection->GetOwningLayer();</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span> </div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="keyword">auto</span> toBackend = backends.find(connectedLayer.<a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>());</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  BOOST_ASSERT_MSG(toBackend != backends.end(), <span class="stringliteral">"Backend id not found for the connected layer"</span>);</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="keywordflow">if</span> (!toBackend->second.get()->SupportsTensorAllocatorAPI())</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  {</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="comment">// The destination backend does not support the tensor allocator API, move to the next one</span></div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  }</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> dstPrefs = toBackend->second.get()->GetHandleFactoryPreferences();</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& dst : dstPrefs)</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  {</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  <span class="comment">// Input layers use the mem copy workload or import, so the selected factory must</span></div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <span class="comment">// support either the map/unmap API or Import API</span></div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">ITensorHandleFactory</a>* factory = registry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(dst);</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <span class="keywordflow">if</span> (!factory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#aa262a54803b53b8198cd60e7af2f60e4">SupportsMapUnmap</a>() &&</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  !<a class="code" href="namespacearmnn.xhtml#a84f86b4de5adf0b164e811c87051a0ee">CheckFlag</a>(factory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ab17a7eb3afac8667ace153b0fe2f82fe">GetImportFlags</a>(), <a class="code" href="namespacearmnn.xhtml#a0fc99721e27eb20ecd0ea85a3cc8b488a1131a914388fac73e5f07b0ba0aad523">MemorySource::Malloc</a>)) <span class="comment">// Just support cpu mem imports for now</span></div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  {</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <span class="comment">// The current tensor handle factory does not support the map/unmap or import</span></div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="comment">// strategy, move to the next one</span></div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <span class="keywordflow">continue</span>;</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>  <span class="keyword">auto</span> it = factoryScores.find(dst);</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keywordflow">if</span> (it == factoryScores.end())</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  {</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  <span class="comment">// Add new score to the table</span></div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  factoryScores[dst] = 0;</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  <span class="keywordflow">if</span> (topChoice == <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9c95f90eb40e31f629e0e2947b8bc6f9">ITensorHandleFactory::LegacyFactoryId</a>)</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  {</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  topChoice = dst;</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>  }</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  {</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="comment">// Increase the score</span></div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  factoryScores[dst]++;</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span> </div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  <span class="comment">// Track the best option</span></div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  <span class="keywordflow">if</span> (factoryScores[dst] > topScore)</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  {</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  topScore = factoryScores[dst];</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  topChoice = dst;</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  }</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  }</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>  }</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span> </div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <span class="keywordflow">return</span> topChoice;</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> </div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span> <span class="comment">// Find the handle factory for the output layer which results in fewest required copies.</span></div><div class="line"><a name="l00628"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#ab46c7f5f4736d550ab0e5e05a0fff4a9"> 628</a></span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> <a class="code" href="namespacearmnn.xhtml#ab46c7f5f4736d550ab0e5e05a0fff4a9">CalculateSlotOptionForOutput</a>(<a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a>& backends,</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>& slot,</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry)</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>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(backends, slot, registry);</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ac043d9a6e3f861fc6aa057ff95e56f18">ITensorHandleFactory::DeferredFactoryId</a>;</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> </div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span> <span class="comment">// For all handle factories supported on the source backend, we wish to find the one which requires the fewest copies</span></div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span> <span class="comment">// when considering all connections.</span></div><div class="line"><a name="l00638"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a8d9f52bbb69750456acca06988beabda"> 638</a></span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> <a class="code" href="namespacearmnn.xhtml#a8d9f52bbb69750456acca06988beabda">CalculateSlotOption</a>(<a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a>& backends,</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>& outputSlot,</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry)</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span> {</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  <span class="comment">// First ensure the from backends can support the TensorHandeAPI</span></div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& layer = outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7ddaf04177053a536f0e7be83a642bc6">GetOwningLayer</a>();</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <span class="keyword">auto</span> frmBackend = backends.find(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>());</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  <span class="keywordflow">if</span> (frmBackend == backends.end() ||</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  !frmBackend->second->SupportsTensorAllocatorAPI())</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9c95f90eb40e31f629e0e2947b8bc6f9">ITensorHandleFactory::LegacyFactoryId</a>;</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  }</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>  <span class="comment">// Connections to Output Layers requires support for map/unmap on the TensorHandle.</span></div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  <span class="keywordtype">bool</span> requiresMapUnmap = <span class="keyword">false</span>;</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& connection : outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#a50b562d4a4edc64d7d8abcca056f0b8c">GetConnections</a>())</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& connectedLayer = connection->GetOwningLayer();</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <span class="keywordflow">if</span> (connectedLayer.<a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</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>  requiresMapUnmap = <span class="keyword">true</span>;</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"> 661</span> </div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml">IBackendInternal</a>* srcBackend = frmBackend->second.get();</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <span class="keyword">auto</span> srcPrefs = srcBackend-><a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#ac5d107c5672f446603b6e6b92bce6244">GetHandleFactoryPreferences</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>  <span class="comment">// Initialize the scores</span></div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  std::map<ITensorHandleFactory::FactoryId, int> factoryScores;</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& pref : srcPrefs)</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  {</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  <span class="keywordflow">if</span> (requiresMapUnmap) <span class="comment">// Only consider factories that support map/unmap if required</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"> 671</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">ITensorHandleFactory</a>* factory = registry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(pref);</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  <span class="keywordflow">if</span> (!factory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#aa262a54803b53b8198cd60e7af2f60e4">SupportsMapUnmap</a>())</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  {</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  <span class="comment">// The current tensor handle factory does not support the map/unmap strategy, move to the next one</span></div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <span class="keywordflow">continue</span>;</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"> 678</span> </div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  <span class="keyword">auto</span> it = factoryScores.find(pref);</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  <span class="keywordflow">if</span> (it == factoryScores.end())</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  {</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  <span class="comment">// Add new score to the table</span></div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  factoryScores[pref] = 0;</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"> 686</span> </div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  <span class="comment">// Score each handle factory based on how many times it requires copies on the slot connections</span></div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& connection : outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#a50b562d4a4edc64d7d8abcca056f0b8c">GetConnections</a>())</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="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& connectedLayer = connection->GetOwningLayer();</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span> </div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <span class="keyword">auto</span> toBackend = backends.find(connectedLayer.<a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>());</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  BOOST_ASSERT_MSG(toBackend != backends.end(), <span class="stringliteral">"Backend id not found for the connected layer"</span>);</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span> </div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <span class="keyword">auto</span> dstPrefs = toBackend->second.get()->GetHandleFactoryPreferences();</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& src : srcPrefs)</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  {</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  <span class="keywordflow">if</span> (factoryScores.find(src) == factoryScores.end()) <span class="comment">// Don't consider excluded factories</span></div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  {</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <span class="keywordflow">continue</span>;</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> </div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& dst : dstPrefs)</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>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#a5ee4a1cca55f69b31e625c786655ed1a">RequiresCopy</a>(src, dst, registry))</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>  <span class="comment">// Copy avoided, increase the score</span></div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  factoryScores[src]++;</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  }</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>  }</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  }</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">// Find the lowest score</span></div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <span class="keywordtype">int</span> minScore = std::numeric_limits<int>::max();</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : factoryScores)</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>  minScore = std::min(minScore, it.second);</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>  <span class="comment">// Collect factories matching the best(lowest) score</span></div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  std::vector<ITensorHandleFactory::FactoryId> optimalFactories;</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : factoryScores)</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  {</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  <span class="keywordflow">if</span> (it.second == minScore)</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>  optimalFactories.push_back(it.first);</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  }</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> </div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  <span class="comment">// For all compatible Factories matching the best score, find the preferred one for the current layer.</span></div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& srcPref : srcPrefs)</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> (<span class="keyword">auto</span>&& comp : optimalFactories)</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>  <span class="keywordflow">if</span> (comp == srcPref)</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>  <span class="keywordflow">return</span> comp;</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> </div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9c95f90eb40e31f629e0e2947b8bc6f9">ITensorHandleFactory::LegacyFactoryId</a>;</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span> }</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span> </div><div class="line"><a name="l00747"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#ab6ed577caec49def150e231c63af0d12"> 747</a></span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016">EdgeStrategy</a> <a class="code" href="namespacearmnn.xhtml#ab6ed577caec49def150e231c63af0d12">CalculateEdgeStrategy</a>(<a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a>& backends,</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> srcFactoryId,</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& layer,</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& connectedLayer,</div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry)</div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span> {</div><div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  <span class="keyword">auto</span> toBackend = backends.find(connectedLayer.<a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>());</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  BOOST_ASSERT_MSG(toBackend != backends.end(), <span class="stringliteral">"Backend id not found for the connected layer"</span>);</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>  <span class="keyword">auto</span> dstPrefs = toBackend->second.get()->GetHandleFactoryPreferences();</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span> </div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  <span class="comment">// Legacy API check for backward compatibility</span></div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  <span class="keywordflow">if</span> (srcFactoryId == <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9c95f90eb40e31f629e0e2947b8bc6f9">ITensorHandleFactory::LegacyFactoryId</a> || dstPrefs.empty())</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  {</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  <span class="keywordflow">if</span> (layer.<a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() != connectedLayer.<a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>())</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>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016ac366da48cc11956ae377a77751936852">EdgeStrategy::CopyToTarget</a>;</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  }</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  {</div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016a78d1be0baa31e083ae8da99aaedaf650">EdgeStrategy::DirectCompatibility</a>;</div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  }</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> </div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  <span class="comment">// TensorHandleFactory API present, so perform more sophisticated strategies.</span></div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  <span class="comment">// Dst Output layers don't require copy because they use import or map/unmap</span></div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  <span class="keywordflow">if</span> (connectedLayer.<a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</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">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016a78d1be0baa31e083ae8da99aaedaf650">EdgeStrategy::DirectCompatibility</a>;</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  }</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span> </div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  <span class="comment">// Search for direct match in prefs</span></div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& pref : dstPrefs)</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>  <span class="keywordflow">if</span> (pref == srcFactoryId)</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  {</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016a78d1be0baa31e083ae8da99aaedaf650">EdgeStrategy::DirectCompatibility</a>;</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  }</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> </div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  <span class="comment">// Search for export/import options</span></div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">ITensorHandleFactory</a>* srcFactory = registry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(srcFactoryId);</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  <span class="keywordflow">if</span> (srcFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9892b82652ffac03f1e4e7ad93906078">GetExportFlags</a>() != 0)</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  {</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& pref : dstPrefs)</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  {</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">ITensorHandleFactory</a>* dstFactory = registry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(pref);</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>  <span class="comment">// Handles cases when a destPref is not listed in TensorHandleFactoryRegistry</span></div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  <span class="keywordflow">if</span> (!dstFactory) {</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  <span class="keywordflow">continue</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> </div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  <span class="keywordflow">if</span> ((dstFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ab17a7eb3afac8667ace153b0fe2f82fe">GetImportFlags</a>() & srcFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9892b82652ffac03f1e4e7ad93906078">GetExportFlags</a>()) != 0)</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  {</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016a46e8b7bfd6fd3c0cb34a100478a39189">EdgeStrategy::ExportToTarget</a>;</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  }</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  }</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> </div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  <span class="comment">// Search for copy options via map/unmap</span></div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  <span class="keywordflow">if</span> (srcFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#aa262a54803b53b8198cd60e7af2f60e4">SupportsMapUnmap</a>())</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  {</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& pref : dstPrefs)</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>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">ITensorHandleFactory</a>* dstFactory = registry.<a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">GetFactory</a>(pref);</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  <span class="keywordflow">if</span> (dstFactory && dstFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#aa262a54803b53b8198cd60e7af2f60e4">SupportsMapUnmap</a>())</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>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016ac366da48cc11956ae377a77751936852">EdgeStrategy::CopyToTarget</a>;</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  }</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>  }</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>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">EdgeStrategy::Undefined</a>;</div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span> }</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="comment">// Select the TensorHandleFactories and the corresponding memory strategy</span></div><div class="line"><a name="l00824"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a5d3468fb5880eb444cd25b55a86220ff"> 824</a></span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> <a class="code" href="namespacearmnn.xhtml#a5d3468fb5880eb444cd25b55a86220ff">SelectTensorHandleStrategy</a>(<a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& optGraph,</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  <a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a>& backends,</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry,</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</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>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> result;</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>  optGraph.<a class="code" href="classarmnn_1_1_graph.xhtml#ad6521013ad981519904822f2ada2c4ec">ForEachLayer</a>([&backends, &registry, &result, &errMessages](<a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* layer)</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>  BOOST_ASSERT(layer);</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>  <span class="comment">// Lets make sure the backend is in our list of supported backends. Something went wrong during backend</span></div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  <span class="comment">// assignment if this check fails</span></div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  BOOST_ASSERT(backends.find(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>()) != backends.end());</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span> </div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  <span class="comment">// Check each output separately</span></div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> slotIdx = 0; slotIdx < layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a1594bddc87d6477df300317658f566bb">GetNumOutputSlots</a>(); slotIdx++)</div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  {</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>& outputSlot = layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(slotIdx);</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span> </div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> slotOption = <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9c95f90eb40e31f629e0e2947b8bc6f9">ITensorHandleFactory::LegacyFactoryId</a>;</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span> </div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  <span class="comment">// Calculate the factory to use which results in the fewest copies being made.</span></div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  <span class="keywordflow">switch</span>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>())</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  {</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>:</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  slotOption = <a class="code" href="namespacearmnn.xhtml#accb1637c58e1523f740025e0d0e7c6dd">CalculateSlotOptionForInput</a>(backends, outputSlot, registry);</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>:</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  slotOption = <a class="code" href="namespacearmnn.xhtml#ab46c7f5f4736d550ab0e5e05a0fff4a9">CalculateSlotOptionForOutput</a>(backends, outputSlot, registry);</div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  slotOption = <a class="code" href="namespacearmnn.xhtml#a8d9f52bbb69750456acca06988beabda">CalculateSlotOption</a>(backends, outputSlot, registry);</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  }</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#af29f6883785691ef946d0c32b6d2f338">SetTensorHandleFactory</a>(slotOption);</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>  <span class="comment">// Now determine the "best" edge strategy for each connection given the slotOption.</span></div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> connectionIdx = 0;</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& connection : outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#a50b562d4a4edc64d7d8abcca056f0b8c">GetConnections</a>())</div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  {</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& connectedLayer = connection->GetOwningLayer();</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span> </div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016">EdgeStrategy</a> strategy = <a class="code" href="namespacearmnn.xhtml#ab6ed577caec49def150e231c63af0d12">CalculateEdgeStrategy</a>(backends, slotOption, *layer, connectedLayer, registry);</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span> </div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  <span class="keywordflow">if</span> (strategy == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">EdgeStrategy::Undefined</a>)</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>  result.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a41a657cfacb52a80a73575c5c730ab88">m_Error</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  <span class="keywordflow">if</span> (errMessages)</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  {</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  errMessages.value().emplace_back(<span class="stringliteral">"Could not find valid strategy required for compatibility"</span></div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  <span class="stringliteral">" between backends."