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diff --git a/21.02/_network_8cpp_source.xhtml b/21.02/_network_8cpp_source.xhtml new file mode 100644 index 0000000000..221c2af710 --- /dev/null +++ b/21.02/_network_8cpp_source.xhtml @@ -0,0 +1,634 @@ +<!-- 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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">21.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_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 and Contributors. 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="_assert_8hpp.xhtml">armnn/utility/Assert.hpp</a>></span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</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="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include <<a class="code" href="_polymorphic_downcast_8hpp.xhtml">armnn/utility/PolymorphicDowncast.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 <<a class="code" href="_profiling_service_8hpp.xhtml">ProfilingService.hpp</a>></span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include <fcntl.h></span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include <algorithm></span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include <fstream></span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include <memory></span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include <algorithm></span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> </div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> {</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a2d936beb0fcf3c5d22ff332f0812b05e"> 41</a></span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a2d936beb0fcf3c5d22ff332f0812b05e">INetwork::INetwork</a>(<a class="code" href="namespacearmnn.xhtml#a4de71c3661093e5c4ae7775114f43413">NetworkOptions</a> networkOptions) : pNetworkImpl(new <a class="code" href="classarmnn_1_1_network_impl.xhtml">NetworkImpl</a>(networkOptions)) {}</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> <a class="code" href="classarmnn_1_1_i_network.xhtml#af760179196d57e2ddbc64b989fb72586">INetwork::~INetwork</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#aff3fde909d22ed157046682e70129259"> 45</a></span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_i_network.xhtml#aff3fde909d22ed157046682e70129259">INetwork::PrintGraph</a>()</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->PrintGraph();</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> }</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#aa6c1c42ea44777302e87ce0fad5ac510"> 50</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#aa6c1c42ea44777302e87ce0fad5ac510">INetwork::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="l00051"></a><span class="lineno"> 51</span> {</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddInputLayer(<span class="keywordtype">id</span>, name);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> }</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> </div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#adc8c1c505bca8233fe238b3b7fb80200"> 56</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#adc8c1c505bca8233fe238b3b7fb80200">INetwork::AddArgMinMaxLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">ArgMinMaxDescriptor</a>& desc,</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> {</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddArgMinMaxLayer(desc, name);</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> </div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#ac7dca3e9f2ab2f2c64b42fc59a67188a"> 63</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ac7dca3e9f2ab2f2c64b42fc59a67188a">INetwork::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="l00064"></a><span class="lineno"> 64</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> {</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddComparisonLayer(comparisonDescriptor, name);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> }</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> </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_i_network.xhtml#aea1059833739d3dccebb3a03ec35a1e6"> 70</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#aea1059833739d3dccebb3a03ec35a1e6">INetwork::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="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddConcatLayer(concatDescriptor, name);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> }</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a178a72bbf254eff34a807a5ca27cb61f"> 77</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a178a72bbf254eff34a807a5ca27cb61f">INetwork::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="l00078"></a><span class="lineno"> 78</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="l00079"></a><span class="lineno"> 79</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="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> {</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddConvolution2dLayer(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> }</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#abaf4646307d946a74c1bf7bdc8efb83b"> 86</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a178a72bbf254eff34a807a5ca27cb61f">INetwork::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="l00087"></a><span class="lineno"> 87</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="l00088"></a><span class="lineno"> 88</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> biases;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddConvolution2dLayer(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> }</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> </div><div class="line"><a name="l00095"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#aa54008a5c8e4916bd1da8e0923a2e049"> 95</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a178a72bbf254eff34a807a5ca27cb61f">INetwork::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="l00096"></a><span class="lineno"> 96</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="l00097"></a><span class="lineno"> 97</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="l00098"></a><span class="lineno"> 98</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name )</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> {</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddConvolution2dLayer(convolution2dDescriptor,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  weights,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<ConstTensor></a>(biases),</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  name);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> }</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00108"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#af1853466264ac187607c96b501a74e2b"> 108</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#af1853466264ac187607c96b501a74e2b">INetwork::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="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> {</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddDepthToSpaceLayer(depthToSpaceDescriptor, name);</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"> 114</span> </div><div class="line"><a name="l00115"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a58f85a122022527a525318473f93d4ef"> 115</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a58f85a122022527a525318473f93d4ef">INetwork::AddDepthwiseConvolution2dLayer</a>(</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</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="l00117"></a><span class="lineno"> 117</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="l00118"></a><span class="lineno"> 118</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="l00119"></a><span class="lineno"> 119</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> {</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddDepthwiseConvolution2dLayer(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> }</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </div><div class="line"><a name="l00125"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a02b981a246785121fd822a2eb996e716"> 125</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a58f85a122022527a525318473f93d4ef">INetwork::AddDepthwiseConvolution2dLayer</a>(</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</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="l00127"></a><span class="lineno"> 127</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="l00128"></a><span class="lineno"> 128</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> biases;</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddDepthwiseConvolution2dLayer(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> }</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#af326ea7544a5510e4d3465a3a842b4d4"> 135</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a58f85a122022527a525318473f93d4ef">INetwork::AddDepthwiseConvolution2dLayer</a>(</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</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="l00137"></a><span class="lineno"> 137</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="l00138"></a><span class="lineno"> 138</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="l00139"></a><span class="lineno"> 139</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> {</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddDepthwiseConvolution2dLayer(convolution2dDescriptor, weights,</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<ConstTensor></a>(biases), name);</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#a357aca04172ed22fa32e5a69122b0fec"> 146</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a357aca04172ed22fa32e5a69122b0fec">INetwork::AddDequantizeLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddDequantizeLayer(name);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> }</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div><div class="line"><a name="l00152"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#ac1134a94265293ea7347180260f787d2"> 152</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ac1134a94265293ea7347180260f787d2">INetwork::AddDetectionPostProcessLayer</a>(</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">DetectionPostProcessDescriptor</a>& descriptor,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</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>,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> {</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddDetectionPostProcessLayer(descriptor, anchors, name);</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> }</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> </div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a095a9b700dc857edc23c5d3bf088919f"> 161</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a095a9b700dc857edc23c5d3bf088919f">INetwork::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="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddElementwiseUnaryLayer(elementwiseUnaryDescriptor, name);</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> </div><div class="line"><a name="l00168"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#afc94c35c0bbe852a60046bf2e756b2e0"> 168</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#afc94c35c0bbe852a60046bf2e756b2e0">INetwork::AddFillLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fill_descriptor.xhtml">FillDescriptor</a>& fillDescriptor,</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> {</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddFillLayer(fillDescriptor, name);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> }</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> </div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div><div class="line"><a name="l00175"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#ae3ef3b97542241d331a38613ae189f3e"> 175</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ae3ef3b97542241d331a38613ae189f3e">INetwork::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="l00176"></a><span class="lineno"> 176</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="l00177"></a><span class="lineno"> 177</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="l00178"></a><span class="lineno"> 178</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> {</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddFullyConnectedLayer(fullyConnectedDescriptor, weights, biases, name);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> }</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00183"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a44349b3cf3ff8d476d5f930946e89c47"> 183</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ae3ef3b97542241d331a38613ae189f3e">INetwork::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="l00184"></a><span class="lineno"> 184</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="l00185"></a><span class="lineno"> 185</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> {</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> biases;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddFullyConnectedLayer(fullyConnectedDescriptor, weights, biases, name);</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> </div><div class="line"><a name="l00191"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a5811dfe93a4938dbbc9e8dd266e339de"> 191</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ae3ef3b97542241d331a38613ae189f3e">INetwork::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="l00192"></a><span class="lineno"> 192</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="l00193"></a><span class="lineno"> 193</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="l00194"></a><span class="lineno"> 194</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> {</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddFullyConnectedLayer(fullyConnectedDescriptor, weights,</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<ConstTensor></a>(biases), name);</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> }</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div><div class="line"><a name="l00200"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a11f49d84f0cfd8df65f4d5206cd43b6d"> 200</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a11f49d84f0cfd8df65f4d5206cd43b6d">INetwork::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="l00201"></a><span class="lineno"> 201</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> {</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddPermuteLayer(permuteDescriptor, name);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> }</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> </div><div class="line"><a name="l00206"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a9a9bcc00ae3d96343c93b437d6f77088"> 206</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a9a9bcc00ae3d96343c93b437d6f77088">INetwork::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="l00207"></a><span class="lineno"> 207</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> {</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddBatchToSpaceNdLayer(batchToSpaceNdDescriptor, name);</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> }</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> </div><div class="line"><a name="l00212"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#ae913b4351b7027f37eb5657dd7867733"> 212</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ae913b4351b7027f37eb5657dd7867733">INetwork::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="l00213"></a><span class="lineno"> 213</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddPooling2dLayer(pooling2dDescriptor, name);</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#aa51350bdd4976f3dd5a4e9d00a906b2c"> 218</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#aa51350bdd4976f3dd5a4e9d00a906b2c">INetwork::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="l00219"></a><span class="lineno"> 219</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> {</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddActivationLayer(activationDescriptor, name);</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> </div><div class="line"><a name="l00224"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a6c5376053e1f875776d7bc36fd0b7d45"> 224</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a6c5376053e1f875776d7bc36fd0b7d45">INetwork::AddNormalizationLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml">NormalizationDescriptor</a>& normalizationDescriptor,</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddNormalizationLayer(normalizationDescriptor, name);</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> </div><div class="line"><a name="l00230"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a8de6b047fcaff95df48dca683e1f3aa4"> 230</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a8de6b047fcaff95df48dca683e1f3aa4">INetwork::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="l00231"></a><span class="lineno"> 231</span> {</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddSliceLayer(sliceDescriptor, name);</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> }</div><div class="line"><a