</span>);</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  }</div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  <span class="keywordflow">return</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>  outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#a3f80ddd1f76ed4ad599e0d1a00659ee5">SetEdgeStrategy</a>(connectionIdx, strategy);</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>  connectionIdx++;</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  }</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  }</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  });</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">return</span> result;</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> </div><div class="line"><a name="l00890"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685"> 890</a></span> <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_network.xhtml">INetwork</a>& inNetwork,</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  <span class="keyword">const</span> std::vector<BackendId>& backendPreferences,</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_device_spec.xhtml">IDeviceSpec</a>& deviceSpec,</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a>& <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a6560146509197f3e197d8d36f76c1347">options</a>,</div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> messages)</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span> {</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  <span class="keywordflow">if</span> (backendPreferences.empty())</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  {</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>(<span class="stringliteral">"Invoked Optimize with no backends specified"</span>);</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_network.xhtml">Network</a>& network = *boost::polymorphic_downcast<const Network*>(&inNetwork);</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  std::unique_ptr<Graph> graph = std::make_unique<Graph>(network.<a class="code" href="classarmnn_1_1_network.xhtml#afe0a4f719f9752a405e71878da7012ba">GetGraph</a>());</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span> </div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  <span class="keyword">auto</span> optNet = <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a>(<span class="keyword">new</span> <a class="code" href="classarmnn_1_1_optimized_network.xhtml">OptimizedNetwork</a>(std::move(graph)), &<a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a58ee539cf95c1e99fe4f54ef6e8bbd05">IOptimizedNetwork::Destroy</a>);</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span> </div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  <a class="code" href="classarmnn_1_1_optimized_network.xhtml">OptimizedNetwork</a>* optNetObjPtr = boost::polymorphic_downcast<OptimizedNetwork*>(optNet.get());</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span> </div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  <span class="comment">// Get the optimized graph</span></div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& optGraph = optNetObjPtr-><a class="code" href="classarmnn_1_1_optimized_network.xhtml#a49800ad35ea869aa5569519760d3b339">GetGraph</a>();</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span> </div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  <span class="comment">// Perform optimisation passes</span></div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  <span class="keyword">using namespace </span>optimizations;</div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">Optimizer::Pass</a>(optGraph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a64ddffb38fbe5b78ec92b753cd4bd0ba">SquashEqualPermuteSiblings</a>(),</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#aba7b0ca6192b8b58ecd517a82b4f378e">SquashEqualTransposeSiblings</a>(),</div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a29f8d97b2d74f99c88298881cd1d825b">SquashEqualReshapeSiblings</a>(),</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#aa31127c77d2117f78d43ca2958dcae19">OptimizeInversePermutes</a>(),</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a2f9d1a13be2ac1c4213729a0ef181fc0">OptimizeInverseTransposes</a>(),</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#aafc70d5af99400ff5ea7991825658b2f">MovePermuteUp</a>(),</div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a5918588fa316cf4c23f1cf02c81ee706">MoveTransposeUp</a>(),</div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#ae0b1382e3af141896a46531c50e8863f">PermuteAsReshape</a>(),</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#ad1aaeee71293f34d9f65d2dd2792830d">TransposeAsReshape</a>(),</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a8341ca3512ebafb19d60eba44d40d9e4">OptimizeConsecutiveReshapes</a>(),</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#add2180a15cdcf5a229de32bb956cb224">FoldPadIntoConvolution2d</a>(),</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a17d1279f5f8e3b92c328b1ed3b6fd549">PermuteAndBatchToSpaceAsDepthToSpace</a>(),</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a98f54d4391347d517c7a7869e7707203">TransposeAndBatchToSpaceAsDepthToSpace</a>()));</div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span> </div><div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  <span class="comment">// Infer the tensor infos for all output slots. Throws an exception on failure</span></div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  optGraph.InferTensorInfos();</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span> </div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  <span class="comment">// If Fp32 to Fp16 optimization is set convert Fp32 network to Fp16</span></div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  <span class="keywordflow">if</span> (options.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a6e1a42622ca43dafc7ba8e684c016eb4">m_ReduceFp32ToFp16</a>)</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  {</div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">Optimizer::Pass</a>(optGraph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a86d19da62b6cfed3928f6fe7026f22fa">Fp32NetworkToFp16Converter</a>()));</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">Optimizer::Pass</a>(optGraph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a226cef3d775179e25ee35d231f4e8fae">ConvertConstantsFloatToHalf</a>()));</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  }</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span> </div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  <span class="comment">// Initialize backend settings</span></div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a> backendSettings(backendPreferences, deviceSpec);</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  <span class="keywordflow">if</span> (backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#ad4ca579528452c669b45f3f35300fd4e">GetAvailablePreferredBackends</a>().empty())</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  {</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  std::stringstream failureMsg;</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  failureMsg << <span class="stringliteral">"None of the preferred backends "</span> << backendPreferences</div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  << <span class="stringliteral">" are supported. Current platform provides "</span> << backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#a0b160952af61b24d88125d66ed6d43c1">m_SupportedBackends</a>;</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  <a class="code" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994">ReportError</a>(failureMsg.str(), messages);</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a>(<span class="keyword">nullptr</span>, &<a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a58ee539cf95c1e99fe4f54ef6e8bbd05">IOptimizedNetwork::Destroy</a>);</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>  <span class="comment">// Create a map to temporarily hold initialized backend objects</span></div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a> tensorHandleFactoryRegistry;</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  <a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a> backends = <a class="code" href="namespacearmnn.xhtml#a1ec6b4c20ed294a96cf94c33c24caaf5">CreateSupportedBackends</a>(tensorHandleFactoryRegistry, backendSettings);</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span> </div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  <span class="comment">// Assign an available backend to each layer</span></div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a> firstLayer = optGraph.begin();</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a> lastLayer = optGraph.end();</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> assignBackendsResult = <a class="code" href="namespacearmnn.xhtml#a8acab870a91373c720c9822b59ecf3b8">AssignBackends</a>(optNetObjPtr,</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  backendSettings,</div><div class="line"><a name="l00957"></a><span class="lineno"> 957</span>  firstLayer,</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  lastLayer,</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  messages);</div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  <span class="keywordflow">if</span> (assignBackendsResult.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a41a657cfacb52a80a73575c5c730ab88">m_Error</a>)</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  {</div><div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  <span class="comment">// Failed to assign a backend to each layer</span></div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a>(<span class="keyword">nullptr</span>, &<a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a58ee539cf95c1e99fe4f54ef6e8bbd05">IOptimizedNetwork::Destroy</a>);</div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  }</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>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">Optimizer::Pass</a>(optGraph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a1a9d718b48612b5817a3c369f9fd71ee">OptimizeInverseConversionsFp16</a>(),</div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#ae1509d340bc981b11101c3316ee8afd6">OptimizeInverseConversionsFp32</a>()));</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="comment">// Apply the backend-specific optimizations</span></div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> backendOptimizationResult = <a class="code" href="namespacearmnn.xhtml#ae97734279fd10b4c754cc15bc8ed9dad">ApplyBackendOptimizations</a>(optNetObjPtr,</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  backendSettings,</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  backends,</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  messages);</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  <span class="keywordflow">if</span> (backendOptimizationResult.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a41a657cfacb52a80a73575c5c730ab88">m_Error</a>)</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="comment">// Failed to apply the backend-specific optimizations</span></div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a>(<span class="keyword">nullptr</span>, &<a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a58ee539cf95c1e99fe4f54ef6e8bbd05">IOptimizedNetwork::Destroy</a>);</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  }</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="comment">// If the debug flag is set, then insert a DebugLayer after each layer</span></div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  <span class="comment">// Doing this after applying the backend optimizations as they might have changed some layers</span></div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  <span class="keywordflow">if</span> (options.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a69eb14082d40fa0a3cff50457344a5e0">m_Debug</a>)</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>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">Optimizer::Pass</a>(optGraph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#aa76c76565125ad77092403176d74fd85">InsertDebugLayer</a>()));</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  }</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span> </div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  <span class="comment">// Calculate the compatibility strategies for tensor handles</span></div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> strategyResult = <a class="code" href="namespacearmnn.xhtml#a5d3468fb5880eb444cd25b55a86220ff">SelectTensorHandleStrategy</a>(optGraph,</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  backends,</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  tensorHandleFactoryRegistry,</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  messages);</div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  <span class="keywordflow">if</span> (strategyResult.<a class="code" href="structarmnn_1_1_optimization_result.xhtml#a41a657cfacb52a80a73575c5c730ab88">m_Error</a>)</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>  <span class="comment">// Failed to apply the backend-specific optimizations</span></div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a>(<span class="keyword">nullptr</span>, &<a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a58ee539cf95c1e99fe4f54ef6e8bbd05">IOptimizedNetwork::Destroy</a>);</div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span>  }</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span> </div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  <span class="comment">// Based on the tensor handle strategy determined above, insert copy layers where required.</span></div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span>  optGraph.AddCompatibilityLayers(backends, tensorHandleFactoryRegistry);</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span> </div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>  <span class="comment">// Convert constants</span></div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">Optimizer::Pass</a>(optGraph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a226cef3d775179e25ee35d231f4e8fae">ConvertConstantsFloatToHalf</a>()));</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">Optimizer::Pass</a>(optGraph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a06cac66872538895dd6b59cdf39173d2">ConvertConstantsHalfToFloat</a>()));</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>  <span class="comment">// Run backend specific optimizations (deprecated)</span></div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& chosenBackend : backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#aa09ac75b83067c5ed455f2bb35c7c98d">m_SelectedBackends</a>)</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="keyword">auto</span> factoryFun = <a class="code" href="namespacearmnn.xhtml#ac2807505b850738bc8a1991ce669dd47">BackendRegistryInstance</a>().<a class="code" href="classarmnn_1_1_backend_registry.xhtml#afc0c63ca8db8957b58826f6d7bd231b2">GetFactory</a>(chosenBackend);</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  <span class="keyword">auto</span> backendPtr = factoryFun();</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>  BOOST_ASSERT(backendPtr.get() != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span> </div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  <a class="code" href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  <span class="keyword">auto</span> backendSpecificOptimizations = backendPtr->GetOptimizations();</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  <a class="code" href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></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>  <span class="keywordflow">if</span> (!backendSpecificOptimizations.empty())</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  {</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">Optimizer::Pass</a>(optNetObjPtr-><a class="code" href="classarmnn_1_1_optimized_network.xhtml#a49800ad35ea869aa5569519760d3b339">GetGraph</a>(), backendSpecificOptimizations);</div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  }</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> </div><div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>  <span class="keywordflow">return</span> optNet;</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> </div><div class="line"><a name="l01025"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a5f56923e4eac55c8c08d72599b0a0d41"> 1025</a></span> <a class="code" href="classarmnn_1_1_network.xhtml#a5f56923e4eac55c8c08d72599b0a0d41">Network::Network</a>()</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span> : m_Graph(<a class="code" href="namespacestd.xhtml">std</a>::make_unique<<a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>>()),</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  m_Guid(profiling::<a class="code" href="classarmnn_1_1profiling_1_1_profiling_service.xhtml">ProfilingService</a>::Instance().NextGuid())</div><div class="line"><a name="l01028"></a><span class="lineno"> 1028</span> {</div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span> }</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span> </div><div class="line"><a name="l01031"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#ac9062f3da8a725626fd7e7bd27449220"> 1031</a></span> <a class="code" href="classarmnn_1_1_network.xhtml#ac9062f3da8a725626fd7e7bd27449220">Network::~Network</a>()</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span> {</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"><a class="line" href="classarmnn_1_1_network.xhtml#a9aa1b214fcaec2371fe4226bd126fb73"> 1035</a></span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_network.xhtml#a9aa1b214fcaec2371fe4226bd126fb73">Network::PrintGraph</a>()</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>  m_Graph->Print();</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">Status::Success</a>;</div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span> }</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span> </div><div class="line"><a name="l01041"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a90d8841cfbbc82ab02328f33fed24ac6"> 1041</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a90d8841cfbbc82ab02328f33fed24ac6">Network::AddInputLayer</a>(<a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> <span class="keywordtype">id</span>, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span> {</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(id, name);</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> </div><div class="line"><a name="l01046"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a1a3c9903dcd90a7f40d8aca0c339501f"> 1046</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a1a3c9903dcd90a7f40d8aca0c339501f">Network::AddBatchToSpaceNdLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">BatchToSpaceNdDescriptor</a>& batchToSpaceNdDescriptor,</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_batch_to_space_nd_layer.xhtml">BatchToSpaceNdLayer</a>>(batchToSpaceNdDescriptor, name);</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span> }</div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</span> </div><div class="line"><a name="l01052"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a52fab7cec34e1fa77df68503e0c0ce59"> 1052</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a52fab7cec34e1fa77df68503e0c0ce59">Network::AddComparisonLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_comparison_descriptor.xhtml">ComparisonDescriptor</a>& comparisonDescriptor,</div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span> {</div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_comparison_layer.xhtml">ComparisonLayer</a>>(comparisonDescriptor, name);</div><div class="line"><a name="l01056"></a><span class="lineno"> 1056</span> }</div><div class="line"><a name="l01057"></a><span class="lineno"> 1057</span> </div><div class="line"><a name="l01058"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a99093f440e7e0ba4c8dcc90c3ec8cf4d"> 1058</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a99093f440e7e0ba4c8dcc90c3ec8cf4d">Network::AddElementwiseUnaryLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.xhtml">ElementwiseUnaryDescriptor</a>& elementwiseUnaryDescriptor,</div><div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01060"></a><span class="lineno"> 1060</span> {</div><div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_elementwise_unary_layer.xhtml">ElementwiseUnaryLayer</a>>(elementwiseUnaryDescriptor, name);</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> </div><div class="line"><a name="l01064"></a><span class="lineno"> 1064</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* Network::AddFullyConnectedLayerImpl(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">FullyConnectedDescriptor</a>& fullyConnectedDescriptor,</div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a>& biases,</div><div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span> {</div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>  <span class="keywordflow">if</span> (fullyConnectedDescriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> && !biases.<a class="code" href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">has_value</a>())</div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>  {</div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddFullyConnectedLayer: biases cannot be empty"</span>);</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> </div><div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml">FullyConnectedLayer</a>>(fullyConnectedDescriptor, name);</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>  layer-><a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l01077"></a><span class="lineno"> 1077</span> </div><div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>  <span class="keywordflow">if</span> (fullyConnectedDescriptor.m_BiasEnabled)</div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>  {</div><div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>  layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>());</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="keywordflow">return</span> layer;</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> </div><div class="line"><a name="l01086"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a80dc86e975ff991ef63aa8b523d4fcdf"> 1086</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a80dc86e975ff991ef63aa8b523d4fcdf">Network::AddFullyConnectedLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">FullyConnectedDescriptor</a>& fullyConnectedDescriptor,</div><div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a>& biases,</div><div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01090"></a><span class="lineno"> 1090</span> {</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>  <span class="keywordflow">return</span> AddFullyConnectedLayerImpl(fullyConnectedDescriptor, weights, biases, name);</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> </div><div class="line"><a name="l01094"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a65835b534db6a10d91e2096952fcf7d7"> 1094</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a80dc86e975ff991ef63aa8b523d4fcdf">Network::AddFullyConnectedLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">FullyConnectedDescriptor</a>& fullyConnectedDescriptor,</div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span> {</div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> biases;</div><div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>  <span class="keywordflow">return</span> AddFullyConnectedLayerImpl(fullyConnectedDescriptor, weights, biases, name);</div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span> }</div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</span> </div><div class="line"><a name="l01102"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a1d28c2b5a3c3c73eb3c4f9f6112bde94"> 1102</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a80dc86e975ff991ef63aa8b523d4fcdf">Network::AddFullyConnectedLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">FullyConnectedDescriptor</a>& fullyConnectedDescriptor,</div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& biases,</div><div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01106"></a><span class="lineno"> 1106</span> {</div><div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> optionalBiases(biases);</div><div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>  <span class="keywordflow">return</span> AddFullyConnectedLayerImpl(fullyConnectedDescriptor, weights, optionalBiases, name);</div><div class="line"><a name="l01109"></a><span class="lineno"> 1109</span> }</div><div class="line"><a name="l01110"></a><span class="lineno"> 1110</span> </div><div class="line"><a name="l01111"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a7b0396c132c4da95e80b210f9b6734e9"> 1111</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a7b0396c132c4da95e80b210f9b6734e9">Network::AddConcatLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_origins_descriptor.xhtml">ConcatDescriptor</a>& concatDescriptor,</div><div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01113"></a><span class="lineno"> 1113</span> {</div><div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_concat_layer.xhtml">ConcatLayer</a>>(concatDescriptor, name);</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> </div><div class="line"><a name="l01117"></a><span class="lineno"> 1117</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* Network::AddConvolution2dLayerImpl(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a>& convolution2dDescriptor,</div><div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a>& biases,</div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01121"></a><span class="lineno"> 1121</span> {</div><div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>  <span class="keywordflow">if</span> (convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> && !biases.<a class="code" href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">has_value</a>())</div><div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>  {</div><div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddConvolution2dLayer: biases cannot be empty"</span>);</div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  }</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span> </div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">Convolution2dLayer</a>>(convolution2dDescriptor, name);</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>  layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span> </div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>  <span class="keywordflow">if</span> (convolution2dDescriptor.m_BiasEnabled)</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>  layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>());</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>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l01137"></a><span class="lineno"> 1137</span> }</div><div class="line"><a name="l01138"></a><span class="lineno"> 1138</span> </div><div class="line"><a name="l01139"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a865189c08aa64d448d05efc92a43725a"> 1139</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a865189c08aa64d448d05efc92a43725a">Network::AddConvolution2dLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a>& convolution2dDescriptor,</div><div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a>& biases,</div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span> {</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>  <span class="keywordflow">return</span> AddConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span> }</div><div class="line"><a name="l01146"></a><span class="lineno"> 1146</span> </div><div class="line"><a name="l01147"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a672c0f6fdd479311818f7efbac694042"> 1147</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a865189c08aa64d448d05efc92a43725a">Network::AddConvolution2dLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a>& convolution2dDescriptor,</div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> biases;</div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>  <span class="keywordflow">return</span> AddConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name);</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> </div><div class="line"><a name="l01155"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a1100ef86ba46e5c43aff78db7a82f049"> 1155</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a865189c08aa64d448d05efc92a43725a">Network::AddConvolution2dLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a>& convolution2dDescriptor,</div><div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& biases,</div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01159"></a><span class="lineno"> 1159</span> {</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> optionalBiases(biases);</div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  <span class="keywordflow">return</span> AddConvolution2dLayerImpl(convolution2dDescriptor, weights, optionalBiases, name);</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> </div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* Network::AddDepthwiseConvolution2dLayerImpl(</div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a>& convolution2dDescriptor,</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a>& biases,</div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span> {</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>  <span class="keywordflow">if</span> (convolution2dDescriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> && !biases.<a class="code" href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">has_value</a>())</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>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddDepthwiseConvolution2dLayer: biases cannot be empty"</span>);</div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>  }</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span> </div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">DepthwiseConvolution2dLayer</a>>(convolution2dDescriptor, name);</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>  layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l01178"></a><span class="lineno"> 1178</span> </div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>  <span class="keywordflow">if</span> (convolution2dDescriptor.m_BiasEnabled)</div><div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  {</div><div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>  layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>());</div><div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>  }</div><div class="line"><a name="l01183"></a><span class="lineno"> 1183</span> </div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span> }</div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span> </div><div class="line"><a name="l01187"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a59e55a0755a655a809520738c697334f"> 1187</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a59e55a0755a655a809520738c697334f">Network::AddDepthToSpaceLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml">DepthToSpaceDescriptor</a>& depthToSpaceDescriptor,</div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01189"></a><span class="lineno"> 1189</span> {</div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_depth_to_space_layer.xhtml">DepthToSpaceLayer</a>>(depthToSpaceDescriptor, name);</div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</span> }</div><div class="line"><a name="l01192"></a><span class="lineno"> 1192</span> </div><div class="line"><a name="l01193"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a1add5219a64f4249a282f52202828451"> 1193</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a1add5219a64f4249a282f52202828451">Network::AddDepthwiseConvolution2dLayer</a>(</div><div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a>& convolution2dDescriptor,</div><div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a>& biases,</div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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="keywordflow">return</span> AddDepthwiseConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l01200"></a><span class="lineno"> 1200</span> }</div><div class="line"><a name="l01201"></a><span class="lineno"> 1201</span> </div><div class="line"><a name="l01202"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#ab192233990fa6525e30cfbe5a4701e2a"> 1202</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a1add5219a64f4249a282f52202828451">Network::AddDepthwiseConvolution2dLayer</a>(</div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a>& convolution2dDescriptor,</div><div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01206"></a><span class="lineno"> 1206</span> {</div><div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> biases;</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>  <span class="keywordflow">return</span> AddDepthwiseConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</span> }</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span> </div><div class="line"><a name="l01211"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a37b53840117ba4159bd7c033bd18d281"> 1211</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a1add5219a64f4249a282f52202828451">Network::AddDepthwiseConvolution2dLayer</a>(</div><div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a>& convolution2dDescriptor,</div><div class="line"><a name="l01213"></a><span class="lineno"> 1213</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& biases,</div><div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01216"></a><span class="lineno"> 1216</span> {</div><div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> optionalBiases(biases);</div><div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>  <span class="keywordflow">return</span> AddDepthwiseConvolution2dLayerImpl(convolution2dDescriptor, weights, optionalBiases, name);</div><div class="line"><a name="l01219"></a><span class="lineno"> 1219</span> }</div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span> </div><div class="line"><a name="l01221"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a52cc1e062595108da0dfef4b200dabd7"> 1221</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a52cc1e062595108da0dfef4b200dabd7">Network::AddDetectionPostProcessLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a>& descriptor,</div><div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01223"></a><span class="lineno"> 1223</span> {</div><div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_detection_post_process_layer.xhtml">DetectionPostProcessLayer</a>>(descriptor, name);</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>  layer-><a class="code" href="classarmnn_1_1_detection_post_process_layer.xhtml#a6844fecab0edaf324de5a57fee8b65f1">m_Anchors</a> = std::make_unique<ScopedCpuTensorHandle>(<a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>);</div><div class="line"><a name="l01227"></a><span class="lineno"> 1227</span> </div><div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l01229"></a><span class="lineno"> 1229</span> }</div><div class="line"><a name="l01230"></a><span class="lineno"> 1230</span> </div><div class="line"><a name="l01231"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#aff9921f194908a3c35015de701723234"> 1231</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#aff9921f194908a3c35015de701723234">Network::AddPermuteLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_permute_descriptor.xhtml">PermuteDescriptor</a>& permuteDescriptor,</div><div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01233"></a><span class="lineno"> 1233</span> {</div><div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_permute_layer.xhtml">PermuteLayer</a>>(permuteDescriptor, name);</div><div class="line"><a name="l01235"></a><span class="lineno"> 1235</span> }</div><div class="line"><a name="l01236"></a><span class="lineno"> 1236</span> </div><div class="line"><a name="l01237"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#ab8b4e22c47ae0b0f259de353e760a4bf"> 1237</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#ab8b4e22c47ae0b0f259de353e760a4bf">Network::AddPooling2dLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">Pooling2dDescriptor</a>& pooling2dDescriptor,</div><div class="line"><a name="l01238"></a><span class="lineno"> 1238</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01239"></a><span class="lineno"> 1239</span> {</div><div class="line"><a name="l01240"></a><span class="lineno"> 1240</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_pooling2d_layer.xhtml">Pooling2dLayer</a>>(pooling2dDescriptor, name);</div><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span> }</div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span> </div><div class="line"><a name="l01243"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a36a40a1209689f39a5a283209991da3c"> 1243</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a36a40a1209689f39a5a283209991da3c">Network::AddActivationLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">ActivationDescriptor</a>& activationDescriptor,</div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01245"></a><span class="lineno"> 1245</span> {</div><div class="line"><a name="l01246"></a><span class="lineno"> 1246</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_activation_layer.xhtml">ActivationLayer</a>>(activationDescriptor, name);</div><div class="line"><a name="l01247"></a><span class="lineno"> 1247</span> }</div><div class="line"><a name="l01248"></a><span class="lineno"> 1248</span> </div><div class="line"><a name="l01249"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a40d7cd9d061c23405392f7c513849a2f"> 1249</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a40d7cd9d061c23405392f7c513849a2f">Network::AddArgMinMaxLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">ArgMinMaxDescriptor</a>& argMinMaxDescriptor,</div><div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01251"></a><span class="lineno"> 1251</span> {</div><div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_arg_min_max_layer.xhtml">ArgMinMaxLayer</a>>(argMinMaxDescriptor, name);</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> </div><div class="line"><a name="l01255"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a942922c1213c451e3286fb5cd31c6499"> 1255</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a942922c1213c451e3286fb5cd31c6499">Network::AddNormalizationLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml">NormalizationDescriptor</a>&</div><div class="line"><a name="l01256"></a><span class="lineno"> 1256</span> normalizationDescriptor,</div><div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01258"></a><span class="lineno"> 1258</span> {</div><div class="line"><a name="l01259"></a><span class="lineno"> 1259</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_normalization_layer.xhtml">NormalizationLayer</a>>(normalizationDescriptor, name);</div><div class="line"><a name="l01260"></a><span class="lineno"> 1260</span> }</div><div class="line"><a name="l01261"></a><span class="lineno"> 1261</span> </div><div class="line"><a name="l01262"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#ad445d732cda17f0a552fa916f59fed8d"> 1262</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#ad445d732cda17f0a552fa916f59fed8d">Network::AddSliceLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_slice_descriptor.xhtml">SliceDescriptor</a>& sliceDescriptor, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01263"></a><span class="lineno"> 1263</span> {</div><div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_slice_layer.xhtml">SliceLayer</a>>(sliceDescriptor, name);</div><div class="line"><a name="l01265"></a><span class="lineno"> 1265</span> }</div><div class="line"><a name="l01266"></a><span class="lineno"> 1266</span> </div><div class="line"><a name="l01267"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a8b1fbac089170c35fcb98d7012859428"> 1267</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a8b1fbac089170c35fcb98d7012859428">Network::AddSoftmaxLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml">SoftmaxDescriptor</a>& softmaxDescriptor,</div><div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_softmax_layer.xhtml">SoftmaxLayer</a>>(softmaxDescriptor, name);</div><div class="line"><a name="l01271"></a><span class="lineno"> 1271</span> }</div><div class="line"><a name="l01272"></a><span class="lineno"> 1272</span> </div><div class="line"><a name="l01273"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#acb8e86be339d57b32f0ba3d9293c880b"> 1273</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#acb8e86be339d57b32f0ba3d9293c880b">Network::AddSplitterLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_views_descriptor.xhtml">ViewsDescriptor</a>& splitterDescriptor,</div><div class="line"><a name="l01274"></a><span class="lineno"> 1274</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01275"></a><span class="lineno"> 1275</span> {</div><div class="line"><a name="l01276"></a><span class="lineno"> 1276</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_splitter_layer.xhtml">SplitterLayer</a>>(splitterDescriptor, name);</div><div class="line"><a name="l01277"></a><span class="lineno"> 1277</span> }</div><div class="line"><a name="l01278"></a><span class="lineno"> 1278</span> </div><div class="line"><a name="l01279"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a10c7356df73267c2acf3248465d5954b"> 1279</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a10c7356df73267c2acf3248465d5954b">Network::AddMaximumLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01280"></a><span class="lineno"> 1280</span> {</div><div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_maximum_layer.xhtml">MaximumLayer</a>>(name);</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"><a class="line" href="classarmnn_1_1_network.xhtml#add39cd8a51e34c532fb56cf313703844"> 1284</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#add39cd8a51e34c532fb56cf313703844">Network::AddMinimumLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_minimum_layer.xhtml">MinimumLayer</a>>(name);</div><div class="line"><a name="l01287"></a><span class="lineno"> 1287</span> }</div><div class="line"><a name="l01288"></a><span class="lineno"> 1288</span> </div><div class="line"><a name="l01289"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#ac9758a0b2749095fd2a7ac152ff8fd49"> 1289</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#ac9758a0b2749095fd2a7ac152ff8fd49">Network::AddMergerLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_origins_descriptor.xhtml">MergerDescriptor</a>& mergerDescriptor,</div><div class="line"><a name="l01290"></a><span class="lineno"> 1290</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01291"></a><span class="lineno"> 1291</span> {</div><div class="line"><a name="l01292"></a><span class="lineno"> 1292</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network.xhtml#a7b0396c132c4da95e80b210f9b6734e9">AddConcatLayer</a>(mergerDescriptor, name);</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> </div><div class="line"><a name="l01295"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#abf67dfbce354d772111fc5e5d4cd850d"> 1295</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#abf67dfbce354d772111fc5e5d4cd850d">Network::AddAbsLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span> * name)</div><div class="line"><a name="l01296"></a><span class="lineno"> 1296</span> {</div><div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network.xhtml#a99093f440e7e0ba4c8dcc90c3ec8cf4d">AddElementwiseUnaryLayer</a>(<a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.xhtml">ElementwiseUnaryDescriptor</a>(<a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">UnaryOperation::Abs</a>), name);</div><div class="line"><a name="l01298"></a><span class="lineno"> 1298</span> }</div><div class="line"><a name="l01299"></a><span class="lineno"> 1299</span> </div><div class="line"><a name="l01300"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#adb60c75544796e23d7abc1ce0476f6d9"> 1300</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#adb60c75544796e23d7abc1ce0476f6d9">Network::AddAdditionLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01301"></a><span class="lineno"> 1301</span> {</div><div class="line"><a name="l01302"></a><span class="lineno"> 1302</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>>(name);</div><div class="line"><a name="l01303"></a><span class="lineno"> 1303</span> }</div><div class="line"><a name="l01304"></a><span class="lineno"> 1304</span> </div><div class="line"><a name="l01305"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a6e6cb8fd00cb855c4f0d93c4a7a2bde2"> 1305</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a6e6cb8fd00cb855c4f0d93c4a7a2bde2">Network::AddMultiplicationLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01306"></a><span class="lineno"> 1306</span> {</div><div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>>(name);</div><div class="line"><a name="l01308"></a><span class="lineno"> 1308</span> }</div><div class="line"><a name="l01309"></a><span class="lineno"> 1309</span> </div><div class="line"><a name="l01310"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#ad55ff20f4c7e60c18b849e61f28f0e2e"> 1310</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#ad55ff20f4c7e60c18b849e61f28f0e2e">Network::AddOutputLayer</a>(<a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> <span class="keywordtype">id</span>, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01311"></a><span class="lineno"> 1311</span> {</div><div class="line"><a name="l01312"></a><span class="lineno"> 1312</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(id, name);</div><div class="line"><a name="l01313"></a><span class="lineno"> 1313</span> }</div><div class="line"><a name="l01314"></a><span class="lineno"> 1314</span> </div><div class="line"><a name="l01315"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#abd4965a5d1d28a91b975e6b0eef024c8"> 1315</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#abd4965a5d1d28a91b975e6b0eef024c8">Network::AddBatchNormalizationLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml">BatchNormalizationDescriptor</a>& desc,</div><div class="line"><a name="l01316"></a><span class="lineno"> 1316</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& mean,</div><div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& variance,</div><div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& beta,</div><div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& gamma,</div><div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01321"></a><span class="lineno"> 1321</span> {</div><div class="line"><a name="l01322"></a><span class="lineno"> 1322</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml">BatchNormalizationLayer</a>>(desc, name);</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>  layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#a3540afac8fad99bbe68b3f7b57590160">m_Mean</a> = std::make_unique<ScopedCpuTensorHandle>(mean);</div><div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>  layer->m_Variance = std::make_unique<ScopedCpuTensorHandle>(variance);</div><div class="line"><a name="l01326"></a><span class="lineno"> 1326</span>  layer->m_Beta = std::make_unique<ScopedCpuTensorHandle>(beta);</div><div class="line"><a name="l01327"></a><span class="lineno"> 1327</span>  layer->m_Gamma = std::make_unique<ScopedCpuTensorHandle>(gamma);</div><div class="line"><a name="l01328"></a><span class="lineno"> 1328</span> </div><div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>  <span class="keywordflow">return</span> layer;</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> </div><div class="line"><a name="l01332"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#acae7df585b6c920cecd8065f0e16ff9b"> 1332</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#acae7df585b6c920cecd8065f0e16ff9b">Network::AddResizeBilinearLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml">ResizeBilinearDescriptor</a>& descriptor,</div><div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01334"></a><span class="lineno"> 1334</span> {</div><div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">ResizeDescriptor</a> resizeDescriptor;</div><div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>  resizeDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a869254cb56968986a78a79e1d6d4a86b">m_Method</a> = <a class="code" href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">ResizeMethod::Bilinear</a>;</div><div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>  resizeDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = descriptor.<a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>;</div><div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>  resizeDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a>;</div><div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>  resizeDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = descriptor.<a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a>;</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="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_resize_layer.xhtml">ResizeLayer</a>>(resizeDescriptor, name);</div><div class="line"><a name="l01342"></a><span class="lineno"> 1342</span> }</div><div class="line"><a name="l01343"></a><span class="lineno"> 1343</span> </div><div class="line"><a name="l01344"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#aa1ee88eebe67898c50a4ca259de49bbc"> 1344</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#aa1ee88eebe67898c50a4ca259de49bbc">Network::AddResizeLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">ResizeDescriptor</a>&</div><div class="line"><a name="l01345"></a><span class="lineno"> 1345</span> resizeDescriptor, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01346"></a><span class="lineno"> 1346</span> {</div><div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_resize_layer.xhtml">ResizeLayer</a>>(resizeDescriptor, name);</div><div class="line"><a name="l01348"></a><span class="lineno"> 1348</span> }</div><div class="line"><a name="l01349"></a><span class="lineno"> 1349</span> </div><div class="line"><a name="l01350"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a98fef92a93b7a51ce6755dae02bb0cd4"> 1350</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a98fef92a93b7a51ce6755dae02bb0cd4">Network::AddInstanceNormalizationLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml">InstanceNormalizationDescriptor</a>& desc,</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01352"></a><span class="lineno"> 1352</span> {</div><div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_instance_normalization_layer.xhtml">InstanceNormalizationLayer</a>>(desc, name);</div><div class="line"><a name="l01354"></a><span class="lineno"> 1354</span> }</div><div class="line"><a name="l01355"></a><span class="lineno"> 1355</span> </div><div class="line"><a name="l01356"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#acce5b3272c9da9cb4201b437dd96a729"> 1356</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#acce5b3272c9da9cb4201b437dd96a729">Network::AddL2NormalizationLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_l2_normalization_descriptor.xhtml">L2NormalizationDescriptor</a>& desc,</div><div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01358"></a><span class="lineno"> 1358</span> {</div><div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_l2_normalization_layer.xhtml">L2NormalizationLayer</a>>(desc, name);</div><div class="line"><a name="l01360"></a><span class="lineno"> 1360</span> }</div><div class="line"><a name="l01361"></a><span class="lineno"> 1361</span> </div><div class="line"><a name="l01362"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a4c47466a95f61c321f525b06fc87b2c5"> 1362</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a4c47466a95f61c321f525b06fc87b2c5">Network::AddLogSoftmaxLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml">LogSoftmaxDescriptor</a>& desc,</div><div class="line"><a name="l01363"></a><span class="lineno"> 1363</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01364"></a><span class="lineno"> 1364</span> {</div><div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_log_softmax_layer.xhtml">LogSoftmaxLayer</a>>(desc, name);</div><div class="line"><a name="l01366"></a><span class="lineno"> 1366</span> }</div><div class="line"><a name="l01367"></a><span class="lineno"> 1367</span> </div><div class="line"><a name="l01368"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a8b2e7eb34ad5aacda72260f77fd880ce"> 1368</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a8b2e7eb34ad5aacda72260f77fd880ce">Network::AddConstantLayer</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& input, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01369"></a><span class="lineno"> 1369</span> {</div><div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>  <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_constant_layer.xhtml">ConstantLayer</a>>(name);</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>  layer-><a class="code" href="classarmnn_1_1_constant_layer.xhtml#a67ccc257eeefce0964c1cafc4b255c9f">m_LayerOutput</a> = std::make_unique<ScopedCpuTensorHandle>(input);</div><div class="line"><a name="l01373"></a><span class="lineno"> 1373</span> </div><div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l01375"></a><span class="lineno"> 1375</span> }</div><div class="line"><a name="l01376"></a><span class="lineno"> 1376</span> </div><div class="line"><a name="l01377"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a09774b1c2b882e1d573dc507479805b6"> 1377</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a09774b1c2b882e1d573dc507479805b6">Network::AddReshapeLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_reshape_descriptor.xhtml">ReshapeDescriptor</a>& reshapeDescriptor,</div><div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_reshape_layer.xhtml">ReshapeLayer</a>>(reshapeDescriptor, name);</div><div class="line"><a name="l01381"></a><span class="lineno"> 1381</span> }</div><div class="line"><a name="l01382"></a><span class="lineno"> 1382</span> </div><div class="line"><a name="l01383"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a9e234ae3b84213cb9fce636cfc2302bb"> 1383</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a9e234ae3b84213cb9fce636cfc2302bb">Network::AddSpaceToBatchNdLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml">SpaceToBatchNdDescriptor</a>& spaceToBatchNdDescriptor,</div><div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_space_to_batch_nd_layer.xhtml">SpaceToBatchNdLayer</a>>(spaceToBatchNdDescriptor, name);</div><div class="line"><a name="l01387"></a><span class="lineno"> 1387</span> }</div><div class="line"><a name="l01388"></a><span class="lineno"> 1388</span> </div><div class="line"><a name="l01389"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#afa43cbc86ae43ce6ee468347b30229c4"> 1389</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#afa43cbc86ae43ce6ee468347b30229c4">Network::AddSpaceToDepthLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml">SpaceToDepthDescriptor</a>& spaceToDepthDescriptor,</div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_space_to_depth_layer.xhtml">SpaceToDepthLayer</a>>(spaceToDepthDescriptor, name);</div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span> }</div><div class="line"><a name="l01394"></a><span class="lineno"> 1394</span> </div><div class="line"><a name="l01395"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a7b9879b0da1f561d10e4f5c545028143"> 1395</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a7b9879b0da1f561d10e4f5c545028143">Network::AddFloorLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01396"></a><span class="lineno"> 1396</span> {</div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_floor_layer.xhtml">FloorLayer</a>>(name);</div><div class="line"><a name="l01398"></a><span class="lineno"> 1398</span> }</div><div class="line"><a name="l01399"></a><span class="lineno"> 1399</span> </div><div class="line"><a name="l01400"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#ab1569dbf88b6511bde91bee3224a558c"> 1400</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#ab1569dbf88b6511bde91bee3224a558c">Network::AddLstmLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml">LstmDescriptor</a>& descriptor,</div><div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_lstm_input_params.xhtml">LstmInputParams</a>& params,</div><div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01403"></a><span class="lineno"> 1403</span> {</div><div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_lstm_layer.xhtml">LstmLayer</a>>(descriptor, name);</div><div class="line"><a name="l01405"></a><span class="lineno"> 1405</span> </div><div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>  <span class="comment">//Lstm Basic Parameters</span></div><div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>  layer-><a class="code" href="classarmnn_1_1_lstm_layer.xhtml#a8838b317568861294a9df608221f185e">m_BasicParameters</a>.