name="l00234"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a30528a3bd85a0dba158bd14e252bd68a"> 234</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a30528a3bd85a0dba158bd14e252bd68a">INetwork::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="l00235"></a><span class="lineno"> 235</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> {</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddSoftmaxLayer(softmaxDescriptor, name);</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#a6f6d81d8a4f1f85f3616e8306760061c"> 240</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a6f6d81d8a4f1f85f3616e8306760061c">INetwork::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="l00241"></a><span class="lineno"> 241</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> {</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddSplitterLayer(splitterDescriptor, name);</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> }</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> </div><div class="line"><a name="l00246"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a0f19808bdada45222e72edf7671a275a"> 246</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a0f19808bdada45222e72edf7671a275a">INetwork::AddMergeLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddMergeLayer(name);</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#a34aa5f1a405a6886f79c97d53f9f65fd"> 251</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a34aa5f1a405a6886f79c97d53f9f65fd">INetwork::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="l00252"></a><span class="lineno"> 252</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> {</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddConcatLayer(mergerDescriptor, name);</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> }</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> </div><div class="line"><a name="l00257"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a030e8e7c1f6980ec9b2ac06b683ee74e"> 257</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a030e8e7c1f6980ec9b2ac06b683ee74e">INetwork::AddAbsLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> {</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddElementwiseUnaryLayer(<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="l00260"></a><span class="lineno"> 260</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#a39f1b38d89c4de186742eafcbb3b1319"> 262</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a39f1b38d89c4de186742eafcbb3b1319">INetwork::AddAdditionLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddAdditionLayer(name);</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#abb59f6ba9988dae88e0f48e68d87fc32"> 267</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#abb59f6ba9988dae88e0f48e68d87fc32">INetwork::AddMultiplicationLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> {</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddMultiplicationLayer(name);</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> }</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a8f798e19187ac7ae6ae6153ee64ab645"> 272</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a8f798e19187ac7ae6ae6153ee64ab645">INetwork::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="l00273"></a><span class="lineno"> 273</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="l00274"></a><span class="lineno"> 274</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="l00275"></a><span class="lineno"> 275</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="l00276"></a><span class="lineno"> 276</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="l00277"></a><span class="lineno"> 277</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> {</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddBatchNormalizationLayer(desc, mean, variance, beta, gamma, name);</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> }</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> </div><div class="line"><a name="l00282"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a25563024ec66627ee83727244a53e944"> 282</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a25563024ec66627ee83727244a53e944">INetwork::AddRankLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddRankLayer(name);</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> }</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div><div class="line"><a name="l00287"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#acc9f9b91636c0714d96a3cba92c624f9"> 287</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#acc9f9b91636c0714d96a3cba92c624f9">INetwork::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="l00288"></a><span class="lineno"> 288</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> {</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">ResizeDescriptor</a> resizeDescriptor;</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</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="l00292"></a><span class="lineno"> 292</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="l00293"></a><span class="lineno"> 293</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="l00294"></a><span class="lineno"> 294</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="l00295"></a><span class="lineno"> 295</span>  resizeDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#ae1a4b3b6c60552509b89747cebb900a2">m_AlignCorners</a> = descriptor.<a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#ae1a4b3b6c60552509b89747cebb900a2">m_AlignCorners</a>;</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  resizeDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a4022d5107338aaf5eb7abebf78a1360b">m_HalfPixelCenters</a> = descriptor.<a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#a4022d5107338aaf5eb7abebf78a1360b">m_HalfPixelCenters</a>;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> </div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddResizeLayer(resizeDescriptor, name);</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> }</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> </div><div class="line"><a name="l00301"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#ad97411f1fcb2c30c212483d8c673506f"> 301</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ad97411f1fcb2c30c212483d8c673506f">INetwork::AddResizeLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">ResizeDescriptor</a>& resizeDescriptor,</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddResizeLayer(resizeDescriptor, name);</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> }</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> </div><div class="line"><a name="l00307"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#ae0cfae1ea51669892608a1a060d24fa0"> 307</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ae0cfae1ea51669892608a1a060d24fa0">INetwork::AddReduceLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_reduce_descriptor.xhtml">ReduceDescriptor</a>& reduceDescriptor,</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> {</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddReduceLayer(reduceDescriptor, name);</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#abd61d3e7ab67551c75bc219bbc4baeb5"> 313</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#abd61d3e7ab67551c75bc219bbc4baeb5">INetwork::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="l00314"></a><span class="lineno"> 314</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> {</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddInstanceNormalizationLayer(desc, name);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> }</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> </div><div class="line"><a name="l00319"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#aaff51346dadec2c1430abf007fed4cc9"> 319</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#aaff51346dadec2c1430abf007fed4cc9">INetwork::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="l00320"></a><span class="lineno"> 320</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> {</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddL2NormalizationLayer(desc, name);</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> }</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> </div><div class="line"><a name="l00325"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a83b33973ca12078166b2436b313627b9"> 325</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a83b33973ca12078166b2436b313627b9">INetwork::AddLogSoftmaxLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml">LogSoftmaxDescriptor</a>& logSoftmaxDescriptor,</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> {</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddLogSoftmaxLayer(logSoftmaxDescriptor, name);</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#a1aa567f46c30960851c02847dc7b4215"> 331</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a1aa567f46c30960851c02847dc7b4215">INetwork::AddConstantLayer</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& input,</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddConstantLayer(input, name);</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> }</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> </div><div class="line"><a name="l00337"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a8a3380be13fba749fc4208214b049347"> 337</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a8a3380be13fba749fc4208214b049347">INetwork::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="l00338"></a><span class="lineno"> 338</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddReshapeLayer(reshapeDescriptor, name);</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> }</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span> </div><div class="line"><a name="l00343"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a72b9d30e9d555bb5c35460b62faedf0d"> 343</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a72b9d30e9d555bb5c35460b62faedf0d">INetwork::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="l00344"></a><span class="lineno"> 344</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> {</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddSpaceToBatchNdLayer(spaceToBatchNdDescriptor, name);</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> }</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span> </div><div class="line"><a name="l00349"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a19bad0cc50526ca9f4f84a688812cdf5"> 349</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a19bad0cc50526ca9f4f84a688812cdf5">INetwork::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="l00350"></a><span class="lineno"> 350</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddSpaceToDepthLayer(spaceToDepthDescriptor, name);</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> }</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> </div><div class="line"><a name="l00355"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a435ea88480b8645026dd45fd692663a1"> 355</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a435ea88480b8645026dd45fd692663a1">INetwork::AddFloorLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> {</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddFloorLayer(name);</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> }</div><div class="line"><a name="l00359"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#af5790069aa11fd1c5bb2e17cecb06528"> 359</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#af5790069aa11fd1c5bb2e17cecb06528">INetwork::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="l00360"></a><span class="lineno"> 360</span> {</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddOutputLayer(<span class="keywordtype">id</span>, name);</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#a0a2fdd4f442952c97a8f24de6700473a"> 364</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a0a2fdd4f442952c97a8f24de6700473a">INetwork::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="l00365"></a><span class="lineno"> 365</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="l00366"></a><span class="lineno"> 366</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddLstmLayer(descriptor, params, name);</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span> }</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> </div><div class="line"><a name="l00371"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a0aeb4e528cf6ba4b7caca14a94fbcafe"> 371</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a0aeb4e528cf6ba4b7caca14a94fbcafe">INetwork::AddDivisionLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> {</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddDivisionLayer(name);</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> }</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> </div><div class="line"><a name="l00376"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#af13795cdf49e63d8bc3cb409592cdb9d"> 376</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#af13795cdf49e63d8bc3cb409592cdb9d">INetwork::AddSubtractionLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> {</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddSubtractionLayer(name);</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> }</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div><div class="line"><a name="l00381"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a57590d7777211673d2052f702f0b07a1"> 381</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a57590d7777211673d2052f702f0b07a1">INetwork::AddMaximumLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> {</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddMaximumLayer(name);</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> </div><div class="line"><a name="l00386"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#ad4726f9b7dd11db250d2a494a8a39494"> 386</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ad4726f9b7dd11db250d2a494a8a39494">INetwork::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="l00387"></a><span class="lineno"> 387</span> {</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddMeanLayer(meanDescriptor, name);</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"><a class="line" href="classarmnn_1_1_i_network.xhtml#a6e2df484ecc65bc82712590b96e04df4"> 391</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a6e2df484ecc65bc82712590b96e04df4">INetwork::AddPadLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_pad_descriptor.xhtml">PadDescriptor</a>& padDescriptor,</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddPadLayer(padDescriptor, name);</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> }</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span> </div><div class="line"><a name="l00397"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a0b426a3feffc76e66d73b5761806e899"> 397</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a0b426a3feffc76e66d73b5761806e899">INetwork::AddQuantizeLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span> {</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddQuantizeLayer(name);</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span> }</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> </div><div class="line"><a name="l00402"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#ac5c93cad39a690af862d49ffaec0d3c0"> 402</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ac5c93cad39a690af862d49ffaec0d3c0">INetwork::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="l00403"></a><span class="lineno"> 403</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> {</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddStridedSliceLayer(stridedSliceDescriptor, name);</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span> }</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span> </div><div class="line"><a name="l00408"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a4bfd8dee1a0315b651e977c672c0847c"> 408</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a4bfd8dee1a0315b651e977c672c0847c">INetwork::AddMinimumLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> {</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddMinimumLayer(name);</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> }</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span> </div><div class="line"><a name="l00413"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a9fcd8cc35c8ae7d092705e7c4c2a7c69"> 413</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a9fcd8cc35c8ae7d092705e7c4c2a7c69">INetwork::AddGreaterLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> {</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddComparisonLayer(<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="l00416"></a><span class="lineno"> 416</span> }</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> </div><div class="line"><a name="l00418"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a7ba52238d75f06ff59a0d2ba613acefe"> 418</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a7ba52238d75f06ff59a0d2ba613acefe">INetwork::AddEqualLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddComparisonLayer(<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="l00421"></a><span class="lineno"> 421</span> }</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span> </div><div