<a class="code" href="structarmnn_1_1_lstm_basic_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">m_InputToForgetWeights</a> =</div><div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a>));</div><div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>  layer->m_BasicParameters.m_InputToCellWeights =</div><div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a>));</div><div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>  layer->m_BasicParameters.m_InputToOutputWeights =</div><div class="line"><a name="l01412"></a><span class="lineno"> 1412</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a>));</div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>  layer->m_BasicParameters.m_RecurrentToForgetWeights =</div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a>));</div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>  layer->m_BasicParameters.m_RecurrentToCellWeights =</div><div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a>));</div><div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>  layer->m_BasicParameters.m_RecurrentToOutputWeights =</div><div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a>));</div><div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>  layer->m_BasicParameters.m_ForgetGateBias =</div><div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a>));</div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>  layer->m_BasicParameters.m_CellBias =</div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a>));</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>  layer->m_BasicParameters.m_OutputGateBias =</div><div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a>));</div><div class="line"><a name="l01425"></a><span class="lineno"> 1425</span> </div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>  <span class="comment">//Lstm Cifg parameters</span></div><div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>  <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div><div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>  {</div><div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> == <span class="keyword">nullptr</span>)</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>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddLstmLayer: Input To Input Weights cannot be NULL"</span>);</div><div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>  }</div><div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> == <span class="keyword">nullptr</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="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(</div><div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>  <span class="stringliteral">"AddLstmLayer: Recurrent To Input Weights cannot be NULL"</span>);</div><div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>  }</div><div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l01439"></a><span class="lineno"> 1439</span>  {</div><div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddLstmLayer: Input Gate Bias cannot be NULL"</span>);</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>  layer->m_CifgParameters.m_InputToInputWeights =</div><div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a>));</div><div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>  layer->m_CifgParameters.m_RecurrentToInputWeights =</div><div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a>));</div><div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>  <span class="comment">// In the VTS tests, cell-to-input weights may be null, even if the other CIFG params are not.</span></div><div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>  {</div><div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>  layer->m_CifgParameters.m_CellToInputWeights =</div><div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a>));</div><div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>  }</div><div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>  layer->m_CifgParameters.m_InputGateBias =</div><div class="line"><a name="l01453"></a><span class="lineno"> 1453</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a>));</div><div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>  }</div><div class="line"><a name="l01455"></a><span class="lineno"> 1455</span> </div><div class="line"><a name="l01456"></a><span class="lineno"> 1456</span>  <span class="comment">//Lstm projection parameters</span></div><div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>  <span class="keywordflow">if</span>(descriptor.m_ProjectionEnabled)</div><div class="line"><a name="l01458"></a><span class="lineno"> 1458</span>  {</div><div class="line"><a name="l01459"></a><span class="lineno"> 1459</span>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a> == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>  {</div><div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddLstmLayer: Projection Weights cannot be NULL"</span>);</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>  layer->m_ProjectionParameters.m_ProjectionWeights =</div><div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a>));</div><div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>  {</div><div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>  layer->m_ProjectionParameters.m_ProjectionBias =</div><div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a>));</div><div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>  }</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> </div><div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>  <span class="comment">//Lstm Peephole params</span></div><div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>  <span class="keywordflow">if</span>(descriptor.m_PeepholeEnabled)</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="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a> == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>  {</div><div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddLstmLayer: Cell To Forget Weights cannot be NULL"</span>);</div><div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>  }</div><div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a> == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>  {</div><div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddLstmLayer: Cell To Output Weights cannot be NULL"</span>);</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>  layer->m_PeepholeParameters.m_CellToForgetWeights =</div><div class="line"><a name="l01484"></a><span class="lineno"> 1484</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a>));</div><div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>  layer->m_PeepholeParameters.m_CellToOutputWeights =</div><div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a>));</div><div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>  }</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>  <span class="comment">//Lstm Layer Normalization params</span></div><div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>  <span class="keywordflow">if</span>(descriptor.m_LayerNormEnabled)</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>  <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</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>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a0cd848f65ec31778d708852f0042fe37">m_InputLayerNormWeights</a> == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>  {</div><div class="line"><a name="l01496"></a><span class="lineno"> 1496</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddLstmLayer: Input layer normalization weights cannot be NULL"</span>);</div><div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>  }</div><div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>  layer->m_LayerNormParameters.m_InputLayerNormWeights =</div><div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a0cd848f65ec31778d708852f0042fe37">m_InputLayerNormWeights</a>));</div><div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>  }</div><div class="line"><a name="l01501"></a><span class="lineno"> 1501</span> </div><div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#af0f796fba1a2be9c56b4c9ee534577ee">m_ForgetLayerNormWeights</a> == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>  {</div><div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddLstmLayer: Forget layer normalization weights cannot be NULL"</span>);</div><div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>  }</div><div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ad0b8c32bb5381f4cc999093ba3b98b43">m_CellLayerNormWeights</a> == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>  {</div><div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddLstmLayer: Cell layer normalization weights cannot be NULL"</span>);</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>  <span class="keywordflow">if</span>(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a9b18daea2e9f42386055326fd016519a">m_OutputLayerNormWeights</a> == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>  {</div><div class="line"><a name="l01512"></a><span class="lineno"> 1512</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddLstmLayer: Output layer normalization weights cannot be NULL"</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>  layer->m_LayerNormParameters.m_ForgetLayerNormWeights =</div><div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#af0f796fba1a2be9c56b4c9ee534577ee">m_ForgetLayerNormWeights</a>));</div><div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>  layer->m_LayerNormParameters.m_CellLayerNormWeights =</div><div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ad0b8c32bb5381f4cc999093ba3b98b43">m_CellLayerNormWeights</a>));</div><div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>  layer->m_LayerNormParameters.m_OutputLayerNormWeights =</div><div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>  std::make_unique<ScopedCpuTensorHandle>(*(params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a9b18daea2e9f42386055326fd016519a">m_OutputLayerNormWeights</a>));</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="keywordflow">return</span> layer;</div><div class="line"><a name="l01522"></a><span class="lineno"> 1522</span> }</div><div class="line"><a name="l01523"></a><span class="lineno"> 1523</span> </div><div class="line"><a name="l01524"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a47d30afdd251fef00a59d2234cca0020"> 1524</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a47d30afdd251fef00a59d2234cca0020">Network::AddDivisionLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01525"></a><span class="lineno"> 1525</span> {</div><div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_division_layer.xhtml">DivisionLayer</a>>(name);</div><div class="line"><a name="l01527"></a><span class="lineno"> 1527</span> }</div><div class="line"><a name="l01528"></a><span class="lineno"> 1528</span> </div><div class="line"><a name="l01529"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a59a557b3b913730cf1153f1337a64496"> 1529</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a59a557b3b913730cf1153f1337a64496">Network::AddSubtractionLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01530"></a><span class="lineno"> 1530</span> {</div><div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>>(name);</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"><a class="line" href="classarmnn_1_1_network.xhtml#a06632621d4259f7ef2aadb03cc08e993"> 1534</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a06632621d4259f7ef2aadb03cc08e993">Network::AddMeanLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_mean_descriptor.xhtml">MeanDescriptor</a>& meanDescriptor, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_mean_layer.xhtml">MeanLayer</a>>(meanDescriptor,name);</div><div class="line"><a name="l01537"></a><span class="lineno"> 1537</span> }</div><div class="line"><a name="l01538"></a><span class="lineno"> 1538</span> </div><div class="line"><a name="l01539"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a7d7934b6f0d8d4ae7749875397d724fc"> 1539</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a7d7934b6f0d8d4ae7749875397d724fc">Network::AddPadLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_pad_descriptor.xhtml">PadDescriptor</a>& padDescriptor, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_pad_layer.xhtml">PadLayer</a>>(padDescriptor,name);</div><div class="line"><a name="l01542"></a><span class="lineno"> 1542</span> }</div><div class="line"><a name="l01543"></a><span class="lineno"> 1543</span> </div><div class="line"><a name="l01544"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a4d008f554108aaee4c2c769dcdde685f"> 1544</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a> *<a class="code" href="classarmnn_1_1_network.xhtml#a4d008f554108aaee4c2c769dcdde685f">Network::AddQuantizeLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span> *name)</div><div class="line"><a name="l01545"></a><span class="lineno"> 1545</span> {</div><div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_quantize_layer.xhtml">QuantizeLayer</a>>(name);</div><div class="line"><a name="l01547"></a><span class="lineno"> 1547</span> }</div><div class="line"><a name="l01548"></a><span class="lineno"> 1548</span> </div><div class="line"><a name="l01549"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a224ea587dd10d2aa0d019be5c9de4b89"> 1549</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a224ea587dd10d2aa0d019be5c9de4b89">Network::AddDequantizeLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01550"></a><span class="lineno"> 1550</span> {</div><div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_dequantize_layer.xhtml">DequantizeLayer</a>>(name);</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="classarmnn_1_1_network.xhtml#a9bf4cfcac428b1331ff83c45f1166665"> 1554</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a9bf4cfcac428b1331ff83c45f1166665">Network::AddStridedSliceLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml">StridedSliceDescriptor</a>& stridedSliceDescriptor,</div><div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_strided_slice_layer.xhtml">StridedSliceLayer</a>>(stridedSliceDescriptor, name);</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> </div><div class="line"><a name="l01560"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#aad4a7bebcdaeeea663429cbd47b2917e"> 1560</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#aad4a7bebcdaeeea663429cbd47b2917e">Network::AddGreaterLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01561"></a><span class="lineno"> 1561</span> {</div><div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network.xhtml#a52fab7cec34e1fa77df68503e0c0ce59">AddComparisonLayer</a>(<a class="code" href="structarmnn_1_1_comparison_descriptor.xhtml">ComparisonDescriptor</a>(<a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a">ComparisonOperation::Greater</a>), name);</div><div class="line"><a name="l01563"></a><span class="lineno"> 1563</span> }</div><div class="line"><a name="l01564"></a><span class="lineno"> 1564</span> </div><div class="line"><a name="l01565"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a9062eab56f601adeae8229fd8759fbd7"> 1565</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a9062eab56f601adeae8229fd8759fbd7">Network::AddEqualLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01566"></a><span class="lineno"> 1566</span> {</div><div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network.xhtml#a52fab7cec34e1fa77df68503e0c0ce59">AddComparisonLayer</a>(<a class="code" href="structarmnn_1_1_comparison_descriptor.xhtml">ComparisonDescriptor</a>(<a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">ComparisonOperation::Equal</a>), name);</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"><a class="line" href="classarmnn_1_1_network.xhtml#ac107b7e1d91f17f2023ea9ed113f559c"> 1570</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#ac107b7e1d91f17f2023ea9ed113f559c">Network::AddRsqrtLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span> * name)</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network.xhtml#a99093f440e7e0ba4c8dcc90c3ec8cf4d">AddElementwiseUnaryLayer</a>(<a class="code" href="structarmnn_1_1_elementwise_unary_descriptor.xhtml">ElementwiseUnaryDescriptor</a>(<a class="code" href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8a09bb7f6e2118c85a6a55bd4bf2beeca4">UnaryOperation::Rsqrt</a>), name);</div><div class="line"><a name="l01573"></a><span class="lineno"> 1573</span> }</div><div class="line"><a name="l01574"></a><span class="lineno"> 1574</span> </div><div class="line"><a name="l01575"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#ac3d4632a58d626521765246bbfdeadcf"> 1575</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#ac3d4632a58d626521765246bbfdeadcf">Network::AddGatherLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01576"></a><span class="lineno"> 1576</span> {</div><div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_gather_layer.xhtml">GatherLayer</a>>(name);</div><div class="line"><a name="l01578"></a><span class="lineno"> 1578</span> }</div><div class="line"><a name="l01579"></a><span class="lineno"> 1579</span> </div><div class="line"><a name="l01580"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a679d1dd7ae79631ba09c642a7b25158a"> 1580</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a679d1dd7ae79631ba09c642a7b25158a">Network::AddMergeLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01581"></a><span class="lineno"> 1581</span> {</div><div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_merge_layer.xhtml">MergeLayer</a>>(name);</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> </div><div class="line"><a name="l01585"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a48a6892297a07e5d87020b9b817e2224"> 1585</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a48a6892297a07e5d87020b9b817e2224">Network::AddSwitchLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_switch_layer.xhtml">SwitchLayer</a>>(name);</div><div class="line"><a name="l01588"></a><span class="lineno"> 1588</span> }</div><div class="line"><a name="l01589"></a><span class="lineno"> 1589</span> </div><div class="line"><a name="l01590"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#ae00badf3bdad170348706604b7e6c694"> 1590</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#ae00badf3bdad170348706604b7e6c694">Network::AddPreluLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01591"></a><span class="lineno"> 1591</span> {</div><div class="line"><a name="l01592"></a><span class="lineno"> 1592</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_prelu_layer.xhtml">PreluLayer</a>>(name);</div><div class="line"><a name="l01593"></a><span class="lineno"> 1593</span> }</div><div class="line"><a name="l01594"></a><span class="lineno"> 1594</span> </div><div class="line"><a name="l01595"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a59f6284064bfe8f2fbdb997fc3b65586"> 1595</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a59f6284064bfe8f2fbdb997fc3b65586">Network::AddTransposeConvolution2dLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">TransposeConvolution2dDescriptor</a>& descriptor,</div><div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weights,</div><div class="line"><a name="l01597"></a><span class="lineno"> 1597</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a>& biases,</div><div class="line"><a name="l01598"></a><span class="lineno"> 1598</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01599"></a><span class="lineno"> 1599</span> {</div><div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> && !biases.<a class="code" href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">has_value</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="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddTransposeConvolution2dLayer: Biases cannot be empty"</span>);</div><div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>  }</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">const</span> <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_transpose_convolution2d_layer.xhtml">TransposeConvolution2dLayer</a>>(descriptor, name);</div><div class="line"><a name="l01606"></a><span class="lineno"> 1606</span> </div><div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>  layer-><a class="code" href="classarmnn_1_1_transpose_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l01608"></a><span class="lineno"> 1608</span> </div><div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>  <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</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>  layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>());</div><div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>  }</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="keywordflow">return</span> layer;</div><div class="line"><a name="l01615"></a><span class="lineno"> 1615</span> }</div><div class="line"><a name="l01616"></a><span class="lineno"> 1616</span> </div><div class="line"><a name="l01617"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#ac4860f8e63591cd71c4c6a9f4b9e349b"> 1617</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#ac4860f8e63591cd71c4c6a9f4b9e349b">Network::AddTransposeLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_transpose_descriptor.xhtml">TransposeDescriptor</a>& transposeDescriptor,</div><div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_transpose_layer.xhtml">TransposeLayer</a>>(transposeDescriptor, name);</div><div class="line"><a name="l01621"></a><span class="lineno"> 1621</span> }</div><div class="line"><a name="l01622"></a><span class="lineno"> 1622</span> </div><div class="line"><a name="l01623"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a204e14633b366322221f04c76ed275e3"> 1623</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a204e14633b366322221f04c76ed275e3">Network::AddStackLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">StackDescriptor</a>& stackDescriptor,</div><div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_stack_layer.xhtml">StackLayer</a>>(stackDescriptor, name);</div><div class="line"><a name="l01627"></a><span class="lineno"> 1627</span> }</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> </div><div class="line"><a name="l01630"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a18aea8e0700f679353afb0a0cb9e0c84"> 1630</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a18aea8e0700f679353afb0a0cb9e0c84">Network::AddStandInLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml">StandInDescriptor</a>& desc,</div><div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01632"></a><span class="lineno"> 1632</span> {</div><div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_stand_in_layer.xhtml">StandInLayer</a>>(desc, name);</div><div class="line"><a name="l01634"></a><span class="lineno"> 1634</span> }</div><div class="line"><a name="l01635"></a><span class="lineno"> 1635</span> </div><div class="line"><a name="l01636"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a6a6657fdd77cabea7a9e0a740635735e"> 1636</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network.xhtml#a6a6657fdd77cabea7a9e0a740635735e">Network::AddQuantizedLstmLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml">QuantizedLstmInputParams</a>& params,</div><div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01638"></a><span class="lineno"> 1638</span> {</div><div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml">QuantizedLstmLayer</a>>(name);</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>  <span class="comment">// InputToX weights</span></div><div class="line"><a name="l01642"></a><span class="lineno"> 1642</span>  layer-><a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">m_InputToInputWeights</a> =</div><div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a23d6133552ba91cc0571517896792ea4">GetInputToInputWeights</a>());</div><div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>  layer->m_QuantizedLstmParameters.m_InputToForgetWeights =</div><div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a339c19855613274cf0ea13921af9e5a3">GetInputToForgetWeights</a>());</div><div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>  layer->m_QuantizedLstmParameters.m_InputToCellWeights =</div><div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a928f70dd19a2b0d3e9b75c27a2099c44">GetInputToCellWeights</a>());</div><div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>  layer->m_QuantizedLstmParameters.m_InputToOutputWeights =</div><div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a477440c44fe870fb6f2486bf68214395">GetInputToOutputWeights</a>());</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>  <span class="comment">// RecurrentToX weights</span></div><div class="line"><a name="l01652"></a><span class="lineno"> 1652</span>  layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights =</div><div class="line"><a name="l01653"></a><span class="lineno"> 1653</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ad2e53e6428416a65ae4ba566207cc6bf">GetRecurrentToInputWeights</a>());</div><div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>  layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights =</div><div class="line"><a name="l01655"></a><span class="lineno"> 1655</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a8ad69d6d46b4b12f47fbe6032c9b7a18">GetRecurrentToForgetWeights</a>());</div><div class="line"><a name="l01656"></a><span class="lineno"> 1656</span>  layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights =</div><div class="line"><a name="l01657"></a><span class="lineno"> 1657</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a63e34dd3e41262e750f7a54de8ca81d1">GetRecurrentToCellWeights</a>());</div><div class="line"><a name="l01658"></a><span class="lineno"> 1658</span>  layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights =</div><div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a94645f29b99800c2e57acc4832519a53">GetRecurrentToOutputWeights</a>());</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>  <span class="comment">// Bias</span></div><div class="line"><a name="l01662"></a><span class="lineno"> 1662</span>  layer->m_QuantizedLstmParameters.m_InputGateBias =</div><div class="line"><a name="l01663"></a><span class="lineno"> 1663</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#aba6d12c9d5671017b6711b80316069ff">GetInputGateBias</a>());</div><div class="line"><a name="l01664"></a><span class="lineno"> 1664</span>  layer->m_QuantizedLstmParameters.m_ForgetGateBias =</div><div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a715696f29b5376cbb8aaec0b77a092af">GetForgetGateBias</a>());</div><div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>  layer->m_QuantizedLstmParameters.m_CellBias =</div><div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a89f3c8b72e3a802240156915141de5ca">GetCellBias</a>());</div><div class="line"><a name="l01668"></a><span class="lineno"> 1668</span>  layer->m_QuantizedLstmParameters.m_OutputGateBias =</div><div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>  std::make_unique<ScopedCpuTensorHandle>(params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a1691bf16df2cabf1a4b82aecbb021f31">GetOutputGateBias</a>());</div><div class="line"><a name="l01670"></a><span class="lineno"> 1670</span> </div><div class="line"><a name="l01671"></a><span class="lineno"> 1671</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l01672"></a><span class="lineno"> 1672</span> }</div><div class="line"><a name="l01673"></a><span class="lineno"> 1673</span> </div><div class="line"><a name="l01674"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network.xhtml#a75a50f464326fefa605ea84ae2c9be85"> 1674</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_network.xhtml#a75a50f464326fefa605ea84ae2c9be85">Network::Accept</a>(<a class="code" href="classarmnn_1_1_i_layer_visitor.xhtml">ILayerVisitor</a>& visitor)<span class="keyword"> const</span></div><div class="line"><a name="l01675"></a><span class="lineno"> 1675</span> <span class="keyword"></span>{</div><div class="line"><a name="l01676"></a><span class="lineno"> 1676</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> layer : <a class="code" href="classarmnn_1_1_network.xhtml#afe0a4f719f9752a405e71878da7012ba">GetGraph</a>())</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>  layer->Accept(visitor);</div><div class="line"><a name="l01679"></a><span class="lineno"> 1679</span>  };</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"><a class="line" href="classarmnn_1_1_optimized_network.xhtml#a971533529217dab76688ac1b4cb92103"> 1682</a></span> <a class="code" href="classarmnn_1_1_optimized_network.xhtml#a971533529217dab76688ac1b4cb92103">OptimizedNetwork::OptimizedNetwork</a>(std::unique_ptr<Graph> graph)</div><div class="line"><a name="l01683"></a><span class="lineno"> 1683</span>  : m_Graph(<a class="code" href="namespacestd.xhtml">std</a>::move(graph)),</div><div class="line"><a name="l01684"></a><span class="lineno"> 1684</span>  m_Guid(profiling::<a class="code" href="classarmnn_1_1profiling_1_1_profiling_service.xhtml">ProfilingService</a>::Instance().NextGuid())</div><div class="line"><a name="l01685"></a><span class="lineno"> 1685</span> {</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> </div><div class="line"><a name="l01688"></a><span class="lineno"><a class="line" href="classarmnn_1_1_optimized_network.xhtml#ab09173dfe4beb721a6d0585e9bfcf392"> 1688</a></span> <a class="code" href="classarmnn_1_1_optimized_network.xhtml#ab09173dfe4beb721a6d0585e9bfcf392">OptimizedNetwork::~OptimizedNetwork</a>()</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> }</div><div class="line"><a name="l01691"></a><span class="lineno"> 1691</span> </div><div class="line"><a name="l01692"></a><span class="lineno"> 1692</span> } <span class="comment">// namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_network_xhtml_a5f56923e4eac55c8c08d72599b0a0d41"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a5f56923e4eac55c8c08d72599b0a0d41">armnn::Network::Network</a></div><div class="ttdeci">Network()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01025">Network.cpp:1025</a></div></div> +<div class="ttc" id="classarmnn_1_1_constant_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_constant_layer.xhtml">armnn::ConstantLayer</a></div><div class="ttdoc">A layer that the constant data can be bound to. </div><div class="ttdef"><b>Definition:</b> <a href="_constant_layer_8hpp_source.xhtml#l00015">ConstantLayer.hpp:15</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a64ddffb38fbe5b78ec92b753cd4bd0ba"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a64ddffb38fbe5b78ec92b753cd4bd0ba">armnn::optimizations::SquashEqualPermuteSiblings</a></div><div class="ttdeci">OptimizeForConnection< Layer, PermuteLayer, SquashEqualSiblingsImpl< PermuteLayer > > SquashEqualPermuteSiblings</div><div class="ttdef"><b>Definition:</b> <a href="_squash_equal_siblings_8hpp_source.xhtml#l00066">SquashEqualSiblings.hpp:66</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a7658f93d899c8646515a29370e6aa994"><div class="ttname"><a href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994">armnn::ReportError</a></div><div class="ttdeci">void ReportError(const std::string &errorMessage, Optional< std::vector< std::string > &> errorMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00075">Network.cpp:75</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="classarmnn_1_1_network_xhtml_ac9062f3da8a725626fd7e7bd27449220"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ac9062f3da8a725626fd7e7bd27449220">armnn::Network::~Network</a></div><div class="ttdeci">~Network()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01031">Network.cpp:1031</a></div></div> +<div class="ttc" id="_device_spec_8hpp_xhtml"><div class="ttname"><a href="_device_spec_8hpp.xhtml">DeviceSpec.hpp</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="namespacearmnn_xhtml_a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a"><div class="ttname"><a href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca8768a6821cd735aea4f5b0df88c1fc6a">armnn::ComparisonOperation::Greater</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_ab8b4e22c47ae0b0f259de353e760a4bf"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ab8b4e22c47ae0b0f259de353e760a4bf">armnn::Network::AddPooling2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddPooling2dLayer(const Pooling2dDescriptor &pooling2dDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a pooling layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01237">Network.cpp:1237</a></div></div> +<div class="ttc" id="classarmnn_1_1_minimum_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_minimum_layer.xhtml">armnn::MinimumLayer</a></div><div class="ttdoc">This layer represents a minimum operation. </div><div class="ttdef"><b>Definition:</b> <a href="_minimum_layer_8hpp_source.xhtml#l00014">MinimumLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_ac043d9a6e3f861fc6aa057ff95e56f18"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ac043d9a6e3f861fc6aa057ff95e56f18">armnn::ITensorHandleFactory::DeferredFactoryId</a></div><div class="ttdeci">static const FactoryId DeferredFactoryId</div><div class="ttdoc">Use the workload factory to create the tensor handle. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00023">ITensorHandleFactory.hpp:23</a></div></div> +<div class="ttc" id="classarmnn_1_1_splitter_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_splitter_layer.xhtml">armnn::SplitterLayer</a></div><div class="ttdoc">This layer represents a split operation. </div><div class="ttdef"><b>Definition:</b> <a href="_splitter_layer_8hpp_source.xhtml#l00013">SplitterLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_lstm_layer_xhtml_a8838b317568861294a9df608221f185e"><div class="ttname"><a href="classarmnn_1_1_lstm_layer.xhtml#a8838b317568861294a9df608221f185e">armnn::LstmLayer::m_BasicParameters</a></div><div class="ttdeci">LstmBasicParameters m_BasicParameters</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_layer_8hpp_source.xhtml#l00081">LstmLayer.hpp:81</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="classarmnn_1_1_output_slot_xhtml_a50b562d4a4edc64d7d8abcca056f0b8c"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a50b562d4a4edc64d7d8abcca056f0b8c">armnn::OutputSlot::GetConnections</a></div><div class="ttdeci">const std::vector< InputSlot * > & GetConnections() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00125">Layer.hpp:125</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a94645f29b99800c2e57acc4832519a53"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a94645f29b99800c2e57acc4832519a53">armnn::QuantizedLstmInputParams::GetRecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensor & GetRecurrentToOutputWeights() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00093">QuantizedLstmParams.hpp:93</a></div></div> +<div class="ttc" id="classarmnn_1_1_backend_registry_xhtml_afc0c63ca8db8957b58826f6d7bd231b2"><div class="ttname"><a href="classarmnn_1_1_backend_registry.xhtml#afc0c63ca8db8957b58826f6d7bd231b2">armnn::BackendRegistry::GetFactory</a></div><div class="ttdeci">FactoryFunction GetFactory(const BackendId &id) const</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.xhtml#l00048">BackendRegistry.cpp:48</a></div></div> +<div class="ttc" id="classarmnn_1_1_batch_normalization_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.xhtml">armnn::BatchNormalizationLayer</a></div><div class="ttdoc">This layer represents a batch normalization operation. </div><div class="ttdef"><b>Definition:</b> <a href="_batch_normalization_layer_8hpp_source.xhtml#l00015">BatchNormalizationLayer.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a55bd1bb29076dc45bb335e7322781463"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a55bd1bb29076dc45bb335e7322781463">armnn::INetwork::Destroy</a></div><div class="ttdeci">static void Destroy(INetwork *network)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00054">Network.cpp:54</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="namespacearmnn_1_1optimizations_xhtml_aa31127c77d2117f78d43ca2958dcae19"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#aa31127c77d2117f78d43ca2958dcae19">armnn::optimizations::OptimizeInversePermutes</a></div><div class="ttdeci">OptimizeForConnection< PermuteLayer, PermuteLayer, OptimizeInversePermutesImpl< PermuteLayer > > OptimizeInversePermutes</div><div class="ttdef"><b>Definition:</b> <a href="_optimize_inverse_permutes_8hpp_source.xhtml#l00042">OptimizeInversePermutes.hpp:42</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_aa262a54803b53b8198cd60e7af2f60e4"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#aa262a54803b53b8198cd60e7af2f60e4">armnn::ITensorHandleFactory::SupportsMapUnmap</a></div><div class="ttdeci">virtual bool SupportsMapUnmap() const final</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00058">ITensorHandleFactory.hpp:58</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="namespacearmnn_xhtml_abf625e50a5eaeafce5b39580dc95a9d3"><div class="ttname"><a href="namespacearmnn.xhtml#abf625e50a5eaeafce5b39580dc95a9d3">armnn::InsertConvertFp32ToFp16LayersAfter</a></div><div class="ttdeci">std::vector< ConvertFp32ToFp16Layer * > InsertConvertFp32ToFp16LayersAfter(Graph &graph, Layer &layer)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.xhtml#l00079">NetworkUtils.cpp:79</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_1_1_network_xhtml_ad55ff20f4c7e60c18b849e61f28f0e2e"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ad55ff20f4c7e60c18b849e61f28f0e2e">armnn::Network::AddOutputLayer</a></div><div class="ttdeci">IConnectableLayer * AddOutputLayer(LayerBindingId id, const char *name=nullptr) override</div><div class="ttdoc">Adds an output layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01310">Network.cpp:1310</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a3f80ddd1f76ed4ad599e0d1a00659ee5"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a3f80ddd1f76ed4ad599e0d1a00659ee5">armnn::OutputSlot::SetEdgeStrategy</a></div><div class="ttdeci">void SetEdgeStrategy(unsigned int connectionIndex, EdgeStrategy strategy)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00177">Layer.cpp:177</a></div></div> +<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml_ad3c37b52145c3cf1b4856c0df008a468"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">armnn::QuantizedLstmLayer::m_QuantizedLstmParameters</a></div><div class="ttdeci">QuantizedLstmParameters m_QuantizedLstmParameters</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00049">QuantizedLstmLayer.hpp:49</a></div></div> +<div class="ttc" id="classarmnn_1_1_transpose_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_transpose_convolution2d_layer.xhtml">armnn::TransposeConvolution2dLayer</a></div><div class="ttdoc">This layer represents a 2D transpose convolution operation. </div><div class="ttdef"><b>Definition:</b> <a href="_transpose_convolution2d_layer_8hpp_source.xhtml#l00015">TransposeConvolution2dLayer.hpp:15</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aff209afc1dc598da399e3e78617ce016a78d1be0baa31e083ae8da99aaedaf650"><div class="ttname"><a href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016a78d1be0baa31e083ae8da99aaedaf650">armnn::EdgeStrategy::DirectCompatibility</a></div><div class="ttdoc">No strategy has been defined. Used internally to verify integrity of optimizations. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad31c56533e4f9f9f51719599fbfcf7bb"><div class="ttname"><a href="namespacearmnn.xhtml#ad31c56533e4f9f9f51719599fbfcf7bb">armnn::InsertConvertFp16ToFp32LayersBefore</a></div><div class="ttdeci">std::vector< ConvertFp16ToFp32Layer * > InsertConvertFp16ToFp32LayersBefore(Graph &graph, Layer &layer, bool expectCorrectInputType)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.xhtml#l00040">NetworkUtils.cpp:40</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_acce5b3272c9da9cb4201b437dd96a729"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#acce5b3272c9da9cb4201b437dd96a729">armnn::Network::AddL2NormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddL2NormalizationLayer(const L2NormalizationDescriptor &desc, const char *name=nullptr) override</div><div class="ttdoc">Adds an L2 normalization layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01356">Network.cpp:1356</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="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a></div><div class="ttdoc">CPU Execution: Reference C++ kernels. </div></div> +<div class="ttc" id="_utils_8hpp_xhtml"><div class="ttname"><a href="_utils_8hpp.xhtml">Utils.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa7427025a851113a492de0b68b23d22a"><div class="ttname"><a href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a></div><div class="ttdeci">Optimizer::Optimizations MakeOptimizations(Args &&... args)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8hpp_source.xhtml#l00043">Optimizer.hpp:43</a></div></div> +<div class="ttc" id="classarmnn_1_1_fully_connected_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_fully_connected_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::FullyConnectedLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_fully_connected_layer_8hpp_source.xhtml#l00019">FullyConnectedLayer.hpp:19</a></div></div> +<div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00270">Optional.hpp:270</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="classarmnn_1_1_network_xhtml_acae7df585b6c920cecd8065f0e16ff9b"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#acae7df585b6c920cecd8065f0e16ff9b">armnn::Network::AddResizeBilinearLayer</a></div><div class="ttdeci">IConnectableLayer * AddResizeBilinearLayer(const ResizeBilinearDescriptor &resizeDesc, const char *name=nullptr) override</div><div class="ttdoc">Adds a resize bilinear layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01332">Network.cpp:1332</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_backend_internal_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_backend_internal.xhtml">armnn::IBackendInternal</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.xhtml#l00068">IBackendInternal.hpp:68</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a06632621d4259f7ef2aadb03cc08e993"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a06632621d4259f7ef2aadb03cc08e993">armnn::Network::AddMeanLayer</a></div><div class="ttdeci">IConnectableLayer * AddMeanLayer(const MeanDescriptor &meanDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Add a Mean layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01534">Network.cpp:1534</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="namespacearmnn_xhtml_a8d9f52bbb69750456acca06988beabda"><div class="ttname"><a href="namespacearmnn.xhtml#a8d9f52bbb69750456acca06988beabda">armnn::CalculateSlotOption</a></div><div class="ttdeci">ITensorHandleFactory::FactoryId CalculateSlotOption(BackendsMap &backends, OutputSlot &outputSlot, TensorHandleFactoryRegistry &registry)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00638">Network.cpp:638</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a2f9d1a13be2ac1c4213729a0ef181fc0"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a2f9d1a13be2ac1c4213729a0ef181fc0">armnn::optimizations::OptimizeInverseTransposes</a></div><div class="ttdeci">OptimizeForConnection< TransposeLayer, TransposeLayer, OptimizeInversePermutesImpl< TransposeLayer > > OptimizeInverseTransposes</div><div class="ttdef"><b>Definition:</b> <a href="_optimize_inverse_permutes_8hpp_source.xhtml#l00044">OptimizeInversePermutes.hpp:44</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a8ad69d6d46b4b12f47fbe6032c9b7a18"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a8ad69d6d46b4b12f47fbe6032c9b7a18">armnn::QuantizedLstmInputParams::GetRecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensor & GetRecurrentToForgetWeights() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00083">QuantizedLstmParams.hpp:83</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a98f54d4391347d517c7a7869e7707203"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a98f54d4391347d517c7a7869e7707203">armnn::optimizations::TransposeAndBatchToSpaceAsDepthToSpace</a></div><div class="ttdeci">OptimizeForConnection< TransposeLayer, BatchToSpaceNdLayer, PermuteAndBatchToSpaceAsDepthToSpaceImpl< TransposeLayer > > TransposeAndBatchToSpaceAsDepthToSpace</div><div class="ttdef"><b>Definition:</b> <a href="_permute_and_batch_to_space_as_depth_to_space_8hpp_source.xhtml#l00105">PermuteAndBatchToSpaceAsDepthToSpace.hpp:105</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="_deprecated_8hpp_xhtml_ab66a241a0ed3ee89c866e777b035d0ed"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_BEGIN</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00033">Deprecated.hpp:33</a></div></div> +<div class="ttc" id="_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_workload_factory_8hpp.xhtml">WorkloadFactory.hpp</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="namespacearmnn_xhtml_ab46c7f5f4736d550ab0e5e05a0fff4a9"><div class="ttname"><a href="namespacearmnn.xhtml#ab46c7f5f4736d550ab0e5e05a0fff4a9">armnn::CalculateSlotOptionForOutput</a></div><div class="ttdeci">ITensorHandleFactory::FactoryId CalculateSlotOptionForOutput(BackendsMap &backends, OutputSlot &slot, TensorHandleFactoryRegistry &registry)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00628">Network.cpp:628</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="classarmnn_1_1_depthwise_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">armnn::DepthwiseConvolution2dLayer</a></div><div class="ttdoc">This layer represents a depthwise convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.xhtml#l00015">DepthwiseConvolution2dLayer.hpp:15</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a5ee4a1cca55f69b31e625c786655ed1a"><div class="ttname"><a href="namespacearmnn.xhtml#a5ee4a1cca55f69b31e625c786655ed1a">armnn::RequiresCopy</a></div><div class="ttdeci">bool RequiresCopy(ITensorHandleFactory::FactoryId src, ITensorHandleFactory::FactoryId dst, TensorHandleFactoryRegistry &registry)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00526">Network.cpp:526</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_bilinear_descriptor_xhtml_adcf5037208faac36c0788239a073f75c"><div class="ttname"><a href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">armnn::ResizeBilinearDescriptor::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#l00716">Descriptors.hpp:716</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_bilinear_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::ResizeBilinearDescriptor::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#l00720">Descriptors.hpp:720</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a4c47466a95f61c321f525b06fc87b2c5"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a4c47466a95f61c321f525b06fc87b2c5">armnn::Network::AddLogSoftmaxLayer</a></div><div class="ttdeci">IConnectableLayer * AddLogSoftmaxLayer(const LogSoftmaxDescriptor &logSoftmaxDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a log softmax layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01362">Network.cpp:1362</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a89f3c8b72e3a802240156915141de5ca"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a89f3c8b72e3a802240156915141de5ca">armnn::QuantizedLstmInputParams::GetCellBias</a></div><div class="ttdeci">const ConstTensor & GetCellBias() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00108">QuantizedLstmParams.hpp:108</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="classarmnn_1_1_output_slot_xhtml_a7ddaf04177053a536f0e7be83a642bc6"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7ddaf04177053a536f0e7be83a642bc6">armnn::OutputSlot::GetOwningLayer</a></div><div class="ttdeci">Layer & GetOwningLayer() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00115">Layer.hpp:115</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aff209afc1dc598da399e3e78617ce016ac366da48cc11956ae377a77751936852"><div class="ttname"><a href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016ac366da48cc11956ae377a77751936852">armnn::EdgeStrategy::CopyToTarget</a></div><div class="ttdoc">Source backends tensor data can be exported to destination backend tensor without copy...</div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a1add5219a64f4249a282f52202828451"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a1add5219a64f4249a282f52202828451">armnn::Network::AddDepthwiseConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddDepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor &convolution2dDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr) override</div><div class="ttdoc">Adds a 2D depthwise convolution layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01193">Network.cpp:1193</a></div></div> +<div class="ttc" id="classarmnn_1_1_convert_fp16_to_fp32_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_convert_fp16_to_fp32_layer.xhtml">armnn::ConvertFp16ToFp32Layer</a></div><div class="ttdoc">This layer converts data type Float 16 to Float 32. </div><div class="ttdef"><b>Definition:</b> <a href="_convert_fp16_to_fp32_layer_8hpp_source.xhtml#l00014">ConvertFp16ToFp32Layer.hpp:14</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="classarmnn_1_1_network_xhtml_afe0a4f719f9752a405e71878da7012ba"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#afe0a4f719f9752a405e71878da7012ba">armnn::Network::GetGraph</a></div><div class="ttdeci">const Graph & GetGraph() const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00034">Network.hpp:34</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a48a6892297a07e5d87020b9b817e2224"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a48a6892297a07e5d87020b9b817e2224">armnn::Network::AddSwitchLayer</a></div><div class="ttdeci">IConnectableLayer * AddSwitchLayer(const char *name=nullptr) override</div><div class="ttdoc">Adds a switch layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01585">Network.cpp:1585</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="classarmnn_1_1_network_xhtml_a7b9879b0da1f561d10e4f5c545028143"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a7b9879b0da1f561d10e4f5c545028143">armnn::Network::AddFloorLayer</a></div><div class="ttdeci">IConnectableLayer * AddFloorLayer(const char *name=nullptr) override</div><div class="ttdoc">Adds a floor layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01395">Network.cpp:1395</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimizer_xhtml_a1f48ba622b76ea04d15c9b62f642bf08"><div class="ttname"><a href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a></div><div class="ttdeci">static void Pass(Graph &graph, const Optimizations &optimizations)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8cpp_source.xhtml#l00016">Optimizer.cpp:16</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="classarmnn_1_1_space_to_depth_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_space_to_depth_layer.xhtml">armnn::SpaceToDepthLayer</a></div><div class="ttdoc">This layer represents a SpaceToDepth operation. </div><div class="ttdef"><b>Definition:</b> <a href="_space_to_depth_layer_8hpp_source.xhtml#l00014">SpaceToDepthLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a90d8841cfbbc82ab02328f33fed24ac6"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a90d8841cfbbc82ab02328f33fed24ac6">armnn::Network::AddInputLayer</a></div><div class="ttdeci">IConnectableLayer * AddInputLayer(LayerBindingId id, const char *name=nullptr) override</div><div class="ttdoc">Adds an input layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01041">Network.cpp:1041</a></div></div> +<div class="ttc" id="classarmnn_1_1_reshape_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_reshape_layer.xhtml">armnn::ReshapeLayer</a></div><div class="ttdoc">This layer represents a reshape operation. </div><div class="ttdef"><b>Definition:</b> <a href="_reshape_layer_8hpp_source.xhtml#l00013">ReshapeLayer.hpp:13</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">armnn::LayerType::ConvertFp32ToFp16</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_parameters_xhtml_a4d731c5e73638c7cf7e63f65e9f8b550"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">armnn::QuantizedLstmParameters::m_InputToInputWeights</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_InputToInputWeights</div><div class="ttdoc">A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8)...</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00017">QuantizedLstmLayer.hpp:17</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="_logging_8hpp_xhtml_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.xhtml#l00163">Logging.hpp:163</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml">armnn::INetwork</a></div><div class="ttdoc">Main network class which provides the interface for building up a neural network. ...</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00105">INetwork.hpp:105</a></div></div> +<div class="ttc" id="classarmnn_1_1_activation_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_activation_layer.xhtml">armnn::ActivationLayer</a></div><div class="ttdoc">This layer represents an activation operation with the specified activation function. </div><div class="ttdef"><b>Definition:</b> <a href="_activation_layer_8hpp_source.xhtml#l00012">ActivationLayer.hpp:12</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimization_views_xhtml"><div class="ttname"><a href="classarmnn_1_1_optimization_views.xhtml">armnn::OptimizationViews</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_optimization_views_8hpp_source.xhtml#l00013">OptimizationViews.hpp:13</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ac2807505b850738bc8a1991ce669dd47"><div class="ttname"><a href="namespacearmnn.xhtml#ac2807505b850738bc8a1991ce669dd47">armnn::BackendRegistryInstance</a></div><div class="ttdeci">BackendRegistry & BackendRegistryInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.xhtml#l00013">BackendRegistry.cpp:13</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="classarmnn_1_1_network_xhtml_a75a50f464326fefa605ea84ae2c9be85"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a75a50f464326fefa605ea84ae2c9be85">armnn::Network::Accept</a></div><div class="ttdeci">void Accept(ILayerVisitor &visitor) const override</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01674">Network.cpp:1674</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_add39cd8a51e34c532fb56cf313703844"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#add39cd8a51e34c532fb56cf313703844">armnn::Network::AddMinimumLayer</a></div><div class="ttdeci">IConnectableLayer * AddMinimumLayer(const char *name=nullptr) override</div><div class="ttdoc">Add a Minimum layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01284">Network.cpp:1284</a></div></div> +<div class="ttc" id="classarmnn_1_1_stand_in_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_stand_in_layer.xhtml">armnn::StandInLayer</a></div><div class="ttdoc">This layer represents an unknown operation in the input graph. </div><div class="ttdef"><b>Definition:</b> <a href="_stand_in_layer_8hpp_source.xhtml#l00014">StandInLayer.hpp:14</a></div></div> +<div class="ttc" id="_backend_settings_8hpp_xhtml"><div class="ttname"><a href="_backend_settings_8hpp.xhtml">BackendSettings.