class="line"><a name="l00423"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#ae2f5193942457daafa733998f3e61449"> 423</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ae2f5193942457daafa733998f3e61449">INetwork::AddRsqrtLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddElementwiseUnaryLayer(<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="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="classarmnn_1_1_i_network.xhtml#a31f19249d1491464736b08b967be68b4"> 428</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a31f19249d1491464736b08b967be68b4">INetwork::AddGatherLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span> {</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">GatherDescriptor</a> gatherDescriptor{};</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddGatherLayer(gatherDescriptor, name);</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> </div><div class="line"><a name="l00434"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a1da203a7e3caa6ae4f0630a4758aac55"> 434</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a31f19249d1491464736b08b967be68b4">INetwork::AddGatherLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">GatherDescriptor</a>& descriptor,</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddGatherLayer(descriptor, name);</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> }</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span> </div><div class="line"><a name="l00440"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a26e69cda5fe9642f9198c24ae5fdf9bc"> 440</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a26e69cda5fe9642f9198c24ae5fdf9bc">INetwork::AddSwitchLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span> {</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddSwitchLayer(name);</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span> }</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span> </div><div class="line"><a name="l00445"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a6d614a503a34ea3712b388aa4340ddbe"> 445</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a6d614a503a34ea3712b388aa4340ddbe">INetwork::AddPreluLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span> {</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddPreluLayer(name);</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span> }</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span> </div><div class="line"><a name="l00450"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a41fd7b56923d5625bac2cbfebed1a393"> 450</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a41fd7b56923d5625bac2cbfebed1a393">INetwork::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="l00451"></a><span class="lineno"> 451</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="l00452"></a><span class="lineno"> 452</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="l00453"></a><span class="lineno"> 453</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span> {</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddTransposeConvolution2dLayer(descriptor, weights, biases, name);</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> }</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span> </div><div class="line"><a name="l00458"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#ab067ba4ee9416d93abb8a52f3dc8feba"> 458</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#ab067ba4ee9416d93abb8a52f3dc8feba">INetwork::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="l00459"></a><span class="lineno"> 459</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddTransposeLayer(transposeDescriptor, name);</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span> }</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span> </div><div class="line"><a name="l00464"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a5210b3df77e7a51ab369b577de821aa2"> 464</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a5210b3df77e7a51ab369b577de821aa2">INetwork::AddStackLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">StackDescriptor</a>& descriptor,</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span> {</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddStackLayer(descriptor, name);</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> </div><div class="line"><a name="l00470"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a74894d085e78ff80f45fc09dd2381f08"> 470</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a74894d085e78ff80f45fc09dd2381f08">INetwork::AddStandInLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml">StandInDescriptor</a>& descriptor,</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span> {</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddStandInLayer(descriptor, name);</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span> }</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span> </div><div class="line"><a name="l00476"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a40067b05f30a3ab65568c826df7a8ea7"> 476</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a40067b05f30a3ab65568c826df7a8ea7">INetwork::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="l00477"></a><span class="lineno"> 477</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span> {</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddQuantizedLstmLayer(params, name);</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span> }</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span> </div><div class="line"><a name="l00482"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a2acbae0b9e98c94b843677484775c86a"> 482</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a2acbae0b9e98c94b843677484775c86a">INetwork::AddQLstmLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml">QLstmDescriptor</a>& descriptor,</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</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="l00484"></a><span class="lineno"> 484</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span> {</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddQLstmLayer(descriptor, params, name);</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span> }</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span> </div><div class="line"><a name="l00489"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a7dfc9717e76257867ad0a9239f210df0"> 489</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_i_network.xhtml#a7dfc9717e76257867ad0a9239f210df0">INetwork::AddLogicalBinaryLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_logical_binary_descriptor.xhtml">LogicalBinaryDescriptor</a>& descriptor,</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span> {</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->AddLogicalBinaryLayer(descriptor, name);</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span> }</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span> </div><div class="line"><a name="l00495"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a1163a712898cd2c368ef2e4510fc36c3"> 495</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a1163a712898cd2c368ef2e4510fc36c3">INetwork::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="l00496"></a><span class="lineno"> 496</span> <span class="keyword"></span>{</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->Accept(visitor);</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span> }</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span> </div><div class="line"><a name="l00500"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a72032c65bf8b8acf09b564b7d80078c5"> 500</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a72032c65bf8b8acf09b564b7d80078c5">INetwork::ExecuteStrategy</a>(<a class="code" href="classarmnn_1_1_i_strategy.xhtml">IStrategy</a>& strategy)<span class="keyword"> const</span></div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span> <span class="keyword"></span>{</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->ExecuteStrategy(strategy);</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span> }</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span> </div><div class="line"><a name="l00505"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a230005513ac5eee1f3944b1960b6f2ed"> 505</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#a230005513ac5eee1f3944b1960b6f2ed">INetwork::CreateRaw</a>(<a class="code" href="namespacearmnn.xhtml#a4de71c3661093e5c4ae7775114f43413">NetworkOptions</a> networkOptions)</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span> {</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> <a class="code" href="classarmnn_1_1_i_network.xhtml#a2d936beb0fcf3c5d22ff332f0812b05e">INetwork</a>(networkOptions);</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span> }</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span> </div><div class="line"><a name="l00510"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b"> 510</a></span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>(<a class="code" href="namespacearmnn.xhtml#a4de71c3661093e5c4ae7775114f43413">NetworkOptions</a> networkOptions)</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span> {</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</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#a230005513ac5eee1f3944b1960b6f2ed">CreateRaw</a>(networkOptions), &<a class="code" href="classarmnn_1_1_i_network.xhtml#a55bd1bb29076dc45bb335e7322781463">INetwork::Destroy</a>);</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> </div><div class="line"><a name="l00515"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network.xhtml#a55bd1bb29076dc45bb335e7322781463"> 515</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="l00516"></a><span class="lineno"> 516</span> {</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <span class="keyword">delete</span> network;</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"><a class="line" href="classarmnn_1_1_i_optimized_network.xhtml#af730a6ec3deb072dc2687089f3f77f9e"> 521</a></span> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#af730a6ec3deb072dc2687089f3f77f9e">IOptimizedNetwork::IOptimizedNetwork</a>(std::unique_ptr<Graph> graph)</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  : pOptimizedNetworkImpl(new <a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml">OptimizedNetworkImpl</a>(<a class="code" href="namespacestd.xhtml">std</a>::move(graph))) {}</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span> </div><div class="line"><a name="l00524"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_optimized_network.xhtml#a5fd8b75db92fb2a84d12e2092a173716"> 524</a></span> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#af730a6ec3deb072dc2687089f3f77f9e">IOptimizedNetwork::IOptimizedNetwork</a>(std::unique_ptr<OptimizedNetworkImpl> impl)</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  : <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a374d52340ec8dc02a819acc20fb5aa92">pOptimizedNetworkImpl</a>(<a class="code" href="namespacestd.xhtml">std</a>::move(impl)) {}</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span> </div><div class="line"><a name="l00527"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_optimized_network.xhtml#a230acad28622c18ab32254f74af569b0"> 527</a></span> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#af730a6ec3deb072dc2687089f3f77f9e">IOptimizedNetwork::IOptimizedNetwork</a>(std::unique_ptr<Graph> graph, <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#a5b6893cda5b69359a4244c06054da18f">ModelOptions</a>& modelOptions)</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  : <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a374d52340ec8dc02a819acc20fb5aa92">pOptimizedNetworkImpl</a>(new <a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml">OptimizedNetworkImpl</a>(<a class="code" href="namespacestd.xhtml">std</a>::move(graph), modelOptions)) {}</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> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a437cc59f5247f213adf34e84696f60da">IOptimizedNetwork::~IOptimizedNetwork</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span> </div><div class="line"><a name="l00532"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_optimized_network.xhtml#a58ee539cf95c1e99fe4f54ef6e8bbd05"> 532</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="l00533"></a><span class="lineno"> 533</span> {</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  <span class="keyword">delete</span> network;</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span> }</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span> </div><div class="line"><a name="l00537"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_optimized_network.xhtml#aff3fde909d22ed157046682e70129259"> 537</a></span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#aff3fde909d22ed157046682e70129259">IOptimizedNetwork::PrintGraph</a>()</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span> {</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a374d52340ec8dc02a819acc20fb5aa92">pOptimizedNetworkImpl</a>->PrintGraph();</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span> }</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span> </div><div class="line"><a name="l00542"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_optimized_network.xhtml#a26794f014974a6f963a8925de07bffeb"> 542</a></span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a26794f014974a6f963a8925de07bffeb">IOptimizedNetwork::SerializeToDot</a>(std::ostream& stream)<span class="keyword"> const</span></div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span> <span class="keyword"></span>{</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a374d52340ec8dc02a819acc20fb5aa92">pOptimizedNetworkImpl</a>->SerializeToDot(stream);</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span> }</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span> </div><div class="line"><a name="l00547"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_optimized_network.xhtml#ab986223ec7e4f04929cb47c74a27aa93"> 547</a></span> <a class="code" href="classarmnn_1_1profiling_1_1_profiling_guid.xhtml">profiling::ProfilingGuid</a> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#ab986223ec7e4f04929cb47c74a27aa93">IOptimizedNetwork::GetGuid</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span> <span class="keyword"></span>{</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a374d52340ec8dc02a819acc20fb5aa92">pOptimizedNetworkImpl</a>->GetGuid();</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span> }</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span> </div><div class="line"><a name="l00552"></a><span class="lineno"><a class="line" href="classarmnn_1_1_optimized_network_impl.xhtml#aff3fde909d22ed157046682e70129259"> 552</a></span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml#aff3fde909d22ed157046682e70129259">OptimizedNetworkImpl::PrintGraph</a>()</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span> {</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  m_Graph->Print();</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">Status::Success</a>;</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span> }</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span> </div><div class="line"><a name="l00558"></a><span class="lineno"><a class="line" href="classarmnn_1_1_optimized_network_impl.xhtml#a26794f014974a6f963a8925de07bffeb"> 558</a></span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml#a26794f014974a6f963a8925de07bffeb">OptimizedNetworkImpl::SerializeToDot</a>(std::ostream& stream)<span class="keyword"> const</span></div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span> <span class="keyword"></span>{</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <span class="keywordflow">return</span> m_Graph->SerializeToDot(stream);</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span> }</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span> </div><div class="line"><a name="l00563"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994"> 563</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="l00564"></a><span class="lineno"> 564</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errorMessages)</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>  std::stringstream fullErrorMessage;</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  fullErrorMessage << <span class="stringliteral">"ERROR: "</span> << errorMessage;</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</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="l00569"></a><span class="lineno"> 569</span>  <span class="keywordflow">if</span> (errorMessages)</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  {</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  errorMessages.value().push_back(fullErrorMessage.str());</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  }</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span> }</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span> </div><div class="line"><a name="l00575"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a38e626422579decc13e3ee37da1a84c9"> 575</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="l00576"></a><span class="lineno"> 