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a29f8d97b2d74f99c88298881cd1d825b"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a29f8d97b2d74f99c88298881cd1d825b">armnn::optimizations::SquashEqualReshapeSiblings</a></div><div class="ttdeci">OptimizeForConnection< Layer, ReshapeLayer, SquashEqualSiblingsImpl< ReshapeLayer > > SquashEqualReshapeSiblings</div><div class="ttdef"><b>Definition:</b> <a href="_squash_equal_siblings_8hpp_source.xhtml#l00069">SquashEqualSiblings.hpp:69</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimized_network_xhtml_a49800ad35ea869aa5569519760d3b339"><div class="ttname"><a href="classarmnn_1_1_optimized_network.xhtml#a49800ad35ea869aa5569519760d3b339">armnn::OptimizedNetwork::GetGraph</a></div><div class="ttdeci">Graph & GetGraph()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00276">Network.hpp:276</a></div></div> +<div class="ttc" id="classarmnn_1_1_detection_post_process_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_detection_post_process_layer.xhtml">armnn::DetectionPostProcessLayer</a></div><div class="ttdoc">This layer represents a detection postprocess operator. </div><div class="ttdef"><b>Definition:</b> <a href="_detection_post_process_layer_8hpp_source.xhtml#l00016">DetectionPostProcessLayer.hpp:16</a></div></div> +<div class="ttc" id="classarmnn_1_1_subgraph_view_xhtml_aaf68d7cca5c48a7f3d398452a5244667"><div class="ttname"><a href="classarmnn_1_1_subgraph_view.xhtml#aaf68d7cca5c48a7f3d398452a5244667">armnn::SubgraphView::end</a></div><div class="ttdeci">Iterator end()</div><div class="ttdef"><b>Definition:</b> <a href="_subgraph_view_8cpp_source.xhtml#l00169">SubgraphView.cpp:169</a></div></div> +<div class="ttc" id="structarmnn_1_1_backend_settings_xhtml_a0b160952af61b24d88125d66ed6d43c1"><div class="ttname"><a href="structarmnn_1_1_backend_settings.xhtml#a0b160952af61b24d88125d66ed6d43c1">armnn::BackendSettings::m_SupportedBackends</a></div><div class="ttdeci">BackendIdSet m_SupportedBackends</div><div class="ttdef"><b>Definition:</b> <a href="_backend_settings_8hpp_source.xhtml#l00020">BackendSettings.hpp:20</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="namespacearmnn_1_1optimizations_xhtml_a5918588fa316cf4c23f1cf02c81ee706"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a5918588fa316cf4c23f1cf02c81ee706">armnn::optimizations::MoveTransposeUp</a></div><div class="ttdeci">OptimizeForConnection< Layer, TransposeLayer, MoveTransposeUpImpl > MoveTransposeUp</div><div class="ttdef"><b>Definition:</b> <a href="_move_transpose_up_8hpp_source.xhtml#l00080">MoveTransposeUp.hpp:80</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_ae50fff9aa2a1ce46392d8641c10aa3bc"><div class="ttname"><a href="namespacearmnn.xhtml#ae50fff9aa2a1ce46392d8641c10aa3bc">armnn::ReturnWithError</a></div><div class="ttdeci">OptimizationResult ReturnWithError(OptimizationResult res, const Layer *layer, const BackendSettings &backendSettings, Optional< std::vector< std::string > &> errMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00099">Network.cpp:99</a></div></div> +<div class="ttc" id="classarmnn_1_1_transpose_convolution2d_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_transpose_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::TransposeConvolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Weight</div><div class="ttdoc">A unique pointer to store weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_transpose_convolution2d_layer_8hpp_source.xhtml#l00019">TransposeConvolution2dLayer.hpp:19</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="classarmnn_1_1_pad_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_pad_layer.xhtml">armnn::PadLayer</a></div><div class="ttdoc">This layer represents a pad operation. </div><div class="ttdef"><b>Definition:</b> <a href="_pad_layer_8hpp_source.xhtml#l00014">PadLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_lstm_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_lstm_layer.xhtml">armnn::LstmLayer</a></div><div class="ttdoc">This layer represents a LSTM operation. </div><div class="ttdef"><b>Definition:</b> <a href="_lstm_layer_8hpp_source.xhtml#l00077">LstmLayer.hpp:77</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="namespacearmnn_1_1optimizations_xhtml_add2180a15cdcf5a229de32bb956cb224"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#add2180a15cdcf5a229de32bb956cb224">armnn::optimizations::FoldPadIntoConvolution2d</a></div><div class="ttdeci">OptimizeForConnection< PadLayer, Convolution2dLayer, FoldPadIntoConvolution2dImpl > FoldPadIntoConvolution2d</div><div class="ttdef"><b>Definition:</b> <a href="_fold_pad_into_convolution2d_8hpp_source.xhtml#l00088">FoldPadIntoConvolution2d.hpp:88</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="classarmnn_1_1_layer_xhtml_a3f6ad59212fa8a47c9265162fff8a274"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a3f6ad59212fa8a47c9265162fff8a274">armnn::Layer::SetBackendId</a></div><div class="ttdeci">void SetBackendId(const BackendId &id)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00264">Layer.hpp:264</a></div></div> +<div class="ttc" id="structarmnn_1_1_backend_settings_xhtml_aa5df3120ee0fbb3321df3133ec9e83ae"><div class="ttname"><a href="structarmnn_1_1_backend_settings.xhtml#aa5df3120ee0fbb3321df3133ec9e83ae">armnn::BackendSettings::IsBackendSupported</a></div><div class="ttdeci">bool IsBackendSupported(const BackendId &backend) const</div><div class="ttdef"><b>Definition:</b> <a href="_backend_settings_8hpp_source.xhtml#l00045">BackendSettings.hpp:45</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_acc25db0641c1c22faf95af3bb49080c9"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">armnn::Graph::Iterator</a></div><div class="ttdeci">LayerList::const_iterator Iterator</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00050">Graph.hpp:50</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a80dc86e975ff991ef63aa8b523d4fcdf"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a80dc86e975ff991ef63aa8b523d4fcdf">armnn::Network::AddFullyConnectedLayer</a></div><div class="ttdeci">IConnectableLayer * AddFullyConnectedLayer(const FullyConnectedDescriptor &fullyConnectedDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr) override</div><div class="ttdoc">Adds a fully connected layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01086">Network.cpp:1086</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="classarmnn_1_1_optional_reference_switch_xhtml_a77c7d528ac063d870b8c8426ec81c1c3"><div class="ttname"><a href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">armnn::OptionalReferenceSwitch< std::is_reference< T >::value, T >::value</a></div><div class="ttdeci">const T & value() const</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00146">Optional.hpp:146</a></div></div> +<div class="ttc" id="classarmnn_1_1_permute_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_permute_layer.xhtml">armnn::PermuteLayer</a></div><div class="ttdoc">This layer represents a permutation operation. </div><div class="ttdef"><b>Definition:</b> <a href="_permute_layer_8hpp_source.xhtml#l00013">PermuteLayer.hpp:13</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a477440c44fe870fb6f2486bf68214395"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a477440c44fe870fb6f2486bf68214395">armnn::QuantizedLstmInputParams::GetInputToOutputWeights</a></div><div class="ttdeci">const ConstTensor & GetInputToOutputWeights() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00073">QuantizedLstmParams.hpp:73</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a5d3468fb5880eb444cd25b55a86220ff"><div class="ttname"><a href="namespacearmnn.xhtml#a5d3468fb5880eb444cd25b55a86220ff">armnn::SelectTensorHandleStrategy</a></div><div class="ttdeci">OptimizationResult SelectTensorHandleStrategy(Graph &optGraph, BackendsMap &backends, TensorHandleFactoryRegistry &registry, Optional< std::vector< std::string > &> errMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00824">Network.cpp:824</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a1594bddc87d6477df300317658f566bb"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a1594bddc87d6477df300317658f566bb">armnn::Layer::GetNumOutputSlots</a></div><div class="ttdeci">unsigned int GetNumOutputSlots() const override</div><div class="ttdoc">Returns the number of connectable output slots. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00308">Layer.hpp:308</a></div></div> +<div class="ttc" id="classarmnn_1_1_space_to_batch_nd_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_space_to_batch_nd_layer.xhtml">armnn::SpaceToBatchNdLayer</a></div><div class="ttdoc">This layer represents a SpaceToBatchNd operation. </div><div class="ttdef"><b>Definition:</b> <a href="_space_to_batch_nd_layer_8hpp_source.xhtml#l00014">SpaceToBatchNdLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_ac107b7e1d91f17f2023ea9ed113f559c"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ac107b7e1d91f17f2023ea9ed113f559c">armnn::Network::AddRsqrtLayer</a></div><div class="ttdeci">IConnectableLayer * AddRsqrtLayer(const char *name=nullptr) override</div><div class="ttdoc">Add Reciprocal of square root layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01570">Network.cpp:1570</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="namespacearmnn_1_1optimizations_xhtml_aa76c76565125ad77092403176d74fd85"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#aa76c76565125ad77092403176d74fd85">armnn::optimizations::InsertDebugLayer</a></div><div class="ttdeci">OptimizeForType< Layer, AddDebugImpl > InsertDebugLayer</div><div class="ttdef"><b>Definition:</b> <a href="_add_debug_8hpp_source.xhtml#l00034">AddDebug.hpp:34</a></div></div> +<div class="ttc" id="_backend_registry_8hpp_xhtml"><div class="ttname"><a href="_backend_registry_8hpp.xhtml">BackendRegistry.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a8341ca3512ebafb19d60eba44d40d9e4"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a8341ca3512ebafb19d60eba44d40d9e4">armnn::optimizations::OptimizeConsecutiveReshapes</a></div><div class="ttdeci">OptimizeForConnection< ReshapeLayer, ReshapeLayer, OptimizeConsecutiveReshapesImpl > OptimizeConsecutiveReshapes</div><div class="ttdef"><b>Definition:</b> <a href="_optimize_consecutive_reshapes_8hpp_source.xhtml#l00063">OptimizeConsecutiveReshapes.hpp:63</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="classarmnn_1_1_elementwise_unary_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_elementwise_unary_layer.xhtml">armnn::ElementwiseUnaryLayer</a></div><div class="ttdoc">This layer represents a elementwiseUnary operation. </div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_unary_layer_8hpp_source.xhtml#l00014">ElementwiseUnaryLayer.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a81b5ff8545adad19a1c9d4ca076d552c"><div class="ttname"><a href="namespacearmnn.xhtml#a81b5ff8545adad19a1c9d4ca076d552c">armnn::GetDataTypeName</a></div><div class="ttdeci">constexpr const char * GetDataTypeName(DataType dataType)</div><div class="ttdef"><b>Definition:</b> <a href="_types_utils_8hpp_source.xhtml#l00168">TypesUtils.hpp:168</a></div></div> +<div class="ttc" id="_optimizer_8hpp_xhtml"><div class="ttname"><a href="_optimizer_8hpp.xhtml">Optimizer.hpp</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="classarmnn_1_1_network_xhtml_a9062eab56f601adeae8229fd8759fbd7"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a9062eab56f601adeae8229fd8759fbd7">armnn::Network::AddEqualLayer</a></div><div class="ttdeci">IConnectableLayer * AddEqualLayer(const char *name=nullptr) override</div><div class="ttdoc">Add a Equal layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01565">Network.cpp:1565</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a865189c08aa64d448d05efc92a43725a"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a865189c08aa64d448d05efc92a43725a">armnn::Network::AddConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddConvolution2dLayer(const Convolution2dDescriptor &convolution2dDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr) override</div><div class="ttdoc">Adds a 2D convolution layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01139">Network.cpp:1139</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="classarmnn_1_1_network_xhtml_a59f6284064bfe8f2fbdb997fc3b65586"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a59f6284064bfe8f2fbdb997fc3b65586">armnn::Network::AddTransposeConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddTransposeConvolution2dLayer(const TransposeConvolution2dDescriptor &descriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr) override</div><div class="ttdoc">Adds a 2D transpose convolution layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01595">Network.cpp:1595</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aff209afc1dc598da399e3e78617ce016a46e8b7bfd6fd3c0cb34a100478a39189"><div class="ttname"><a href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016a46e8b7bfd6fd3c0cb34a100478a39189">armnn::EdgeStrategy::ExportToTarget</a></div><div class="ttdoc">Destination backend can work directly with tensors on source backend. </div></div> +<div class="ttc" id="classarmnn_1_1_i_backend_internal_xhtml_ac5d107c5672f446603b6e6b92bce6244"><div class="ttname"><a href="classarmnn_1_1_i_backend_internal.xhtml#ac5d107c5672f446603b6e6b92bce6244">armnn::IBackendInternal::GetHandleFactoryPreferences</a></div><div class="ttdeci">virtual std::vector< ITensorHandleFactory::FactoryId > GetHandleFactoryPreferences() const</div><div class="ttdoc">(Optional) Returns a vector of supported TensorHandleFactory ids in preference order. </div><div class="ttdef"><b>Definition:</b> <a href="_i_backend_internal_8cpp_source.xhtml#l00096">IBackendInternal.cpp:96</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a1a9d718b48612b5817a3c369f9fd71ee"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a1a9d718b48612b5817a3c369f9fd71ee">armnn::optimizations::OptimizeInverseConversionsFp16</a></div><div class="ttdeci">OptimizeForConnection< ConvertFp16ToFp32Layer, ConvertFp32ToFp16Layer, OptimizeInverseConversionsImpl > OptimizeInverseConversionsFp16</div><div class="ttdef"><b>Definition:</b> <a href="_optimize_inverse_conversions_8hpp_source.xhtml#l00042">OptimizeInverseConversions.hpp:42</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml_a6e1a42622ca43dafc7ba8e684c016eb4"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a6e1a42622ca43dafc7ba8e684c016eb4">armnn::OptimizerOptions::m_ReduceFp32ToFp16</a></div><div class="ttdeci">bool m_ReduceFp32ToFp16</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00595">INetwork.hpp:595</a></div></div> +<div class="ttc" id="classarmnn_1_1_quantize_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_quantize_layer.xhtml">armnn::QuantizeLayer</a></div><div class="ttdef"><b>Definition:</b> <a href="_quantize_layer_8hpp_source.xhtml#l00017">QuantizeLayer.hpp:17</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimization_result_xhtml_aca1654c65182fe4e7d5fd45f556fcd57"><div class="ttname"><a href="structarmnn_1_1_optimization_result.xhtml#aca1654c65182fe4e7d5fd45f556fcd57">armnn::OptimizationResult::IsError</a></div><div class="ttdeci">bool IsError() const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00301">Network.hpp:301</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimized_network_xhtml_ab09173dfe4beb721a6d0585e9bfcf392"><div class="ttname"><a href="classarmnn_1_1_optimized_network.xhtml#ab09173dfe4beb721a6d0585e9bfcf392">armnn::OptimizedNetwork::~OptimizedNetwork</a></div><div class="ttdeci">~OptimizedNetwork()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01688">Network.cpp:1688</a></div></div> +<div class="ttc" id="classarmnn_1_1_subgraph_view_xhtml"><div class="ttname"><a href="classarmnn_1_1_subgraph_view.xhtml">armnn::SubgraphView</a></div><div class="ttdoc">The SubgraphView class represents a subgraph of a Graph. </div><div class="ttdef"><b>Definition:</b> <a href="_subgraph_view_8hpp_source.xhtml#l00023">SubgraphView.hpp:23</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae97734279fd10b4c754cc15bc8ed9dad"><div class="ttname"><a href="namespacearmnn.xhtml#ae97734279fd10b4c754cc15bc8ed9dad">armnn::ApplyBackendOptimizations</a></div><div class="ttdeci">OptimizationResult ApplyBackendOptimizations(OptimizedNetwork *optNetObjPtr, BackendSettings &backendSettings, BackendsMap &backends, Optional< std::vector< std::string > &> errMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00428">Network.cpp:428</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_1_1_instance_normalization_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_instance_normalization_layer.xhtml">armnn::InstanceNormalizationLayer</a></div><div class="ttdoc">This layer represents an instance normalization operation. </div><div class="ttdef"><b>Definition:</b> <a href="_instance_normalization_layer_8hpp_source.xhtml#l00013">InstanceNormalizationLayer.hpp:13</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml_a69eb14082d40fa0a3cff50457344a5e0"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a69eb14082d40fa0a3cff50457344a5e0">armnn::OptimizerOptions::m_Debug</a></div><div class="ttdeci">bool m_Debug</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00598">INetwork.hpp:598</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ab6ed577caec49def150e231c63af0d12"><div class="ttname"><a href="namespacearmnn.xhtml#ab6ed577caec49def150e231c63af0d12">armnn::CalculateEdgeStrategy</a></div><div class="ttdeci">EdgeStrategy CalculateEdgeStrategy(BackendsMap &backends, ITensorHandleFactory::FactoryId srcFactoryId, const Layer &layer, const Layer &connectedLayer, TensorHandleFactoryRegistry &registry)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00747">Network.cpp:747</a></div></div> +<div class="ttc" id="namespacestd_xhtml"><div class="ttname"><a href="namespacestd.xhtml">std</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.xhtml#l00147">BackendId.hpp:147</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a17d1279f5f8e3b92c328b1ed3b6fd549"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a17d1279f5f8e3b92c328b1ed3b6fd549">armnn::optimizations::PermuteAndBatchToSpaceAsDepthToSpace</a></div><div class="ttdeci">OptimizeForConnection< PermuteLayer, BatchToSpaceNdLayer, PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteLayer > > PermuteAndBatchToSpaceAsDepthToSpace</div><div class="ttdef"><b>Definition:</b> <a href="_permute_and_batch_to_space_as_depth_to_space_8hpp_source.xhtml#l00103">PermuteAndBatchToSpaceAsDepthToSpace.hpp:103</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_1_1optimizations_xhtml_aafc70d5af99400ff5ea7991825658b2f"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#aafc70d5af99400ff5ea7991825658b2f">armnn::optimizations::MovePermuteUp</a></div><div class="ttdeci">OptimizeForConnection< Layer, PermuteLayer, MovePermuteUpImpl > MovePermuteUp</div><div class="ttdef"><b>Definition:</b> <a href="_move_permute_up_8hpp_source.xhtml#l00080">MovePermuteUp.hpp:80</a></div></div> +<div class="ttc" id="classarmnn_1_1_constant_layer_xhtml_a67ccc257eeefce0964c1cafc4b255c9f"><div class="ttname"><a href="classarmnn_1_1_constant_layer.xhtml#a67ccc257eeefce0964c1cafc4b255c9f">armnn::ConstantLayer::m_LayerOutput</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_LayerOutput</div><div class="ttdef"><b>Definition:</b> <a href="_constant_layer_8hpp_source.xhtml#l00043">ConstantLayer.hpp:43</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a928f70dd19a2b0d3e9b75c27a2099c44"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a928f70dd19a2b0d3e9b75c27a2099c44">armnn::QuantizedLstmInputParams::GetInputToCellWeights</a></div><div class="ttdeci">const ConstTensor & GetInputToCellWeights() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00068">QuantizedLstmParams.hpp:68</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a09774b1c2b882e1d573dc507479805b6"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a09774b1c2b882e1d573dc507479805b6">armnn::Network::AddReshapeLayer</a></div><div class="ttdeci">IConnectableLayer * AddReshapeLayer(const ReshapeDescriptor &reshapeDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a reshape layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01377">Network.cpp:1377</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">armnn::LayerType::ConvertFp16ToFp32</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a0fc99721e27eb20ecd0ea85a3cc8b488a1131a914388fac73e5f07b0ba0aad523"><div class="ttname"><a href="namespacearmnn.xhtml#a0fc99721e27eb20ecd0ea85a3cc8b488a1131a914388fac73e5f07b0ba0aad523">armnn::MemorySource::Malloc</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_ac4860f8e63591cd71c4c6a9f4b9e349b"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ac4860f8e63591cd71c4c6a9f4b9e349b">armnn::Network::AddTransposeLayer</a></div><div class="ttdeci">IConnectableLayer * AddTransposeLayer(const TransposeDescriptor &transposeDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a transpose layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01617">Network.cpp:1617</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.xhtml#l00013">OutputLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_ad6521013ad981519904822f2ada2c4ec"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#ad6521013ad981519904822f2ada2c4ec">armnn::Graph::ForEachLayer</a></div><div class="ttdeci">void ForEachLayer(Func func) const</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00039">Graph.hpp:39</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">armnn::Status::Success</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimized_network_xhtml_a9aa1b214fcaec2371fe4226bd126fb73"><div class="ttname"><a href="classarmnn_1_1_optimized_network.xhtml#a9aa1b214fcaec2371fe4226bd126fb73">armnn::OptimizedNetwork::PrintGraph</a></div><div class="ttdeci">Status PrintGraph() override</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00064">Network.cpp:64</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a679d1dd7ae79631ba09c642a7b25158a"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a679d1dd7ae79631ba09c642a7b25158a">armnn::Network::AddMergeLayer</a></div><div class="ttdeci">IConnectableLayer * AddMergeLayer(const char *name=nullptr) override</div><div class="ttdoc">Adds a merge layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01580">Network.cpp:1580</a></div></div> +<div class="ttc" id="classarmnn_1_1_dequantize_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_dequantize_layer.xhtml">armnn::DequantizeLayer</a></div><div class="ttdoc">This layer dequantizes the input tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_dequantize_layer_8hpp_source.xhtml#l00013">DequantizeLayer.hpp:13</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a226cef3d775179e25ee35d231f4e8fae"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a226cef3d775179e25ee35d231f4e8fae">armnn::optimizations::ConvertConstantsFloatToHalf</a></div><div class="ttdeci">ConvertConstants< Float32ToFloat16, IsFloat16Layer > ConvertConstantsFloatToHalf</div><div class="ttdef"><b>Definition:</b> <a href="_convert_constants_8hpp_source.xhtml#l00101">ConvertConstants.hpp:101</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="include_2armnn_2backends_2_i_backend_internal_8hpp_xhtml"><div class="ttname"><a href="include_2armnn_2backends_2_i_backend_internal_8hpp.xhtml">IBackendInternal.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_ad1aaeee71293f34d9f65d2dd2792830d"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#ad1aaeee71293f34d9f65d2dd2792830d">armnn::optimizations::TransposeAsReshape</a></div><div class="ttdeci">OptimizeForType< TransposeLayer, TransposeAsReshapeImpl > TransposeAsReshape</div><div class="ttdef"><b>Definition:</b> <a href="_transpose_as_reshape_8hpp_source.xhtml#l00078">TransposeAsReshape.hpp:78</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a10c7356df73267c2acf3248465d5954b"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a10c7356df73267c2acf3248465d5954b">armnn::Network::AddMaximumLayer</a></div><div class="ttdeci">IConnectableLayer * AddMaximumLayer(const char *name=nullptr) override</div><div class="ttdoc">Add a Maximum layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01279">Network.cpp:1279</a></div></div> +<div class="ttc" id="classarmnn_1_1_gather_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_gather_layer.xhtml">armnn::GatherLayer</a></div><div class="ttdoc">This layer represents a Gather operator. </div><div class="ttdef"><b>Definition:</b> <a href="_gather_layer_8hpp_source.xhtml#l00014">GatherLayer.hpp:14</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="classarmnn_1_1_detection_post_process_layer_xhtml_a6844fecab0edaf324de5a57fee8b65f1"><div class="ttname"><a href="classarmnn_1_1_detection_post_process_layer.xhtml#a6844fecab0edaf324de5a57fee8b65f1">armnn::DetectionPostProcessLayer::m_Anchors</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Anchors</div><div class="ttdoc">A unique pointer to store Anchor values. </div><div class="ttdef"><b>Definition:</b> <a href="_detection_post_process_layer_8hpp_source.xhtml#l00020">DetectionPostProcessLayer.hpp:20</a></div></div> +<div class="ttc" id="classarmnn_1_1_fully_connected_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_fully_connected_layer.xhtml">armnn::FullyConnectedLayer</a></div><div class="ttdoc">This layer represents a fully connected operation. </div><div class="ttdef"><b>Definition:</b> <a href="_fully_connected_layer_8hpp_source.xhtml#l00015">FullyConnectedLayer.hpp:15</a></div></div> +<div class="ttc" id="_all_8hpp_xhtml"><div class="ttname"><a href="_all_8hpp.xhtml">All.hpp</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="_deprecated_8hpp_xhtml_ad762b11b48e5c1d1c1743f529485728a"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_END</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00034">Deprecated.hpp:34</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00890">Network.cpp:890</a></div></div> +<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml">armnn::QuantizedLstmLayer</a></div><div class="ttdoc">This layer represents a QuantizedLstm operation. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00045">QuantizedLstmLayer.hpp:45</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a9da573d7a1fc03726fd41f2130cbcf92"><div class="ttname"><a href="namespacearmnn.xhtml#a9da573d7a1fc03726fd41f2130cbcf92">armnn::GetLayerTypeAsCString</a></div><div class="ttdeci">char const * GetLayerTypeAsCString(LayerType type)</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8cpp_source.xhtml#l00013">InternalTypes.cpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_log_softmax_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_log_softmax_layer.xhtml">armnn::LogSoftmaxLayer</a></div><div class="ttdoc">This layer represents a log softmax operation. </div><div class="ttdef"><b>Definition:</b> <a href="_log_softmax_layer_8hpp_source.xhtml#l00014">LogSoftmaxLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_batch_normalization_layer_xhtml_a3540afac8fad99bbe68b3f7b57590160"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.xhtml#a3540afac8fad99bbe68b3f7b57590160">armnn::BatchNormalizationLayer::m_Mean</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Mean</div><div class="ttdoc">A unique pointer to store Mean values. </div><div class="ttdef"><b>Definition:</b> <a href="_batch_normalization_layer_8hpp_source.xhtml#l00019">BatchNormalizationLayer.hpp:19</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="_graph_8hpp_xhtml"><div class="ttname"><a href="_graph_8hpp.xhtml">Graph.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a770b51078da02f44a819e9f95d8058b5"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">armnn::TensorInfo::GetQuantizationOffset</a></div><div class="ttdeci">int32_t GetQuantizationOffset() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00264">Tensor.cpp:264</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="classarmnn_1_1_tensor_info_xhtml_a047ca888c43bd7fb5702853bf72410d0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">armnn::TensorInfo::GetQuantizationScale</a></div><div class="ttdeci">float GetQuantizationScale() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00247">Tensor.cpp:247</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00095">Tensor.hpp:95</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_1_1_i_optimized_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_optimized_network.xhtml">armnn::IOptimizedNetwork</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00568">INetwork.hpp:568</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407a7b83d3f08fa392b79e3f553b585971cd">armnn::BoostLogSeverityMapping::warning</a></div></div> +<div class="ttc" id="classarmnn_1_1_optional_base_xhtml_a86b749ce2c4bc627fa8a1fcfaf0e314f"><div class="ttname"><a href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">armnn::OptionalBase::has_value</a></div><div class="ttdeci">bool has_value() const noexcept</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00053">Optional.hpp:53</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimization_result_xhtml_a955b65059e7f9429a5d6041136bc1487"><div class="ttname"><a href="structarmnn_1_1_optimization_result.xhtml#a955b65059e7f9429a5d6041136bc1487">armnn::OptimizationResult::IsOk</a></div><div class="ttdeci">bool IsOk() const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00299">Network.hpp:299</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="classarmnn_1_1_convolution2d_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::Convolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.xhtml#l00020">Convolution2dLayer.hpp:20</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="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div></div> +<div class="ttc" id="classarmnn_1_1_stack_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_stack_layer.xhtml">armnn::StackLayer</a></div><div class="ttdoc">This layer represents a stack operation. </div><div class="ttdef"><b>Definition:</b> <a href="_stack_layer_8hpp_source.xhtml#l00013">StackLayer.hpp:13</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnn::LayerType::Permute</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="classarmnn_1_1_network_xhtml_a7b0396c132c4da95e80b210f9b6734e9"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a7b0396c132c4da95e80b210f9b6734e9">armnn::Network::AddConcatLayer</a></div><div class="ttdeci">IConnectableLayer * AddConcatLayer(const ConcatDescriptor &concatDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a concatenation layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01111">Network.cpp:1111</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimization_views_xhtml_ad5fee4381bf82ffa37658dddf4d1fa01"><div class="ttname"><a href="classarmnn_1_1_optimization_views.xhtml#ad5fee4381bf82ffa37658dddf4d1fa01">armnn::OptimizationViews::GetFailedSubgraphs</a></div><div class="ttdeci">const Subgraphs & GetFailedSubgraphs() const</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_optimization_views_8hpp_source.xhtml#l00050">OptimizationViews.hpp:50</a></div></div> +<div class="ttc" id="classarmnn_1_1_concat_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_concat_layer.xhtml">armnn::ConcatLayer</a></div><div class="ttdoc">This layer represents a merge operation. </div><div class="ttdef"><b>Definition:</b> <a href="_concat_layer_8hpp_source.xhtml#l00013">ConcatLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_softmax_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_softmax_layer.xhtml">armnn::SoftmaxLayer</a></div><div class="ttdoc">This layer represents a softmax operation. </div><div class="ttdef"><b>Definition:</b> <a href="_softmax_layer_8hpp_source.xhtml#l00013">SoftmaxLayer.hpp:13</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="classarmnn_1_1_layer_xhtml_a9a97cb6d32661a57fc33bd29b8e41ff4"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a9a97cb6d32661a57fc33bd29b8e41ff4">armnn::Layer::GetNameStr</a></div><div class="ttdeci">const std::string & GetNameStr() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00216">Layer.hpp:216</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="structarmnn_1_1_quantized_lstm_input_params_xhtml_a23d6133552ba91cc0571517896792ea4"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a23d6133552ba91cc0571517896792ea4">armnn::QuantizedLstmInputParams::GetInputToInputWeights</a></div><div class="ttdeci">const ConstTensor & GetInputToInputWeights() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00058">QuantizedLstmParams.hpp:58</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="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70b"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a></div><div class="ttdeci">Status</div><div class="ttdoc">enumeration </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00026">Types.hpp:26</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</a></div></div> +<div class="ttc" id="classarmnn_1_1_batch_to_space_nd_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_batch_to_space_nd_layer.xhtml">armnn::BatchToSpaceNdLayer</a></div><div class="ttdoc">This layer represents a BatchToSpaceNd operation. </div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_layer_8hpp_source.xhtml#l00013">BatchToSpaceNdLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml">armnn::OutputSlot</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00083">Layer.hpp:83</a></div></div> +<div class="ttc" id="classarmnn_1_1_subgraph_view_selector_xhtml_aaf71a63dbbc776f8961b0f4fdb9da021"><div class="ttname"><a href="classarmnn_1_1_subgraph_view_selector.xhtml#aaf71a63dbbc776f8961b0f4fdb9da021">armnn::SubgraphViewSelector::Subgraphs</a></div><div class="ttdeci">std::vector< SubgraphViewPtr > Subgraphs</div><div class="ttdef"><b>Definition:</b> <a href="_subgraph_view_selector_8hpp_source.xhtml#l00025">SubgraphViewSelector.hpp:25</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00566">INetwork.hpp:566</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a7d7934b6f0d8d4ae7749875397d724fc"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a7d7934b6f0d8d4ae7749875397d724fc">armnn::Network::AddPadLayer</a></div><div class="ttdeci">IConnectableLayer * AddPadLayer(const PadDescriptor &padDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a fully pad layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01539">Network.cpp:1539</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a18aea8e0700f679353afb0a0cb9e0c84"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a18aea8e0700f679353afb0a0cb9e0c84">armnn::Network::AddStandInLayer</a></div><div class="ttdeci">IConnectableLayer * AddStandInLayer(const StandInDescriptor &descriptor, const char *name=nullptr) override</div><div class="ttdoc">Add a stand-in layer for a type unknown to the Arm NN framework. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01630">Network.cpp:1630</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a31d953b9d49a6b4378f45097047976d0"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a31d953b9d49a6b4378f45097047976d0">armnn::LayerType::Softmax</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00259">Tensor.cpp:259</a></div></div> +<div class="ttc" id="classarmnn_1_1_arg_min_max_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_arg_min_max_layer.xhtml">armnn::ArgMinMaxLayer</a></div><div class="ttdoc">This layer represents a ArgMinMax operation. </div><div class="ttdef"><b>Definition:</b> <a href="_arg_min_max_layer_8hpp_source.xhtml#l00014">ArgMinMaxLayer.hpp:14</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="classarmnn_1_1_network_xhtml_a36a40a1209689f39a5a283209991da3c"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a36a40a1209689f39a5a283209991da3c">armnn::Network::AddActivationLayer</a></div><div class="ttdeci">IConnectableLayer * AddActivationLayer(const ActivationDescriptor &activationDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds an activation layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01243">Network.cpp:1243</a></div></div> +<div class="ttc" id="structarmnn_1_1_backend_settings_xhtml_ad4ca579528452c669b45f3f35300fd4e"><div class="ttname"><a href="structarmnn_1_1_backend_settings.xhtml#ad4ca579528452c669b45f3f35300fd4e">armnn::BackendSettings::GetAvailablePreferredBackends</a></div><div class="ttdeci">BackendIdVector GetAvailablePreferredBackends() const</div><div class="ttdef"><b>Definition:</b> <a href="_backend_settings_8hpp_source.xhtml#l00066">BackendSettings.hpp:66</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a59a557b3b913730cf1153f1337a64496"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a59a557b3b913730cf1153f1337a64496">armnn::Network::AddSubtractionLayer</a></div><div class="ttdeci">IConnectableLayer * AddSubtractionLayer(const char *name=nullptr) override</div><div class="ttdoc">Adds a subtraction layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01529">Network.cpp:1529</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a98fef92a93b7a51ce6755dae02bb0cd4"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a98fef92a93b7a51ce6755dae02bb0cd4">armnn::Network::AddInstanceNormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddInstanceNormalizationLayer(const InstanceNormalizationDescriptor &desc, const char *name=nullptr) override</div><div class="ttdoc">Adds an instance normalization layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01350">Network.cpp:1350</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_device_spec_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_device_spec.xhtml">armnn::IDeviceSpec</a></div><div class="ttdoc">Device specific knowledge to be passed to the optimizer. </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00161">Types.hpp:161</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a74dc9ec1a223eab8b072368b2dacee87"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a74dc9ec1a223eab8b072368b2dacee87">armnn::IWorkloadFactory::IsLayerSupported</a></div><div class="ttdeci">static bool IsLayerSupported(const BackendId &backendId, const IConnectableLayer &layer, Optional< DataType > dataType, std::string &outReasonIfUnsupported)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l00045">WorkloadFactory.cpp:45</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml">armnn::OptimizerOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00582">INetwork.hpp:582</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a59e55a0755a655a809520738c697334f"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a59e55a0755a655a809520738c697334f">armnn::Network::AddDepthToSpaceLayer</a></div><div class="ttdeci">IConnectableLayer * AddDepthToSpaceLayer(const DepthToSpaceDescriptor &depthToSpaceDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a depth to space layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01187">Network.cpp:1187</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimization_views_xhtml_a58dc3ea86870112f745b2a1f7dca55e9"><div class="ttname"><a href="classarmnn_1_1_optimization_views.xhtml#a58dc3ea86870112f745b2a1f7dca55e9">armnn::OptimizationViews::Validate</a></div><div class="ttdeci">bool Validate(const SubgraphView &originalSubgraph) const</div><div class="ttdef"><b>Definition:</b> <a href="_optimization_views_8cpp_source.xhtml#l00011">OptimizationViews.cpp:11</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="structarmnn_1_1_optimization_result_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimization_result.xhtml">armnn::OptimizationResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00285">Network.hpp:285</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_afdb1d37740e7a083b625d669588b6a0e"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">armnn::Layer::GetBackendId</a></div><div class="ttdeci">const BackendId & GetBackendId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00263">Layer.hpp:263</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_bilinear_descriptor_xhtml_a46c3fa15c46fb0d1dcdc24d0ea5cb5cd"><div class="ttname"><a href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">armnn::ResizeBilinearDescriptor::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#l00718">Descriptors.hpp:718</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a204e14633b366322221f04c76ed275e3"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a204e14633b366322221f04c76ed275e3">armnn::Network::AddStackLayer</a></div><div class="ttdeci">IConnectableLayer * AddStackLayer(const StackDescriptor &stackDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a stack layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01623">Network.cpp:1623</a></div></div> +<div class="ttc" id="classarmnn_1_1_floor_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_floor_layer.xhtml">armnn::FloorLayer</a></div><div class="ttdoc">This layer represents a floor operation. </div><div class="ttdef"><b>Definition:</b> <a href="_floor_layer_8hpp_source.xhtml#l00013">FloorLayer.hpp:13</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_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_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_normalization_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_normalization_layer.xhtml">armnn::NormalizationLayer</a></div><div class="ttdoc">This layer represents a normalization operation. </div><div class="ttdef"><b>Definition:</b> <a href="_normalization_layer_8hpp_source.xhtml#l00013">NormalizationLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a9892b82652ffac03f1e4e7ad93906078"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9892b82652ffac03f1e4e7ad93906078">armnn::ITensorHandleFactory::GetExportFlags</a></div><div class="ttdeci">virtual MemorySourceFlags GetExportFlags() const</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00060">ITensorHandleFactory.hpp:60</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a715696f29b5376cbb8aaec0b77a092af"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a715696f29b5376cbb8aaec0b77a092af">armnn::QuantizedLstmInputParams::GetForgetGateBias</a></div><div class="ttdeci">const ConstTensor & GetForgetGateBias() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00103">QuantizedLstmParams.hpp:103</a></div></div> +<div class="ttc" id="classarmnn_1_1_pooling2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_pooling2d_layer.xhtml">armnn::Pooling2dLayer</a></div><div class="ttdoc">This layer represents a pooling 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_pooling2d_layer_8hpp_source.xhtml#l00013">Pooling2dLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_convert_fp32_to_fp16_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_convert_fp32_to_fp16_layer.xhtml">armnn::ConvertFp32ToFp16Layer</a></div><div class="ttdoc">This layer converts data type Float 32 to Float 16. </div><div class="ttdef"><b>Definition:</b> <a href="_convert_fp32_to_fp16_layer_8hpp_source.xhtml#l00013">ConvertFp32ToFp16Layer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimized_network_xhtml_a971533529217dab76688ac1b4cb92103"><div class="ttname"><a href="classarmnn_1_1_optimized_network.xhtml#a971533529217dab76688ac1b4cb92103">armnn::OptimizedNetwork::OptimizedNetwork</a></div><div class="ttdeci">OptimizedNetwork(std::unique_ptr< Graph > graph)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01682">Network.cpp:1682</a></div></div> +<div class="ttc" id="_logging_8hpp_xhtml"><div class="ttname"><a href="_logging_8hpp.xhtml">Logging.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_transpose_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_transpose_layer.xhtml">armnn::TransposeLayer</a></div><div class="ttdoc">This layer represents a transpose operation. </div><div class="ttdef"><b>Definition:</b> <a href="_transpose_layer_8hpp_source.xhtml#l00013">TransposeLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_acb8e86be339d57b32f0ba3d9293c880b"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#acb8e86be339d57b32f0ba3d9293c880b">armnn::Network::AddSplitterLayer</a></div><div class="ttdeci">IConnectableLayer * AddSplitterLayer(const ViewsDescriptor &splitterDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a splitter layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01273">Network.cpp:1273</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimization_result_xhtml_a41a657cfacb52a80a73575c5c730ab88"><div class="ttname"><a href="structarmnn_1_1_optimization_result.xhtml#a41a657cfacb52a80a73575c5c730ab88">armnn::OptimizationResult::m_Error</a></div><div class="ttdeci">bool m_Error</div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00288">Network.hpp:288</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_handle_factory_registry_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">armnn::TensorHandleFactoryRegistry</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_factory_registry_8hpp_source.xhtml#l00020">TensorHandleFactoryRegistry.hpp:20</a></div></div> +<div class="ttc" id="classarmnn_1_1_addition_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_addition_layer.xhtml">armnn::AdditionLayer</a></div><div class="ttdoc">This layer represents an addition operation. </div><div class="ttdef"><b>Definition:</b> <a href="_addition_layer_8hpp_source.xhtml#l00013">AdditionLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_aafbd4b469e47160017f409df8d077184"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#aafbd4b469e47160017f409df8d077184">armnn::Graph::SubstituteSubgraph</a></div><div class="ttdeci">void SubstituteSubgraph(SubgraphView &subgraph, IConnectableLayer *substituteLayer)</div><div class="ttdoc">Substitutes the given sub-graph with either a new layer or a new sub-graph. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00396">Graph.cpp:396</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a9aa1b214fcaec2371fe4226bd126fb73"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a9aa1b214fcaec2371fe4226bd126fb73">armnn::Network::PrintGraph</a></div><div class="ttdeci">Status PrintGraph() override</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01035">Network.cpp:1035</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_afa43cbc86ae43ce6ee468347b30229c4"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#afa43cbc86ae43ce6ee468347b30229c4">armnn::Network::AddSpaceToDepthLayer</a></div><div class="ttdeci">IConnectableLayer * AddSpaceToDepthLayer(const SpaceToDepthDescriptor &spaceToDepthDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a space to depth layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01389">Network.cpp:1389</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_af002111f64aee648e3258247075cae36"><div class="ttname"><a href="namespacearmnn.xhtml#af002111f64aee648e3258247075cae36">armnn::CheckScaleSetOnQuantizedType</a></div><div class="ttdeci">bool CheckScaleSetOnQuantizedType(Layer *layer, Optional< std::vector< std::string > &> errMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00114">Network.cpp:114</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_network.xhtml">armnn::Network</a></div><div class="ttdoc">Private implementation of INetwork. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00028">Network.hpp:28</a></div></div> +<div class="ttc" id="_cpu_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.xhtml">CpuTensorHandle.hpp</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="classarmnn_1_1_output_slot_xhtml_af29f6883785691ef946d0c32b6d2f338"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#af29f6883785691ef946d0c32b6d2f338">armnn::OutputSlot::SetTensorHandleFactory</a></div><div class="ttdeci">void SetTensorHandleFactory(const ITensorHandleFactory::FactoryId &id)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00167">Layer.cpp:167</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="classarmnn_1_1_slice_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_slice_layer.xhtml">armnn::SliceLayer</a></div><div class="ttdef"><b>Definition:</b> <a href="_slice_layer_8hpp_source.xhtml#l00013">SliceLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_ae00badf3bdad170348706604b7e6c694"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ae00badf3bdad170348706604b7e6c694">armnn::Network::AddPreluLayer</a></div><div class="ttdeci">IConnectableLayer * AddPreluLayer(const char *name=nullptr) override</div><div class="ttdoc">Adds a PReLU layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01590">Network.cpp:1590</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_ae0b1382e3af141896a46531c50e8863f"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#ae0b1382e3af141896a46531c50e8863f">armnn::optimizations::PermuteAsReshape</a></div><div class="ttdeci">OptimizeForType< PermuteLayer, PermuteAsReshapeImpl > PermuteAsReshape</div><div class="ttdef"><b>Definition:</b> <a href="_permute_as_reshape_8hpp_source.xhtml#l00067">PermuteAsReshape.hpp:67</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimization_result_xhtml_a2a35773a5a0e08b180a12205c3e15500"><div class="ttname"><a href="structarmnn_1_1_optimization_result.xhtml#a2a35773a5a0e08b180a12205c3e15500">armnn::OptimizationResult::IsWarningOnly</a></div><div class="ttdeci">bool IsWarningOnly() const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00300">Network.hpp:300</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="namespacearmnn_1_1optimizations_xhtml_aba7b0ca6192b8b58ecd517a82b4f378e"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#aba7b0ca6192b8b58ecd517a82b4f378e">armnn::optimizations::SquashEqualTransposeSiblings</a></div><div class="ttdeci">OptimizeForConnection< Layer, TransposeLayer, SquashEqualSiblingsImpl< TransposeLayer > > SquashEqualTransposeSiblings</div><div class="ttdef"><b>Definition:</b> <a href="_squash_equal_siblings_8hpp_source.xhtml#l00068">SquashEqualSiblings.hpp:68</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a1ca931603a06e926ca359e52890a6fea"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a1ca931603a06e926ca359e52890a6fea">armnn::INetwork::CreateRaw</a></div><div class="ttdeci">static INetwork * CreateRaw()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00044">Network.cpp:44</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aff209afc1dc598da399e3e78617ce016"><div class="ttname"><a href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016">armnn::EdgeStrategy</a></div><div class="ttdeci">EdgeStrategy</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00064">ITensorHandleFactory.hpp:64</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a4d008f554108aaee4c2c769dcdde685f"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a4d008f554108aaee4c2c769dcdde685f">armnn::Network::AddQuantizeLayer</a></div><div class="ttdeci">IConnectableLayer * AddQuantizeLayer(const char *name=nullptr) override</div><div class="ttdoc">Add a quantize layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01544">Network.cpp:1544</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_aba6d12c9d5671017b6711b80316069ff"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#aba6d12c9d5671017b6711b80316069ff">armnn::QuantizedLstmInputParams::GetInputGateBias</a></div><div class="ttdeci">const ConstTensor & GetInputGateBias() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00098">QuantizedLstmParams.hpp:98</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimization_views_xhtml_a9a1555f25af4a0ae2c0a1fc0ed9aded8"><div class="ttname"><a href="classarmnn_1_1_optimization_views.xhtml#a9a1555f25af4a0ae2c0a1fc0ed9aded8">armnn::OptimizationViews::GetSubstitutions</a></div><div class="ttdeci">const Substitutions & GetSubstitutions() const</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_optimization_views_8hpp_source.xhtml#l00049">OptimizationViews.hpp:49</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a40d7cd9d061c23405392f7c513849a2f"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a40d7cd9d061c23405392f7c513849a2f">armnn::Network::AddArgMinMaxLayer</a></div><div class="ttdeci">IConnectableLayer * AddArgMinMaxLayer(const ArgMinMaxDescriptor &desc, const char *name=nullptr) override</div><div class="ttdoc">Adds an ArgMinMax layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01249">Network.cpp:1249</a></div></div> +<div class="ttc" id="structarmnn_1_1_backend_settings_xhtml_ae6d0506ac92f9ba9529d019847144aa3"><div class="ttname"><a href="structarmnn_1_1_backend_settings.xhtml#ae6d0506ac92f9ba9529d019847144aa3">armnn::BackendSettings::m_PreferredBackends</a></div><div class="ttdeci">BackendIdVector m_PreferredBackends</div><div class="ttdef"><b>Definition:</b> <a href="_backend_settings_8hpp_source.xhtml#l00019">BackendSettings.hpp:19</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8acab870a91373c720c9822b59ecf3b8"><div class="ttname"><a href="namespacearmnn.xhtml#a8acab870a91373c720c9822b59ecf3b8">armnn::AssignBackends</a></div><div class="ttdeci">OptimizationResult AssignBackends(OptimizedNetwork *optNetObjPtr, BackendSettings &backendSettings, Graph::Iterator &firstLayer, Graph::Iterator &lastLayer, Optional< std::vector< std::string > &> errMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00269">Network.cpp:269</a></div></div> +<div class="ttc" id="classarmnn_1_1_subtraction_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_subtraction_layer.xhtml">armnn::SubtractionLayer</a></div><div class="ttdoc">This layer represents a subtraction operation. </div><div class="ttdef"><b>Definition:</b> <a href="_subtraction_layer_8hpp_source.xhtml#l00014">SubtractionLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1profiling_1_1_profiling_service_xhtml"><div class="ttname"><a href="classarmnn_1_1profiling_1_1_profiling_service.xhtml">armnn::profiling::ProfilingService</a></div><div class="ttdef"><b>Definition:</b> <a href="_profiling_service_8hpp_source.xhtml#l00042">ProfilingService.hpp:42</a></div></div> +<div class="ttc" id="classarmnn_1_1_switch_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_switch_layer.xhtml">armnn::SwitchLayer</a></div><div class="ttdoc">This layer calculates both true and false outputs for input. </div><div class="ttdef"><b>Definition:</b> <a href="_switch_layer_8hpp_source.xhtml#l00013">SwitchLayer.hpp:13</a></div></div> +<div class="ttc" id="_layer_8hpp_xhtml"><div class="ttname"><a href="_layer_8hpp.xhtml">Layer.hpp</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="namespacearmnn_1_1optimizations_xhtml_a06cac66872538895dd6b59cdf39173d2"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a06cac66872538895dd6b59cdf39173d2">armnn::optimizations::ConvertConstantsHalfToFloat</a></div><div class="ttdeci">ConvertConstants< Float16ToFloat32, IsFloat32Layer > ConvertConstantsHalfToFloat</div><div class="ttdef"><b>Definition:</b> <a href="_convert_constants_8hpp_source.xhtml#l00100">ConvertConstants.hpp:100</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="classarmnn_1_1_network_xhtml_abd4965a5d1d28a91b975e6b0eef024c8"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#abd4965a5d1d28a91b975e6b0eef024c8">armnn::Network::AddBatchNormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddBatchNormalizationLayer(const BatchNormalizationDescriptor &desc, const ConstTensor &mean, const ConstTensor &variance, const ConstTensor &beta, const ConstTensor &gamma, const char *name=nullptr) override</div><div class="ttdoc">Adds a batch normalization layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01315">Network.cpp:1315</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="classarmnn_1_1_subgraph_view_selector_xhtml_a3730b0a6006f0d87f894a44e01869d90"><div class="ttname"><a href="classarmnn_1_1_subgraph_view_selector.xhtml#a3730b0a6006f0d87f894a44e01869d90">armnn::SubgraphViewSelector::SelectSubgraphs</a></div><div class="ttdeci">static Subgraphs SelectSubgraphs(Graph &graph, const LayerSelectorFunction &selector)</div><div class="ttdoc">Selects subgraphs from a graph based on the selector function and the algorithm. </div><div class="ttdef"><b>Definition:</b> <a href="_subgraph_view_selector_8cpp_source.xhtml#l00254">SubgraphViewSelector.cpp:254</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a1a3c9903dcd90a7f40d8aca0c339501f"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a1a3c9903dcd90a7f40d8aca0c339501f">armnn::Network::AddBatchToSpaceNdLayer</a></div><div class="ttdeci">IConnectableLayer * AddBatchToSpaceNdLayer(const BatchToSpaceNdDescriptor &batchToSpaceNdDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a batch to space ND layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01046">Network.cpp:1046</a></div></div> +<div class="ttc" id="classarmnn_1_1_l2_normalization_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_l2_normalization_layer.xhtml">armnn::L2NormalizationLayer</a></div><div class="ttdoc">This layer represents a L2 normalization operation. </div><div class="ttdef"><b>Definition:</b> <a href="_l2_normalization_layer_8hpp_source.xhtml#l00013">L2NormalizationLayer.hpp:13</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a1ec6b4c20ed294a96cf94c33c24caaf5"><div class="ttname"><a href="namespacearmnn.xhtml#a1ec6b4c20ed294a96cf94c33c24caaf5">armnn::CreateSupportedBackends</a></div><div class="ttdeci">BackendsMap CreateSupportedBackends(TensorHandleFactoryRegistry &handleFactoryRegistry, BackendSettings &backendSettings)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00409">Network.cpp:409</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_ae1509d340bc981b11101c3316ee8afd6"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#ae1509d340bc981b11101c3316ee8afd6">armnn::optimizations::OptimizeInverseConversionsFp32</a></div><div class="ttdeci">OptimizeForConnection< ConvertFp32ToFp16Layer, ConvertFp16ToFp32Layer, OptimizeInverseConversionsImpl > OptimizeInverseConversionsFp32</div><div class="ttdef"><b>Definition:</b> <a href="_optimize_inverse_conversions_8hpp_source.xhtml#l00044">OptimizeInverseConversions.hpp:44</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_accb1637c58e1523f740025e0d0e7c6dd"><div class="ttname"><a href="namespacearmnn.xhtml#accb1637c58e1523f740025e0d0e7c6dd">armnn::CalculateSlotOptionForInput</a></div><div class="ttdeci">ITensorHandleFactory::FactoryId CalculateSlotOptionForInput(BackendsMap &backends, OutputSlot &slot, TensorHandleFactoryRegistry &registry)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00546">Network.cpp:546</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="_exceptions_8hpp_xhtml"><div class="ttname"><a href="_exceptions_8hpp.xhtml">Exceptions.