576</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> warningMessages)</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span> {</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  std::stringstream fullWarningMessage;</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  fullWarningMessage << <span class="stringliteral">"WARNING: "</span> << warningMessage;</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</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="l00581"></a><span class="lineno"> 581</span>  <span class="keywordflow">if</span> (warningMessages)</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  {</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  warningMessages.value().push_back(fullWarningMessage.str());</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> }</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span> </div><div class="line"><a name="l00587"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#ae50fff9aa2a1ce46392d8641c10aa3bc"> 587</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="l00588"></a><span class="lineno"> 588</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* layer,</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</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="l00590"></a><span class="lineno"> 590</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span> {</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  std::stringstream failureMsg;</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  failureMsg << <span class="stringliteral">"Layer of type "</span> << <a class="code" href="namespacearmnn.xhtml#addb6b14dd1b632263ffe77430259a7c4">GetLayerTypeAsCString</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>())</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</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="l00595"></a><span class="lineno"> 595</span>  <a class="code" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994">ReportError</a>(failureMsg.str(), errMessages);</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span> </div><div class="line"><a name="l00597"></a><span class="lineno"> 597</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="l00598"></a><span class="lineno"> 598</span>  <span class="keywordflow">return</span> res;</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span> }</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span> </div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span> </div><div class="line"><a name="l00602"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#af002111f64aee648e3258247075cae36"> 602</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="l00603"></a><span class="lineno"> 603</span> {</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  <span class="keywordtype">bool</span> noErrors = <span class="keyword">true</span>;</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</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="l00606"></a><span class="lineno"> 606</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="l00607"></a><span class="lineno"> 607</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="l00608"></a><span class="lineno"> 608</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="l00609"></a><span class="lineno"> 609</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="l00610"></a><span class="lineno"> 610</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="l00611"></a><span class="lineno"> 611</span>  noErrors = <span class="keyword">false</span>;</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  std::stringstream ss;</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  ss << <span class="stringliteral">"output "</span> << i << <span class="stringliteral">" of layer "</span> << <a class="code" href="namespacearmnn.xhtml#addb6b14dd1b632263ffe77430259a7c4">GetLayerTypeAsCString</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>())</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</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="l00615"></a><span class="lineno"> 615</span>  << <span class="stringliteral">" Quantized 8 bit but its scale parameter has not been set"</span>;</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <a class="code" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994">ReportError</a>(ss.str(), errMessages);</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  }</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  <span class="comment">// Softmax under QuantisedAsymm8 must always be scale (1.0f/256.0f) and offset 0</span></div><div class="line"><a name="l00619"></a><span class="lineno"> 619</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="l00620"></a><span class="lineno"> 620</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>() != 0) &&</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a31d953b9d49a6b4378f45097047976d0">armnn::LayerType::Softmax</a>)</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>  std::stringstream ss;</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  ss << <span class="stringliteral">"Quantization parameters for Softmax layer (Scale: "</span> <<</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</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="l00626"></a><span class="lineno"> 626</span>  <span class="stringliteral">") are incorrect and have been updated to Scale: 0.00390625 and Offset: 0"</span>;</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</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="l00628"></a><span class="lineno"> 628</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="l00629"></a><span class="lineno"> 629</span>  info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(0);</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(info);</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>  }</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  }</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  <span class="keywordflow">return</span> noErrors;</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> </div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span> <span class="keyword">template</span> <<span class="keyword">typename</span> LayerT></div><div class="line"><a name="l00638"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a33d586a0d9bbb1f12ac7a3ba8d03e21e"> 638</a></span> LayerT* <a class="code" href="namespacearmnn.xhtml#a33d586a0d9bbb1f12ac7a3ba8d03e21e">ConvertBf16ToFp32Weight</a>(<a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* l)</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span> {</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  LayerT* layer = PolymorphicDowncast<LayerT*>(l);</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  <span class="keywordflow">if</span> ((layer->GetType() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">LayerType::Convolution2d</a> || layer->GetType() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e">LayerType::FullyConnected</a>)</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  && layer->m_Weight)</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  {</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = layer->m_Weight->GetTensorInfo();</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span> </div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  <span class="keywordflow">if</span> (info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>)</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>  std::vector<float> newValues(info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</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>  <a class="code" href="classarmnn_utils_1_1_floating_point_converter.xhtml#af9e9df90cb6319b0406acf9a3bc27667">armnnUtils::FloatingPointConverter::ConvertBFloat16ToFloat32</a>(</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  layer->m_Weight->template GetTensor<armnn::BFloat16>(), info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(), newValues.data());</div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span> </div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> newInfo(info.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> newInput(newInfo, newValues);</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  layer->m_Weight.reset(<span class="keyword">new</span> <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">ScopedCpuTensorHandle</a>(newInput));</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  }</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  }</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span> }</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span> </div><div class="line"><a name="l00661"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a56f168327453ea4461cbc1c0ac7f15b6"> 661</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="l00662"></a><span class="lineno"> 662</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph,</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* layer,</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  <a class="code" href="classarmnn_1_1_backend_id.xhtml">BackendId</a> backend,</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataTypeIn,</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataTypeOut,</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  <span class="keyword">const</span> std::vector<BackendId>& availablePreferredBackends,</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  std::string& reasonIfUnsupported,</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</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="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> result;</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span> </div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  <span class="comment">// Helper lambda to compose meaningful error message before returning with error</span></div><div class="line"><a name="l00674"></a><span class="lineno"> 674</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="l00675"></a><span class="lineno"> 675</span>  {</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</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="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="comment">// need to set the compute device on the layer</span></div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  <span class="comment">// before we can check if it is supported</span></div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a3f6ad59212fa8a47c9265162fff8a274">SetBackendId</a>(backend);</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</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="l00683"></a><span class="lineno"> 683</span>  {</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</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="l00685"></a><span class="lineno"> 685</span>  {</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</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="l00687"></a><span class="lineno"> 687</span>  && layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">LayerType::ConvertFp32ToFp16</a></div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  && layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">LayerType::ConvertFp16ToFp32</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="comment">// Insert FP16 -> FP32 conversion layer before current layer</span></div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  std::vector<ConvertFp16ToFp32Layer*> convertFp16ToFp32Layers;</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <span class="keywordflow">if</span> (dataTypeIn == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>)</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  {</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  convertFp16ToFp32Layers =</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <a class="code" href="namespacearmnn.xhtml#ad31c56533e4f9f9f51719599fbfcf7bb">InsertConvertFp16ToFp32LayersBefore</a>(graph, *layer);</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  }</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="comment">// Insert FP32 -> FP16 conversion layer after current layer</span></div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  std::vector<ConvertFp32ToFp16Layer*> convertFp32ToFp16Layers;</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <span class="keywordflow">if</span> (dataTypeOut == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>)</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>  convertFp32ToFp16Layers =</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <a class="code" href="namespacearmnn.xhtml#abf625e50a5eaeafce5b39580dc95a9d3">InsertConvertFp32ToFp16LayersAfter</a>(graph, *layer);</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> </div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  <span class="comment">// Assign a supported backend to the newly introduced conversion layers</span></div><div class="line"><a name="l00707"></a><span class="lineno"> 707</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="l00708"></a><span class="lineno"> 708</span>  {</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  <span class="keywordtype">bool</span> supportedBackendFound = <span class="keyword">false</span>;</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  std::string reasonIfUnsupported;</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span> </div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <span class="comment">// Try preferred backend first</span></div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a3f6ad59212fa8a47c9265162fff8a274">SetBackendId</a>(preferredBackend);</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</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="l00715"></a><span class="lineno"> 715</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>(),</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  reasonIfUnsupported))</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  {</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  supportedBackendFound = <span class="keyword">true</span>;</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  }</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  <span class="keywordflow">else</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="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& backend : availablePreferredBackends)</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  {</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  <span class="comment">// Skip preferred backend (we already determined that it is not supported)</span></div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  <span class="keywordflow">if</span> (backend == preferredBackend)</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  {</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  }</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>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a3f6ad59212fa8a47c9265162fff8a274">SetBackendId</a>(backend);</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</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="l00732"></a><span class="lineno"> 732</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>(),</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  reasonIfUnsupported))</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>  supportedBackendFound = <span class="keyword">true</span>;</div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  }</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  }</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  }</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span> </div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  <span class="keywordflow">return</span> supportedBackendFound;</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">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="l00745"></a><span class="lineno"> 745</span>  {</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  <span class="keywordflow">if</span> (!AssignFirstSupportedBackend(convertLayer, backend))</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  {</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  <span class="keywordflow">return</span> ReturnError(convertLayer);</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  }</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  }</div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span> </div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <span class="keywordflow">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="l00753"></a><span class="lineno"> 753</span>  {</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  <span class="keywordflow">if</span> (!AssignFirstSupportedBackend(convertLayer, backend))</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="keywordflow">return</span> ReturnError(convertLayer);</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>  }</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span> </div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  }</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">else</span> <span class="keywordflow">if</span> (dataTypeIn == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a> || dataTypeOut == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</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">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="l00766"></a><span class="lineno"> 766</span>  && layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a6512859957de2cf2a5fe4dccb07bd9da">LayerType::ConvertFp32ToBf16</a></div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  && layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a2ba4c46787312a2467153f40c542851a">LayerType::ConvertBf16ToFp32</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>  <span class="comment">// Insert BF16 -> FP32 conversion layer before current layer</span></div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  std::vector<ConvertBf16ToFp32Layer*> convertBf16ToFp32Layers;</div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  <span class="keywordflow">if</span> (dataTypeIn == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>)</div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  {</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  convertBf16ToFp32Layers =</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  <a class="code" href="namespacearmnn.xhtml#adf69fa0e439ddb632462b42253d67b6a">InsertConvertBf16ToFp32LayersBefore</a>(graph, *layer);</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  <span class="keywordflow">if</span> (layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">LayerType::Convolution2d</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>  ConvertBf16ToFp32Weight<Convolution2dLayer>(layer);</div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  }</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e">LayerType::FullyConnected</a>)</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>  ConvertBf16ToFp32Weight<FullyConnectedLayer>(layer);</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>  }</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>  <span class="comment">// Insert FP32 -> BF16 conversion layer after current layer</span></div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  std::vector<ConvertFp32ToBf16Layer*> convertFp32ToBf16Layers;</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  <span class="keywordflow">if</span> (dataTypeOut == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>)</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  {</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  convertFp32ToBf16Layers =</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <a class="code" href="namespacearmnn.xhtml#a8ae358a041b4adc33577e8b4c07b8d23">InsertConvertFp32ToBf16LayersAfter</a>(graph, *layer);</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  }</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span> </div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  <span class="comment">// Assign a supported backend to the newly introduced conversion layers</span></div><div class="line"><a name="l00794"></a><span class="lineno"> 794</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="l00795"></a><span class="lineno"> 795</span>  {</div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  <span class="keywordtype">bool</span> supportedBackendFound = <span class="keyword">false</span>;</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  std::string reasonIfUnsupported;</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span> </div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  <span class="comment">// Try preferred backend first</span></div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a3f6ad59212fa8a47c9265162fff8a274">SetBackendId</a>(preferredBackend);</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</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="l00802"></a><span class="lineno"> 802</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>(),</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  reasonIfUnsupported))</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>  supportedBackendFound = <span class="keyword">true</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="keywordflow">else</span></div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  {</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& backend : availablePreferredBackends)</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  {</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  <span class="comment">// Skip preferred backend (we already determined that it is not supported)</span></div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  <span class="keywordflow">if</span> (backend == preferredBackend)</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  {</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  }</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span> </div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a3f6ad59212fa8a47c9265162fff8a274">SetBackendId</a>(backend);</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</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="l00819"></a><span class="lineno"> 819</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>(),</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  reasonIfUnsupported))</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>  supportedBackendFound = <span class="keyword">true</span>;</div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  }</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  }</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  }</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span> </div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  <span class="keywordflow">return</span> supportedBackendFound;</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  };</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>  <span class="keywordflow">for</span> (<a class="code" href="classarmnn_1_1_convert_bf16_to_fp32_layer.xhtml">ConvertBf16ToFp32Layer</a>* convertLayer : convertBf16ToFp32Layers)</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span>  {</div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span>  <span class="keywordflow">if</span> (!AssignFirstSupportedBackend(convertLayer, backend))</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="keywordflow">return</span> ReturnError(convertLayer);</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  }</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  }</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span> </div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  <span class="keywordflow">for</span> (<a class="code" href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">ConvertFp32ToBf16Layer</a>* convertLayer : convertFp32ToBf16Layers)</div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  {</div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  <span class="keywordflow">if</span> (!AssignFirstSupportedBackend(convertLayer, backend))</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  {</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  <span class="keywordflow">return</span> ReturnError(convertLayer);</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  }</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> </div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  <span class="keywordflow">return</span> result;</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>  }</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span> </div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  std::stringstream warningMsg;</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  warningMsg << <span class="stringliteral">"Layer of type "</span> << <a class="code" href="namespacearmnn.xhtml#addb6b14dd1b632263ffe77430259a7c4">GetLayerTypeAsCString</a>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>())</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</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="l00854"></a><span class="lineno"> 854</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="l00855"></a><span class="lineno"> 855</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="l00856"></a><span class="lineno"> 856</span>  << <span class="stringliteral">" (reason: "</span> << reasonIfUnsupported</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  << <span class="stringliteral">"), falling back to the next backend."</span>;</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  <a class="code" href="namespacearmnn.xhtml#a38e626422579decc13e3ee37da1a84c9">ReportWarning</a>(warningMsg.str(), errMessages);</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span> </div><div class="line"><a name="l00860"></a><span class="lineno"> 860</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="l00861"></a><span class="lineno"> 861</span>  }</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  {</div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  }</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> </div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span> </div><div class="line"><a name="l00869"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a224df72b3d7a3bba8609bc167286e3f7"> 869</a></span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> <a class="code" href="namespacearmnn.xhtml#a224df72b3d7a3bba8609bc167286e3f7">AssignBackends</a>(<a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml">OptimizedNetworkImpl</a>* optNetObjPtr,</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a>& backendSettings,</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a>& firstLayer,</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a>& lastLayer,</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span> {</div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> result;</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="comment">// Helper lambda to compose meaningful error message before returning with error</span></div><div class="line"><a name="l00878"></a><span class="lineno"> 878</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="l00879"></a><span class="lineno"> 879</span>  {</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</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="l00881"></a><span class="lineno"> 881</span>  };</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span> </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>  <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="l00885"></a><span class="lineno"> 885</span>  <span class="keywordflow">if</span> (availablePreferredBackends.empty())</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>  std::stringstream failureMsg;</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  failureMsg << <span class="stringliteral">"No preferred backends are available"</span>;</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  <a class="code" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994">ReportError</a>(failureMsg.str(), errMessages);</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span> </div><div class="line"><a name="l00891"></a><span class="lineno"> 891</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="l00892"></a><span class="lineno"> 892</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  }</div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span> </div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it = firstLayer; it != lastLayer; ++it)</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  {</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  <span class="keyword">auto</span> layer = *it;</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span> </div><div class="line"><a name="l00899"></a><span class="lineno"> 899</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="l00900"></a><span class="lineno"> 900</span>  layer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo().GetDataType();</div><div class="line"><a name="l00901"></a><span class="lineno"> 901</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="l00902"></a><span class="lineno"> 902</span>  layer->GetOutputSlot(0).GetTensorInfo().GetDataType();</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>  std::string reasonIfUnsupported;</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  <span class="keywordtype">bool</span> found = <span class="keyword">false</span>;</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn.xhtml#af002111f64aee648e3258247075cae36">CheckScaleSetOnQuantizedType</a>(layer, errMessages))</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">// don't bomb immediately, find all the quantized outputs</span></div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  <span class="comment">// which haven't had a scale set and report them all back.</span></div><div class="line"><a name="l00910"></a><span class="lineno"> 910</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="l00911"></a><span class="lineno"> 911</span>  }</div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span> </div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  <span class="comment">// First try assign layer to hint backend</span></div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  <span class="keywordflow">if</span> (layer->GetBackendHint().has_value() &&</div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#aa5df3120ee0fbb3321df3133ec9e83ae">IsBackendSupported</a>(layer->GetBackendHint().value()) &&</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  <a class="code" href="namespacearmnn.xhtml#a56f168327453ea4461cbc1c0ac7f15b6">AttemptBackendAssignment</a>(backendSettings,</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  optNetObjPtr-><a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml#a49800ad35ea869aa5569519760d3b339">GetGraph</a>(),</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  layer,</div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  layer->GetBackendHint().value(),</div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  dataTypeIn,</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  dataTypeOut,</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  availablePreferredBackends,</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  reasonIfUnsupported,</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  errMessages).IsOk())</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  {</div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  found = <span class="keyword">true</span>;</div><div class="line"><a name="l00927"></a><span class="lineno"> 927</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="l00928"></a><span class="lineno"> 928</span>  }</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  {</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  <span class="comment">// Try assign layer to prefered list of backends</span></div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  <span class="keywordflow">for</span> (<span class="keyword">const</span> <span class="keyword">auto</span>& backend : availablePreferredBackends)</div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  {</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  <span class="keywordflow">if</span> (layer->GetBackendHint().has_value() &&</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  layer->GetBackendHint().value() == backend)</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="keywordflow">continue</span>; <span class="comment">//Don't re-test the backend hint</span></div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  }</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span> </div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <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="l00941"></a><span class="lineno"> 941</span>  optNetObjPtr-><a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml#a49800ad35ea869aa5569519760d3b339">GetGraph</a>(),</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  layer,</div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  backend,</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  dataTypeIn,</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  dataTypeOut,</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  availablePreferredBackends,</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  reasonIfUnsupported,</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  errMessages);</div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span> </div><div class="line"><a name="l00950"></a><span class="lineno"> 950</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="l00951"></a><span class="lineno"> 951</span>  {</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  found = <span class="keyword">true</span>;</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#aa09ac75b83067c5ed455f2bb35c7c98d">m_SelectedBackends</a>.insert(backend);</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  }</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</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="l00957"></a><span class="lineno"> 957</span>  {</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  <span class="keywordflow">return</span> res; <span class="comment">// Cannot continue.</span></div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  <span class="comment">// Note: we don't need to log the error as it would already</span></div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  <span class="comment">// be logged in AttemptBackendAssignment().