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_backend_id_xhtml_af7445617163d3f07c47b92ae56c6cf8b"><div class="ttname"><a href="classarmnn_1_1_backend_id.xhtml#af7445617163d3f07c47b92ae56c6cf8b">armnn::BackendId::Get</a></div><div class="ttdeci">const std::string & Get() const</div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.xhtml#l00136">BackendId.hpp:136</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_optimized_network_xhtml_a6201b0b0af2110feee1489a5fe9c7ec2"><div class="ttname"><a href="classarmnn_1_1_optimized_network.xhtml#a6201b0b0af2110feee1489a5fe9c7ec2">armnn::OptimizedNetwork::SerializeToDot</a></div><div class="ttdeci">Status SerializeToDot(std::ostream &stream) const override</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00070">Network.cpp:70</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00018">ITensorHandleFactory.hpp:18</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_adb60c75544796e23d7abc1ce0476f6d9"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#adb60c75544796e23d7abc1ce0476f6d9">armnn::Network::AddAdditionLayer</a></div><div class="ttdeci">IConnectableLayer * AddAdditionLayer(const char *name=nullptr) override</div><div class="ttdoc">Adds an addition layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01300">Network.cpp:1300</a></div></div> +<div class="ttc" id="structarmnn_1_1_backend_settings_xhtml_aa09ac75b83067c5ed455f2bb35c7c98d"><div class="ttname"><a href="structarmnn_1_1_backend_settings.xhtml#aa09ac75b83067c5ed455f2bb35c7c98d">armnn::BackendSettings::m_SelectedBackends</a></div><div class="ttdeci">BackendIdSet m_SelectedBackends</div><div class="ttdef"><b>Definition:</b> <a href="_backend_settings_8hpp_source.xhtml#l00021">BackendSettings.hpp:21</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a224ea587dd10d2aa0d019be5c9de4b89"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a224ea587dd10d2aa0d019be5c9de4b89">armnn::Network::AddDequantizeLayer</a></div><div class="ttdeci">IConnectableLayer * AddDequantizeLayer(const char *name=nullptr) override</div><div class="ttdoc">Adds a Dequantize layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01549">Network.cpp:1549</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a63e34dd3e41262e750f7a54de8ca81d1"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a63e34dd3e41262e750f7a54de8ca81d1">armnn::QuantizedLstmInputParams::GetRecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensor & GetRecurrentToCellWeights() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00088">QuantizedLstmParams.hpp:88</a></div></div> +<div class="ttc" id="_network_8hpp_xhtml"><div class="ttname"><a href="_network_8hpp.xhtml">Network.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a9e234ae3b84213cb9fce636cfc2302bb"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a9e234ae3b84213cb9fce636cfc2302bb">armnn::Network::AddSpaceToBatchNdLayer</a></div><div class="ttdeci">IConnectableLayer * AddSpaceToBatchNdLayer(const SpaceToBatchNdDescriptor &spaceToBatchNdDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a space to batch layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01383">Network.cpp:1383</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56f168327453ea4461cbc1c0ac7f15b6"><div class="ttname"><a href="namespacearmnn.xhtml#a56f168327453ea4461cbc1c0ac7f15b6">armnn::AttemptBackendAssignment</a></div><div class="ttdeci">OptimizationResult AttemptBackendAssignment(BackendSettings &backendSettings, Graph &graph, Layer *layer, BackendId backend, DataType dataTypeIn, DataType dataTypeOut, const std::vector< BackendId > &availablePreferredBackends, std::string &reasonIfUnsupported, Optional< std::vector< std::string > &> errMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00149">Network.cpp:149</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a339c19855613274cf0ea13921af9e5a3"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a339c19855613274cf0ea13921af9e5a3">armnn::QuantizedLstmInputParams::GetInputToForgetWeights</a></div><div class="ttdeci">const ConstTensor & GetInputToForgetWeights() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00063">QuantizedLstmParams.hpp:63</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_handle_factory_registry_xhtml_ae5ecc42140a12c855554a4a621fc8456"><div class="ttname"><a href="classarmnn_1_1_tensor_handle_factory_registry.xhtml#ae5ecc42140a12c855554a4a621fc8456">armnn::TensorHandleFactoryRegistry::GetFactory</a></div><div class="ttdeci">ITensorHandleFactory * GetFactory(ITensorHandleFactory::FactoryId id) const</div><div class="ttdoc">Find a TensorHandleFactory by Id Returns nullptr if not found. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_factory_registry_8cpp_source.xhtml#l00039">TensorHandleFactoryRegistry.cpp:39</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00058">Layer.cpp:58</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_abf67dfbce354d772111fc5e5d4cd850d"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#abf67dfbce354d772111fc5e5d4cd850d">armnn::Network::AddAbsLayer</a></div><div class="ttdeci">IConnectableLayer * AddAbsLayer(const char *name=nullptr) override</div><div class="ttdoc">Add absolute layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01295">Network.cpp:1295</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_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="classarmnn_1_1_i_tensor_handle_factory_xhtml_a32f4aa6a7089d877af08928139c2c277"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">armnn::ITensorHandleFactory::FactoryId</a></div><div class="ttdeci">std::string FactoryId</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00021">ITensorHandleFactory.hpp:21</a></div></div> +<div class="ttc" id="classarmnn_1_1_division_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_division_layer.xhtml">armnn::DivisionLayer</a></div><div class="ttdoc">This layer represents a division operation. </div><div class="ttdef"><b>Definition:</b> <a href="_division_layer_8hpp_source.xhtml#l00014">DivisionLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_layer_visitor.xhtml">armnn::ILayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_layer_visitor_8hpp_source.xhtml#l00016">ILayerVisitor.hpp:16</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_ad445d732cda17f0a552fa916f59fed8d"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ad445d732cda17f0a552fa916f59fed8d">armnn::Network::AddSliceLayer</a></div><div class="ttdeci">IConnectableLayer * AddSliceLayer(const SliceDescriptor &sliceDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a slice layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01262">Network.cpp:1262</a></div></div> +<div class="ttc" id="classarmnn_1_1_strided_slice_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_strided_slice_layer.xhtml">armnn::StridedSliceLayer</a></div><div class="ttdoc">This layer represents a strided slice operation. </div><div class="ttdef"><b>Definition:</b> <a href="_strided_slice_layer_8hpp_source.xhtml#l00013">StridedSliceLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_aaef29472862381822654ab6cbf7cba2a"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00259">Layer.hpp:259</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_aad4a7bebcdaeeea663429cbd47b2917e"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#aad4a7bebcdaeeea663429cbd47b2917e">armnn::Network::AddGreaterLayer</a></div><div class="ttdeci">IConnectableLayer * AddGreaterLayer(const char *name=nullptr) override</div><div class="ttdoc">Add a Greater layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01560">Network.cpp:1560</a></div></div> +<div class="ttc" id="classarmnn_1_1_maximum_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_maximum_layer.xhtml">armnn::MaximumLayer</a></div><div class="ttdoc">This layer represents a maximum operation. </div><div class="ttdef"><b>Definition:</b> <a href="_maximum_layer_8hpp_source.xhtml#l00014">MaximumLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_ad2e53e6428416a65ae4ba566207cc6bf"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ad2e53e6428416a65ae4ba566207cc6bf">armnn::QuantizedLstmInputParams::GetRecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensor & GetRecurrentToInputWeights() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00078">QuantizedLstmParams.hpp:78</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_ac9758a0b2749095fd2a7ac152ff8fd49"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ac9758a0b2749095fd2a7ac152ff8fd49">armnn::Network::AddMergerLayer</a></div><div class="ttdeci">IConnectableLayer * AddMergerLayer(const MergerDescriptor &mergerDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a concat layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01289">Network.cpp:1289</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a86d19da62b6cfed3928f6fe7026f22fa"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a86d19da62b6cfed3928f6fe7026f22fa">armnn::optimizations::Fp32NetworkToFp16Converter</a></div><div class="ttdeci">OptimizeForType< Layer, ConvertFp32NetworkToFp16Impl > Fp32NetworkToFp16Converter</div><div class="ttdef"><b>Definition:</b> <a href="_convert_fp32_network_to_fp16_8hpp_source.xhtml#l00078">ConvertFp32NetworkToFp16.hpp:78</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_aa1ee88eebe67898c50a4ca259de49bbc"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#aa1ee88eebe67898c50a4ca259de49bbc">armnn::Network::AddResizeLayer</a></div><div class="ttdeci">IConnectableLayer * AddResizeLayer(const ResizeDescriptor &resizeDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a resize layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01344">Network.cpp:1344</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a8b2e7eb34ad5aacda72260f77fd880ce"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a8b2e7eb34ad5aacda72260f77fd880ce">armnn::Network::AddConstantLayer</a></div><div class="ttdeci">IConnectableLayer * AddConstantLayer(const ConstTensor &input, const char *name=nullptr) override</div><div class="ttdoc">Adds a layer with no inputs and a single output, which always corresponds to the passed in constant t...</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01368">Network.cpp:1368</a></div></div> +<div class="ttc" id="classarmnn_1_1_prelu_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_prelu_layer.xhtml">armnn::PreluLayer</a></div><div class="ttdef"><b>Definition:</b> <a href="_prelu_layer_8hpp_source.xhtml#l00014">PreluLayer.hpp:14</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_network_xhtml_a6e6cb8fd00cb855c4f0d93c4a7a2bde2"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a6e6cb8fd00cb855c4f0d93c4a7a2bde2">armnn::Network::AddMultiplicationLayer</a></div><div class="ttdeci">IConnectableLayer * AddMultiplicationLayer(const char *name=nullptr) override</div><div class="ttdoc">Adds a multiplication layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01305">Network.cpp:1305</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a52fab7cec34e1fa77df68503e0c0ce59"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a52fab7cec34e1fa77df68503e0c0ce59">armnn::Network::AddComparisonLayer</a></div><div class="ttdeci">IConnectableLayer * AddComparisonLayer(const ComparisonDescriptor &comparisonDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Add a Comparison layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01052">Network.cpp:1052</a></div></div> +<div class="ttc" id="classarmnn_1_1_subgraph_view_xhtml_a2fc512b3ddb7bb2cdf02f44038ca2500"><div class="ttname"><a href="classarmnn_1_1_subgraph_view.xhtml#a2fc512b3ddb7bb2cdf02f44038ca2500">armnn::SubgraphView::begin</a></div><div class="ttdeci">Iterator begin()</div><div class="ttdef"><b>Definition:</b> <a href="_subgraph_view_8cpp_source.xhtml#l00164">SubgraphView.cpp:164</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a38e626422579decc13e3ee37da1a84c9"><div class="ttname"><a href="namespacearmnn.xhtml#a38e626422579decc13e3ee37da1a84c9">armnn::ReportWarning</a></div><div class="ttdeci">void ReportWarning(const std::string &warningMessage, Optional< std::vector< std::string > &> warningMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00087">Network.cpp:87</a></div></div> +<div class="ttc" id="classarmnn_1_1_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml">armnn::Convolution2dLayer</a></div><div class="ttdoc">This layer represents a convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.xhtml#l00015">Convolution2dLayer.hpp:15</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a84f86b4de5adf0b164e811c87051a0ee"><div class="ttname"><a href="namespacearmnn.xhtml#a84f86b4de5adf0b164e811c87051a0ee">armnn::CheckFlag</a></div><div class="ttdeci">bool CheckFlag(MemorySourceFlags flags, MemorySource source)</div><div class="ttdef"><b>Definition:</b> <a href="_memory_sources_8hpp_source.xhtml#l00047">MemorySources.hpp:47</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00275">Tensor.cpp:275</a></div></div> +<div class="ttc" id="classarmnn_1_1_mean_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_mean_layer.xhtml">armnn::MeanLayer</a></div><div class="ttdoc">This layer represents a mean operation. </div><div class="ttdef"><b>Definition:</b> <a href="_mean_layer_8hpp_source.xhtml#l00014">MeanLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_comparison_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_comparison_layer.xhtml">armnn::ComparisonLayer</a></div><div class="ttdoc">This layer represents a comparison operation. </div><div class="ttdef"><b>Definition:</b> <a href="_comparison_layer_8hpp_source.xhtml#l00014">ComparisonLayer.hpp:14</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_1_1_network_xhtml_a942922c1213c451e3286fb5cd31c6499"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a942922c1213c451e3286fb5cd31c6499">armnn::Network::AddNormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddNormalizationLayer(const NormalizationDescriptor &normalizationDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a normalization layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01255">Network.cpp:1255</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::DepthwiseConvolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.xhtml#l00019">DepthwiseConvolution2dLayer.hpp:19</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="classarmnn_1_1_merge_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_merge_layer.xhtml">armnn::MergeLayer</a></div><div class="ttdoc">This layer dequantizes the input tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_merge_layer_8hpp_source.xhtml#l00013">MergeLayer.hpp:13</a></div></div> +<div class="ttc" id="_file_only_profiling_decorator_tests_8cpp_xhtml_a6560146509197f3e197d8d36f76c1347"><div class="ttname"><a href="_file_only_profiling_decorator_tests_8cpp.xhtml#a6560146509197f3e197d8d36f76c1347">options</a></div><div class="ttdeci">armnn::Runtime::CreationOptions::ExternalProfilingOptions options</div><div class="ttdef"><b>Definition:</b> <a href="_file_only_profiling_decorator_tests_8cpp_source.xhtml#l00045">FileOnlyProfilingDecoratorTests.cpp:45</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="structarmnn_1_1_backend_settings_xhtml"><div class="ttname"><a href="structarmnn_1_1_backend_settings.xhtml">armnn::BackendSettings</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_settings_8hpp_source.xhtml#l00017">BackendSettings.hpp:17</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="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="classarmnn_1_1_network_xhtml_aff9921f194908a3c35015de701723234"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#aff9921f194908a3c35015de701723234">armnn::Network::AddPermuteLayer</a></div><div class="ttdeci">IConnectableLayer * AddPermuteLayer(const PermuteDescriptor &permuteDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a permute layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01231">Network.cpp:1231</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="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="classarmnn_1_1_multiplication_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_multiplication_layer.xhtml">armnn::MultiplicationLayer</a></div><div class="ttdoc">This layer represents a multiplication operation. </div><div class="ttdef"><b>Definition:</b> <a href="_multiplication_layer_8hpp_source.xhtml#l00014">MultiplicationLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_ac3d4632a58d626521765246bbfdeadcf"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ac3d4632a58d626521765246bbfdeadcf">armnn::Network::AddGatherLayer</a></div><div class="ttdeci">IConnectableLayer * AddGatherLayer(const char *name=nullptr) override</div><div class="ttdoc">Add Gather layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01575">Network.cpp:1575</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a8b1fbac089170c35fcb98d7012859428"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a8b1fbac089170c35fcb98d7012859428">armnn::Network::AddSoftmaxLayer</a></div><div class="ttdeci">IConnectableLayer * AddSoftmaxLayer(const SoftmaxDescriptor &softmaxDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a softmax layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01267">Network.cpp:1267</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_ab1569dbf88b6511bde91bee3224a558c"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ab1569dbf88b6511bde91bee3224a558c">armnn::Network::AddLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddLstmLayer(const LstmDescriptor &descriptor, const LstmInputParams &params, const char *name=nullptr) override</div><div class="ttdoc">Add a Lstm layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01400">Network.cpp:1400</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_bilinear_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_resize_bilinear_descriptor.xhtml">armnn::ResizeBilinearDescriptor</a></div><div class="ttdoc">A ResizeBilinearDescriptor for the ResizeBilinearLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00707">Descriptors.hpp:707</a></div></div> +<div class="ttc" id="_subgraph_view_selector_8hpp_xhtml"><div class="ttname"><a href="_subgraph_view_selector_8hpp.xhtml">SubgraphViewSelector.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a99093f440e7e0ba4c8dcc90c3ec8cf4d"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a99093f440e7e0ba4c8dcc90c3ec8cf4d">armnn::Network::AddElementwiseUnaryLayer</a></div><div class="ttdeci">IConnectableLayer * AddElementwiseUnaryLayer(const ElementwiseUnaryDescriptor &elementwiseUnaryDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Add an ElementwiseUnary layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01058">Network.cpp:1058</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00063">Layer.cpp:63</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a47d30afdd251fef00a59d2234cca0020"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a47d30afdd251fef00a59d2234cca0020">armnn::Network::AddDivisionLayer</a></div><div class="ttdeci">IConnectableLayer * AddDivisionLayer(const char *name=nullptr) override</div><div class="ttdoc">Adds a division layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01524">Network.cpp:1524</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_optimized_network_xhtml_a58ee539cf95c1e99fe4f54ef6e8bbd05"><div class="ttname"><a href="classarmnn_1_1_i_optimized_network.xhtml#a58ee539cf95c1e99fe4f54ef6e8bbd05">armnn::IOptimizedNetwork::Destroy</a></div><div class="ttdeci">static void Destroy(IOptimizedNetwork *network)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00059">Network.cpp:59</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_ab17a7eb3afac8667ace153b0fe2f82fe"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ab17a7eb3afac8667ace153b0fe2f82fe">armnn::ITensorHandleFactory::GetImportFlags</a></div><div class="ttdeci">virtual MemorySourceFlags GetImportFlags() const</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00061">ITensorHandleFactory.hpp:61</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_basic_parameters_xhtml_a5a0d8af26a6aad1e5be521ea7dc550eb"><div class="ttname"><a href="structarmnn_1_1_lstm_basic_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">armnn::LstmBasicParameters::m_InputToForgetWeights</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_InputToForgetWeights</div><div class="ttdoc">A unique pointer to represent 2D weights tensor with dimensions [input_size, num_units]. </div><div class="ttdef"><b>Definition:</b> <a href="_lstm_layer_8hpp_source.xhtml#l00057">LstmLayer.hpp:57</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a9bf4cfcac428b1331ff83c45f1166665"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a9bf4cfcac428b1331ff83c45f1166665">armnn::Network::AddStridedSliceLayer</a></div><div class="ttdeci">IConnectableLayer * AddStridedSliceLayer(const StridedSliceDescriptor &stridedSliceDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds a strided slice layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01554">Network.cpp:1554</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="_tensor_handle_factory_registry_8hpp_xhtml"><div class="ttname"><a href="_tensor_handle_factory_registry_8hpp.xhtml">TensorHandleFactoryRegistry.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_backend_settings_xhtml_ae4f9f2c5e3b5cf694315f66cde5b33f0"><div class="ttname"><a href="structarmnn_1_1_backend_settings.xhtml#ae4f9f2c5e3b5cf694315f66cde5b33f0">armnn::BackendSettings::IsCpuRefUsed</a></div><div class="ttdeci">bool IsCpuRefUsed() const</div><div class="ttdef"><b>Definition:</b> <a href="_backend_settings_8hpp_source.xhtml#l00060">BackendSettings.hpp:60</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a6a6657fdd77cabea7a9e0a740635735e"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a6a6657fdd77cabea7a9e0a740635735e">armnn::Network::AddQuantizedLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddQuantizedLstmLayer(const QuantizedLstmInputParams &params, const char *name=nullptr) override</div><div class="ttdoc">Add a QuantizedLstm layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01636">Network.cpp:1636</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a706f7345af3f18f4b16e226a672214c6"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a706f7345af3f18f4b16e226a672214c6">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00049">Network.cpp:49</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a1691bf16df2cabf1a4b82aecbb021f31"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a1691bf16df2cabf1a4b82aecbb021f31">armnn::QuantizedLstmInputParams::GetOutputGateBias</a></div><div class="ttdeci">const ConstTensor & GetOutputGateBias() const</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00113">QuantizedLstmParams.hpp:113</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a9c95f90eb40e31f629e0e2947b8bc6f9"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9c95f90eb40e31f629e0e2947b8bc6f9">armnn::ITensorHandleFactory::LegacyFactoryId</a></div><div class="ttdeci">static const FactoryId LegacyFactoryId</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00022">ITensorHandleFactory.hpp:22</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a52cc1e062595108da0dfef4b200dabd7"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a52cc1e062595108da0dfef4b200dabd7">armnn::Network::AddDetectionPostProcessLayer</a></div><div class="ttdeci">IConnectableLayer * AddDetectionPostProcessLayer(const DetectionPostProcessDescriptor &descriptor, const ConstTensor &anchors, const char *name=nullptr) override</div><div class="ttdoc">Adds a Detection PostProcess layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01221">Network.cpp:1221</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="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +<div class="ttc" id="classarmnn_1_1_depth_to_space_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_depth_to_space_layer.xhtml">armnn::DepthToSpaceLayer</a></div><div class="ttdoc">This layer represents a DepthToSpace operation. </div><div class="ttdef"><b>Definition:</b> <a href="_depth_to_space_layer_8hpp_source.xhtml#l00014">DepthToSpaceLayer.hpp:14</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_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_a9173495a61a0092b5f38b855f02c3585"><div class="ttname"><a href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">armnn::BackendsMap</a></div><div class="ttdeci">std::map< BackendId, std::unique_ptr< class IBackendInternal > > BackendsMap</div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00305">Network.hpp:305</a></div></div> +<div class="ttc" id="_profiling_service_8hpp_xhtml"><div class="ttname"><a href="_profiling_service_8hpp.xhtml">ProfilingService.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_resize_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_resize_layer.xhtml">armnn::ResizeLayer</a></div><div class="ttdoc">This layer represents a resize operation. </div><div class="ttdef"><b>Definition:</b> <a href="_resize_layer_8hpp_source.xhtml#l00013">ResizeLayer.hpp:13</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="classarmnn_1_1_optimized_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_optimized_network.xhtml">armnn::OptimizedNetwork</a></div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00265">Network.hpp:265</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8hpp_source.xhtml#l00014">InternalTypes.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_backend_id_xhtml"><div class="ttname"><a href="classarmnn_1_1_backend_id.xhtml">armnn::BackendId</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.xhtml#l00075">BackendId.hpp:75</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_e0a84d05c80a2ef4231141dcbbeac5c8.xhtml">armnn</a></li><li class="navelem"><a class="el" href="_network_8cpp.xhtml">Network.cpp</a></li> + <li class="footer">Generated on Fri Mar 13 2020 16:09:08 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> +</div> +</body> +</html> |