</span></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="keywordflow">else</span></div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span>  {</div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(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="l00965"></a><span class="lineno"> 965</span>  }</div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  }</div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  }</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">// If the layer is unsupported by any devices, log and return a null network.</span></div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  <span class="keywordflow">if</span> (!found)</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  {</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</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="l00973"></a><span class="lineno"> 973</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="l00974"></a><span class="lineno"> 974</span>  <span class="comment">// available as accelerated operations, or are only available under certain</span></div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  <span class="comment">// conditions, currently they comprise MemCopy, Constant, Permute)</span></div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a> layerType = layer->GetType();</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</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="l00978"></a><span class="lineno"> 978</span>  layerType == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</a> ||</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  layerType == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnn::LayerType::Permute</a>))</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  {</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</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="l00982"></a><span class="lineno"> 982</span>  layer->SetBackendId(cpuBackendId);</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  backendSettings.<a class="code" href="structarmnn_1_1_backend_settings.xhtml#aa09ac75b83067c5ed455f2bb35c7c98d">m_SelectedBackends</a>.insert(cpuBackendId);</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  }</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  <span class="keywordflow">else</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="keywordflow">return</span> ReturnError(layer);</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  }</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  }</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  }</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span> </div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span> }</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span> </div><div class="line"><a name="l00995"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a48e4d70ae8893f6f1a8ebfced5b03a07"> 995</a></span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> <a class="code" href="namespacearmnn.xhtml#a224df72b3d7a3bba8609bc167286e3f7">AssignBackends</a>(<a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml">OptimizedNetworkImpl</a>* optNetObjPtr,</div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a>& backendSettings,</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  <a class="code" href="classarmnn_1_1_subgraph_view.xhtml">SubgraphView</a>& subgraph,</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span> {</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  <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="l01001"></a><span class="lineno"> 1001</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="l01002"></a><span class="lineno"> 1002</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a224df72b3d7a3bba8609bc167286e3f7">AssignBackends</a>(optNetObjPtr,</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>  backendSettings,</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>  firstLayer,</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  lastLayer,</div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>  errMessages);</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> </div><div class="line"><a name="l01009"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a1ec6b4c20ed294a96cf94c33c24caaf5"> 1009</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="l01010"></a><span class="lineno"> 1010</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a>& backendSettings)</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="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a> backends;</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</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="l01014"></a><span class="lineno"> 1014</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="l01015"></a><span class="lineno"> 1015</span>  {</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  <span class="keyword">auto</span> backendFactory = backendRegistry.GetFactory(selectedBackend);</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  <span class="keyword">auto</span> backendObjPtr = backendFactory();</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(backendObjPtr);</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>  backendObjPtr->RegisterTensorHandleFactories(handleFactoryRegistry);</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>  backends[backendObjPtr->GetId()] = std::move(backendObjPtr);</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"> 1025</span>  <span class="keywordflow">return</span> backends;</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span> }</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span> </div><div class="line"><a name="l01028"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a9f31d956861d8277fa5f8fb877dbbb6c"> 1028</a></span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> <a class="code" href="namespacearmnn.xhtml#a9f31d956861d8277fa5f8fb877dbbb6c">ApplyBackendOptimizations</a>(<a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml">OptimizedNetworkImpl</a>* optNetObjPtr,</div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a>& backendSettings,</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>  <a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a>& backends,</div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#a5b6893cda5b69359a4244c06054da18f">ModelOptions</a>& modelOptions,</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</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>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(optNetObjPtr);</div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span> </div><div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> result;</div><div class="line"><a name="l01037"></a><span class="lineno"> 1037</span> </div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  <span class="comment">// Get the optimized graph</span></div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& optGraph = optNetObjPtr-><a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml#a49800ad35ea869aa5569519760d3b339">GetGraph</a>();</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span> </div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>  <span class="comment">// Run backend specific optimizations</span></div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</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="l01043"></a><span class="lineno"> 1043</span>  {</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>  <span class="keyword">auto</span> backendObjPtr = backends.find(selectedBackend)->second.get();</div><div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(backendObjPtr);</div><div class="line"><a name="l01046"></a><span class="lineno"> 1046</span> </div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  <span class="comment">// Select sub-graphs based on backend</span></div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  <a class="code" href="classarmnn_1_1_subgraph_view_selector.xhtml#aaf71a63dbbc776f8961b0f4fdb9da021">SubgraphViewSelector::Subgraphs</a> subgraphs =</div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  <a class="code" href="classarmnn_1_1_subgraph_view_selector.xhtml#a3730b0a6006f0d87f894a44e01869d90">SubgraphViewSelector::SelectSubgraphs</a>(optGraph,</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>  <span class="comment">// Select layers assigned to the requested backend</span></div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</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="l01052"></a><span class="lineno"> 1052</span>  {</div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  <span class="keywordflow">return</span> layer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a> &&</div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>  layer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() != <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a> &&</div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>  layer.<a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() == backendObjPtr->GetId();</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>  <span class="keywordflow">if</span> (subgraphs.empty())</div><div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>  {</div><div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  <span class="comment">// No sub-graphs found, try with next selected backend</span></div><div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  }</div><div class="line"><a name="l01062"></a><span class="lineno"> 1062</span> </div><div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>  <span class="comment">// Try to optimize each sub-graph</span></div><div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& subgraph : subgraphs)</div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  {</div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>  <span class="comment">// Try to optimize the current sub-graph</span></div><div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>  <a class="code" href="classarmnn_1_1_optimization_views.xhtml">OptimizationViews</a> optimizationViews = backendObjPtr->OptimizeSubgraphView(*subgraph, modelOptions);</div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(optimizationViews.<a class="code" href="classarmnn_1_1_optimization_views.xhtml#a58dc3ea86870112f745b2a1f7dca55e9">Validate</a>(*subgraph));</div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</span> </div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>  <span class="comment">// Optimization attempted, check the resulting optimized sub-graph</span></div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</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="l01072"></a><span class="lineno"> 1072</span>  {</div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</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="l01074"></a><span class="lineno"> 1074</span>  <a class="code" href="classarmnn_1_1_subgraph_view.xhtml">SubgraphView</a>& replacementSubgraph = substitution.m_ReplacementSubgraph;</div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>  <a class="code" href="classarmnn_1_1_subgraph_view.xhtml">SubgraphView</a>& substitutableSubgraph = substitution.m_SubstitutableSubgraph;</div><div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>  optGraph.<a class="code" href="classarmnn_1_1_graph.xhtml#aafbd4b469e47160017f409df8d077184">SubstituteSubgraph</a>(substitutableSubgraph, replacementSubgraph);</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="comment">// Assign the current backend to the optimized sub-graph</span></div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</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="l01080"></a><span class="lineno"> 1080</span>  {</div><div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(l);</div><div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>  l->SetBackendId(selectedBackend);</div><div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>  });</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"> 1086</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="l01087"></a><span class="lineno"> 1087</span>  {</div><div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>  std::stringstream warningMsg;</div><div class="line"><a name="l01089"></a><span class="lineno"> 1089</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="l01090"></a><span class="lineno"> 1090</span>  <a class="code" href="namespacearmnn.xhtml#a38e626422579decc13e3ee37da1a84c9">ReportWarning</a>(warningMsg.str(), errMessages);</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span> </div><div class="line"><a name="l01092"></a><span class="lineno"> 1092</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="l01093"></a><span class="lineno"> 1093</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a> settingsCopy(backendSettings);</div><div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>  <span class="keywordflow">if</span> (!backendObjPtr->GetId().IsCpuRef())</div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  {</div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>  <span class="comment">// Add the current backend to the list of backends to ignore</span></div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>  settingsCopy.m_IgnoredBackends.insert(backendObjPtr->GetId());</div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  }</div><div class="line"><a name="l01099"></a><span class="lineno"> 1099</span> </div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  <span class="keywordtype">int</span> count=0;</div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</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="l01102"></a><span class="lineno"> 1102</span>  {</div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  <span class="comment">// An error occurred: the optimization was attempted but not performed, try different backends</span></div><div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>  std::stringstream subgraphMsg;</div><div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>  subgraphMsg << <span class="stringliteral">"Re-assigning backends to "</span> << failedSubgraph.GetLayers().size()</div><div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>  << <span class="stringliteral">" layers inside sub-graph "</span> << count++;</div><div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>  <a class="code" href="namespacearmnn.xhtml#a38e626422579decc13e3ee37da1a84c9">ReportWarning</a>(subgraphMsg.str(), errMessages);</div><div class="line"><a name="l01108"></a><span class="lineno"> 1108</span> </div><div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> reassignmentResult = <a class="code" href="namespacearmnn.xhtml#a224df72b3d7a3bba8609bc167286e3f7">AssignBackends</a>(optNetObjPtr,</div><div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>  settingsCopy,</div><div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  *subgraph,</div><div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  errMessages);</div><div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>  <span class="keywordflow">if</span> (reassignmentResult.m_Error)</div><div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  {</div><div class="line"><a name="l01115"></a><span class="lineno"> 1115</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="l01116"></a><span class="lineno"> 1116</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="l01117"></a><span class="lineno"> 1117</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>  }</div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>  }</div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  }</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>  }</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">return</span> result;</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"><a class="line" href="namespacearmnn.xhtml#a5ee4a1cca55f69b31e625c786655ed1a"> 1127</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="l01128"></a><span class="lineno"> 1128</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> dst,</div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry)</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> (src != dst)</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>  <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="l01134"></a><span class="lineno"> 1134</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="l01135"></a><span class="lineno"> 1135</span> </div><div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>  <span class="keywordflow">if</span> (srcFactory && dstFactory &&</div><div class="line"><a name="l01137"></a><span class="lineno"> 1137</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="l01138"></a><span class="lineno"> 1138</span>  {</div><div class="line"><a name="l01139"></a><span class="lineno"> 1139</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>  }</div><div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>  }</div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span> }</div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span> </div><div class="line"><a name="l01146"></a><span class="lineno"> 1146</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="l01147"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#accb1637c58e1523f740025e0d0e7c6dd"> 1147</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="l01148"></a><span class="lineno"> 1148</span>  <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>& slot,</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry)</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_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="l01152"></a><span class="lineno"> 1152</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>);</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>  <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="l01155"></a><span class="lineno"> 1155</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="l01156"></a><span class="lineno"> 1156</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="l01157"></a><span class="lineno"> 1157</span>  <span class="comment">// select a factory with maximum compatibility with the layers connected to the InputLayer.</span></div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span> </div><div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>  <span class="comment">// First ensure the from backends can support the TensorHandeAPI</span></div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</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="l01161"></a><span class="lineno"> 1161</span>  <span class="keywordflow">if</span> (frmBackend == backends.end() ||</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>  !frmBackend->second->SupportsTensorAllocatorAPI())</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>  <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="l01165"></a><span class="lineno"> 1165</span>  }</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span> </div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</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="l01168"></a><span class="lineno"> 1168</span>  <span class="comment">// fewest copies.</span></div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>  std::map<ITensorHandleFactory::FactoryId, int> factoryScores;</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>  <span class="keywordtype">int</span> topScore = 0;</div><div class="line"><a name="l01171"></a><span class="lineno"> 1171</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="l01172"></a><span class="lineno"> 1172</span> </div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</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="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> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& connectedLayer = connection->GetOwningLayer();</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>  <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="l01178"></a><span class="lineno"> 1178</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(toBackend != backends.end(), <span class="stringliteral">"Backend id not found for the connected layer"</span>);</div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span> </div><div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  <span class="keywordflow">if</span> (!toBackend->second.get()->SupportsTensorAllocatorAPI())</div><div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>  {</div><div class="line"><a name="l01182"></a><span class="lineno"> 1182</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="l01183"></a><span class="lineno"> 1183</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>  }</div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span> </div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  <span class="keyword">auto</span> dstPrefs = toBackend->second.get()->GetHandleFactoryPreferences();</div><div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& dst : dstPrefs)</div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>  {</div><div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>  <span class="comment">// Input layers use the mem copy workload or import, so the selected factory must</span></div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>  <span class="comment">// support either the map/unmap API or Import API</span></div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</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="l01192"></a><span class="lineno"> 1192</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="l01193"></a><span class="lineno"> 1193</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="l01194"></a><span class="lineno"> 1194</span>  {</div><div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>  <span class="comment">// The current tensor handle factory does not support the map/unmap or import</span></div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>  <span class="comment">// strategy, move to the next one</span></div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  <span class="keywordflow">continue</span>;</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> </div><div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>  <span class="keyword">auto</span> it = factoryScores.find(dst);</div><div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>  <span class="keywordflow">if</span> (it == factoryScores.end())</div><div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>  {</div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>  <span class="comment">// Add new score to the table</span></div><div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  factoryScores[dst] = 0;</div><div class="line"><a name="l01205"></a><span class="lineno"> 1205</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="l01206"></a><span class="lineno"> 1206</span>  {</div><div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  topChoice = dst;</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>  }</div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>  }</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>  {</div><div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>  <span class="comment">// Increase the score</span></div><div class="line"><a name="l01213"></a><span class="lineno"> 1213</span>  factoryScores[dst]++;</div><div class="line"><a name="l01214"></a><span class="lineno"> 1214</span> </div><div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>  <span class="comment">// Track the best option</span></div><div class="line"><a name="l01216"></a><span class="lineno"> 1216</span>  <span class="keywordflow">if</span> (factoryScores[dst] > topScore)</div><div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>  {</div><div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>  topScore = factoryScores[dst];</div><div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>  topChoice = dst;</div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  }</div><div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>  }</div><div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  }</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> </div><div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>  <span class="keywordflow">return</span> topChoice;</div><div class="line"><a name="l01226"></a><span class="lineno"> 1226</span> }</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="comment">// Find the handle factory for the output layer which results in fewest required copies.</span></div><div class="line"><a name="l01229"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#ab46c7f5f4736d550ab0e5e05a0fff4a9"> 1229</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="l01230"></a><span class="lineno"> 1230</span>  <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>& slot,</div><div class="line"><a name="l01231"></a><span class="lineno"> 1231</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry)</div><div class="line"><a name="l01232"></a><span class="lineno"> 1232</span> {</div><div class="line"><a name="l01233"></a><span class="lineno"> 1233</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(backends, slot, registry);</div><div class="line"><a name="l01234"></a><span class="lineno"> 1234</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="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"> 1237</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="l01238"></a><span class="lineno"> 1238</span> <span class="comment">// when considering all connections.</span></div><div class="line"><a name="l01239"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a8d9f52bbb69750456acca06988beabda"> 1239</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="l01240"></a><span class="lineno"> 1240</span>  <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>& outputSlot,</div><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry)</div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span> {</div><div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>  <span class="comment">// First ensure the from backends can support the TensorHandeAPI</span></div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</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="l01245"></a><span class="lineno"> 1245</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="l01246"></a><span class="lineno"> 1246</span>  <span class="keywordflow">if</span> (frmBackend == backends.end() ||</div><div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>  !frmBackend->second->SupportsTensorAllocatorAPI())</div><div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>  {</div><div class="line"><a name="l01249"></a><span class="lineno"> 1249</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="l01250"></a><span class="lineno"> 1250</span>  }</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="comment">// Connections to Output Layers requires support for map/unmap on the TensorHandle.</span></div><div class="line"><a name="l01253"></a><span class="lineno"> 1253</span>  <span class="keywordtype">bool</span> requiresMapUnmap = <span class="keyword">false</span>;</div><div class="line"><a name="l01254"></a><span class="lineno"> 1254</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="l01255"></a><span class="lineno"> 1255</span>  {</div><div class="line"><a name="l01256"></a><span class="lineno"> 1256</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="l01257"></a><span class="lineno"> 1257</span>  <span class="keywordflow">if</span> (connectedLayer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</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>  requiresMapUnmap = <span class="keyword">true</span>;</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"> 1262</span> </div><div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>  <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml">IBackendInternal</a>* srcBackend = frmBackend->second.get();</div><div class="line"><a name="l01264"></a><span class="lineno"> 1264</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="l01265"></a><span class="lineno"> 1265</span> </div><div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>  <span class="comment">// Initialize the scores</span></div><div class="line"><a name="l01267"></a><span class="lineno"> 1267</span>  std::map<ITensorHandleFactory::FactoryId, int> factoryScores;</div><div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& pref : srcPrefs)</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">if</span> (requiresMapUnmap) <span class="comment">// Only consider factories that support map/unmap if required</span></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>  <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="l01273"></a><span class="lineno"> 1273</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="l01274"></a><span class="lineno"> 1274</span>  {</div><div class="line"><a name="l01275"></a><span class="lineno"> 1275</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="l01276"></a><span class="lineno"> 1276</span>  <span class="keywordflow">continue</span>;</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"> 1279</span> </div><div class="line"><a name="l01280"></a><span class="lineno"> 1280</span>  <span class="keyword">auto</span> it = factoryScores.find(pref);</div><div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>  <span class="keywordflow">if</span> (it == factoryScores.end())</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>  <span class="comment">// Add new score to the table</span></div><div class="line"><a name="l01284"></a><span class="lineno"> 1284</span>  factoryScores[pref] = 0;</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>  }</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>  <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="l01289"></a><span class="lineno"> 1289</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="l01290"></a><span class="lineno"> 1290</span>  {</div><div class="line"><a name="l01291"></a><span class="lineno"> 1291</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="l01292"></a><span class="lineno"> 1292</span> </div><div class="line"><a name="l01293"></a><span class="lineno"> 1293</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="l01294"></a><span class="lineno"> 1294</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(toBackend != backends.end(), <span class="stringliteral">"Backend id not found for the connected layer"</span>);</div><div class="line"><a name="l01295"></a><span class="lineno"> 1295</span> </div><div class="line"><a name="l01296"></a><span class="lineno"> 1296</span>  <span class="keyword">auto</span> dstPrefs = toBackend->second.get()->GetHandleFactoryPreferences();</div><div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& src : srcPrefs)</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>  <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="l01300"></a><span class="lineno"> 1300</span>  {</div><div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l01302"></a><span class="lineno"> 1302</span>  }</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>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& dst : dstPrefs)</div><div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>  {</div><div class="line"><a name="l01306"></a><span class="lineno"> 1306</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#a5ee4a1cca55f69b31e625c786655ed1a">RequiresCopy</a>(src, dst, registry))</div><div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>  {</div><div class="line"><a name="l01308"></a><span class="lineno"> 1308</span>  <span class="comment">// Copy avoided, increase the score</span></div><div class="line"><a name="l01309"></a><span class="lineno"> 1309</span>  factoryScores[src]++;</div><div class="line"><a name="l01310"></a><span class="lineno"> 1310</span>  <span class="keywordflow">break</span>;</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>  }</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"> 1315</span> </div><div class="line"><a name="l01316"></a><span class="lineno"> 1316</span>  <span class="comment">// Find the lowest score</span></div><div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>  <span class="keywordtype">int</span> minScore = std::numeric_limits<int>::max();</div><div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : factoryScores)</div><div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>  {</div><div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>  minScore = std::min(minScore, it.second);</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> </div><div class="line"><a name="l01323"></a><span class="lineno"> 1323</span>  <span class="comment">// Collect factories matching the best(lowest) score</span></div><div class="line"><a name="l01324"></a><span class="lineno"> 1324</span>  std::vector<ITensorHandleFactory::FactoryId> optimalFactories;</div><div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> it : factoryScores)</div><div class="line"><a name="l01326"></a><span class="lineno"> 1326</span>  {</div><div class="line"><a name="l01327"></a><span class="lineno"> 1327</span>  <span class="keywordflow">if</span> (it.second == minScore)</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>  optimalFactories.push_back(it.first);</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"> 1332</span> </div><div class="line"><a name="l01333"></a><span class="lineno"> 1333</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="l01334"></a><span class="lineno"> 1334</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& srcPref : srcPrefs)</div><div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>  {</div><div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& comp : optimalFactories)</div><div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>  {</div><div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>  <span class="keywordflow">if</span> (comp == srcPref)</div><div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>  {</div><div class="line"><a name="l01340"></a><span class="lineno"> 1340</span>  <span class="keywordflow">return</span> comp;</div><div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>  }</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"> 1344</span> </div><div class="line"><a name="l01345"></a><span class="lineno"> 1345</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="l01346"></a><span class="lineno"> 1346</span> }</div><div class="line"><a name="l01347"></a><span class="lineno"> 1347</span> </div><div class="line"><a name="l01348"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a738d3243c1dc564304d78908c6112e4f"> 1348</a></span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016">EdgeStrategy</a> <a class="code" href="namespacearmnn.xhtml#a738d3243c1dc564304d78908c6112e4f">CalculateEdgeStrategy</a>(<a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a>& backends,</div><div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>  <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a32f4aa6a7089d877af08928139c2c277">ITensorHandleFactory::FactoryId</a> srcFactoryId,</div><div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& layer,</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& connectedLayer,</div><div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry,</div><div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>  <span class="keywordtype">bool</span> importEnabled)</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>  <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="l01356"></a><span class="lineno"> 1356</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(toBackend != backends.end(), <span class="stringliteral">"Backend id not found for the connected layer"</span>);</div><div class="line"><a name="l01357"></a><span class="lineno"> 1357</span> </div><div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>  <span class="keyword">auto</span> dstPrefs = toBackend->second.get()->GetHandleFactoryPreferences();</div><div class="line"><a name="l01359"></a><span class="lineno"> 1359</span> </div><div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>  <span class="comment">// Legacy API check for backward compatibility</span></div><div class="line"><a name="l01361"></a><span class="lineno"> 1361</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="l01362"></a><span class="lineno"> 1362</span>  {</div><div class="line"><a name="l01363"></a><span class="lineno"> 1363</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="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> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016ac366da48cc11956ae377a77751936852">EdgeStrategy::CopyToTarget</a>;</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>  <span class="keywordflow">else</span></div><div class="line"><a name="l01368"></a><span class="lineno"> 1368</span>  {</div><div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016a78d1be0baa31e083ae8da99aaedaf650">EdgeStrategy::DirectCompatibility</a>;</div><div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>  }</div><div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>  }</div><div class="line"><a name="l01372"></a><span class="lineno"> 1372</span> </div><div class="line"><a name="l01373"></a><span class="lineno"> 1373</span>  <span class="comment">// TensorHandleFactory API present, so perform more sophisticated strategies.</span></div><div class="line"><a name="l01374"></a><span class="lineno"> 1374</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="l01375"></a><span class="lineno"> 1375</span>  <span class="keywordflow">if</span> (connectedLayer.<a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>)</div><div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>  {</div><div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016a78d1be0baa31e083ae8da99aaedaf650">EdgeStrategy::DirectCompatibility</a>;</div><div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>  }</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="comment">// Search for direct match in prefs</span></div><div class="line"><a name="l01381"></a><span class="lineno"> 1381</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& pref : dstPrefs)</div><div class="line"><a name="l01382"></a><span class="lineno"> 1382</span>  {</div><div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>  <span class="keywordflow">if</span> (pref == srcFactoryId)</div><div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>  {</div><div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016a78d1be0baa31e083ae8da99aaedaf650">EdgeStrategy::DirectCompatibility</a>;</div><div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>  }</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"> 1389</span>  <span class="comment">// Search for export/import options</span></div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</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="l01391"></a><span class="lineno"> 1391</span>  <span class="keywordflow">if</span> (srcFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a9892b82652ffac03f1e4e7ad93906078">GetExportFlags</a>() != 0 && importEnabled)</div><div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>  {</div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& pref : dstPrefs)</div><div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>  {</div><div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>  <a class="code" href="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="l01396"></a><span class="lineno"> 1396</span> </div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>  <span class="comment">// Handles cases when a destPref is not listed in TensorHandleFactoryRegistry</span></div><div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>  <span class="keywordflow">if</span> (!dstFactory) {</div><div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>  }</div><div class="line"><a name="l01401"></a><span class="lineno"> 1401</span> </div><div class="line"><a name="l01402"></a><span class="lineno"> 1402</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="l01403"></a><span class="lineno"> 1403</span>  {</div><div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>  <span class="keyword">auto</span> srcCapability = srcFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a73fbbe9df988c8cabddea04a8dcb9323">GetCapabilities</a>(&layer, &layer, <a class="code" href="namespacearmnn.xhtml#a10c50bc964cc8cc559eebcd7df5a8af3aa47abd1077ef632a38ada05b6edbf389">CapabilityClass::PaddingRequired</a>);</div><div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>  <span class="keyword">auto</span> dstCapability = dstFactory-><a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a73fbbe9df988c8cabddea04a8dcb9323">GetCapabilities</a>(&connectedLayer,</div><div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>  &connectedLayer,</div><div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>  <a class="code" href="namespacearmnn.xhtml#a10c50bc964cc8cc559eebcd7df5a8af3aa47abd1077ef632a38ada05b6edbf389">CapabilityClass::PaddingRequired</a>);</div><div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>  <span class="comment">// Do not require memory copy if the source and destination do not require padding.</span></div><div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>  <span class="keywordflow">if</span> (srcCapability.empty() && dstCapability.empty())</div><div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>  {</div><div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016a46e8b7bfd6fd3c0cb34a100478a39189">EdgeStrategy::ExportToTarget</a>;</div><div class="line"><a name="l01412"></a><span class="lineno"> 1412</span>  }</div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>  }</div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>  }</div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>  }</div><div class="line"><a name="l01416"></a><span class="lineno"> 1416</span> </div><div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>  <span class="comment">// Search for copy options via map/unmap</span></div><div class="line"><a name="l01418"></a><span class="lineno"> 1418</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="l01419"></a><span class="lineno"> 1419</span>  {</div><div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& pref : dstPrefs)</div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>  {</div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</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="l01423"></a><span class="lineno"> 1423</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="l01424"></a><span class="lineno"> 1424</span>  {</div><div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016ac366da48cc11956ae377a77751936852">EdgeStrategy::CopyToTarget</a>;</div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>  }</div><div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>  }</div><div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>  }</div><div class="line"><a name="l01429"></a><span class="lineno"> 1429</span> </div><div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">EdgeStrategy::Undefined</a>;</div><div class="line"><a name="l01431"></a><span class="lineno"> 1431</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="comment">// Select the TensorHandleFactories and the corresponding memory strategy</span></div><div class="line"><a name="l01434"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a86541d11fcad5246a78cbc21d637a504"> 1434</a></span> <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> <a class="code" href="namespacearmnn.xhtml#a86541d11fcad5246a78cbc21d637a504">SelectTensorHandleStrategy</a>(<a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& optGraph,</div><div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>  <a class="code" href="namespacearmnn.xhtml#a9173495a61a0092b5f38b855f02c3585">BackendsMap</a>& backends,</div><div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a>& registry,</div><div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>  <span class="keywordtype">bool</span> importEnabled,</div><div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> errMessages)</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>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> result;</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>  optGraph.<a class="code" href="classarmnn_1_1_graph.xhtml#ad6521013ad981519904822f2ada2c4ec">ForEachLayer</a>([&backends, &registry, &result, &errMessages, importEnabled](<a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* layer)</div><div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>  {</div><div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(layer);</div><div class="line"><a name="l01445"></a><span class="lineno"> 1445</span> </div><div class="line"><a name="l01446"></a><span class="lineno"> 1446</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="l01447"></a><span class="lineno"> 1447</span>  <span class="comment">// assignment if this check fails</span></div><div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(backends.find(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>()) != backends.end());</div><div class="line"><a name="l01449"></a><span class="lineno"> 1449</span> </div><div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>  <span class="comment">// Check each output separately</span></div><div class="line"><a name="l01451"></a><span class="lineno"> 1451</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="l01452"></a><span class="lineno"> 1452</span>  {</div><div class="line"><a name="l01453"></a><span class="lineno"> 1453</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="l01454"></a><span class="lineno"> 1454</span> </div><div class="line"><a name="l01455"></a><span class="lineno"> 1455</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="l01456"></a><span class="lineno"> 1456</span> </div><div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>  <span class="comment">// Calculate the factory to use which results in the fewest copies being made.</span></div><div class="line"><a name="l01458"></a><span class="lineno"> 1458</span>  <span class="keywordflow">switch</span>(layer-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>())</div><div class="line"><a name="l01459"></a><span class="lineno"> 1459</span>  {</div><div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>:</div><div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>  slotOption = <a class="code" href="namespacearmnn.xhtml#accb1637c58e1523f740025e0d0e7c6dd">CalculateSlotOptionForInput</a>(backends, outputSlot, registry);</div><div class="line"><a name="l01462"></a><span class="lineno"> 1462</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>:</div><div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>  slotOption = <a class="code" href="namespacearmnn.xhtml#ab46c7f5f4736d550ab0e5e05a0fff4a9">CalculateSlotOptionForOutput</a>(backends, outputSlot, registry);</div><div class="line"><a name="l01465"></a><span class="lineno"> 1465</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>  slotOption = <a class="code" href="namespacearmnn.xhtml#a8d9f52bbb69750456acca06988beabda">CalculateSlotOption</a>(backends, outputSlot, registry);</div><div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>  <span class="keywordflow">break</span>;</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>  outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#af29f6883785691ef946d0c32b6d2f338">SetTensorHandleFactory</a>(slotOption);</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">// Now determine the "best" edge strategy for each connection given the slotOption.</span></div><div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> connectionIdx = 0;</div><div class="line"><a name="l01474"></a><span class="lineno"> 1474</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="l01475"></a><span class="lineno"> 1475</span>  {</div><div class="line"><a name="l01476"></a><span class="lineno"> 1476</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="l01477"></a><span class="lineno"> 1477</span> </div><div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>  <a class="code" href="namespacearmnn.xhtml#aff209afc1dc598da399e3e78617ce016">EdgeStrategy</a> strategy = <a class="code" href="namespacearmnn.xhtml#a738d3243c1dc564304d78908c6112e4f">CalculateEdgeStrategy</a>(backends, slotOption, *layer, connectedLayer,</div><div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>  registry, importEnabled);</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">if</span> (strategy == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">EdgeStrategy::Undefined</a>)</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>  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="l01484"></a><span class="lineno"> 1484</span>  <span class="keywordflow">if</span> (errMessages)</div><div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>  {</div><div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>  errMessages.value().emplace_back(<span class="stringliteral">"Could not find valid strategy required for compatibility"</span></div><div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>  <span class="stringliteral">" between backends."</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="keywordflow">return</span>;</div><div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>  }</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>  outputSlot.<a class="code" href="classarmnn_1_1_output_slot.xhtml#a3f80ddd1f76ed4ad599e0d1a00659ee5">SetEdgeStrategy</a>(connectionIdx, strategy);</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>  connectionIdx++;</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>  }</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> </div><div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>  <span class="keywordflow">return</span> result;</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"><a class="line" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685"> 1502</a></span> <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a22df7404d1196068ad18d0286f9b9425">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="l01503"></a><span class="lineno"> 1503</span>  <span class="keyword">const</span> std::vector<BackendId>& backendPreferences,</div><div class="line"><a name="l01504"></a><span class="lineno"> 1504</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="l01505"></a><span class="lineno"> 1505</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a>& options,</div><div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional</a><std::vector<std::string>&> messages)</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">if</span> (backendPreferences.empty())</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">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Invoked Optimize with no backends specified"</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> </div><div class="line"><a name="l01513"></a><span class="lineno"> 1513</span>  <span class="keywordflow">if</span> (options.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a6e1a42622ca43dafc7ba8e684c016eb4">m_ReduceFp32ToFp16</a> && options.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a11f463726addcc1d2845266997d79e9c">m_ReduceFp32ToBf16</a>)</div><div class="line"><a name="l01514"></a><span class="lineno"> 1514</span>  {</div><div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"BFloat16 and Float16 optimization cannot be enabled at the same time."</span>);</div><div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>  }</div><div class="line"><a name="l01517"></a><span class="lineno"> 1517</span> </div><div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>  std::unique_ptr<Graph> graph = std::make_unique<Graph>(inNetwork.<a class="code" href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">pNetworkImpl</a>->GetGraph());</div><div class="line"><a name="l01519"></a><span class="lineno"> 1519</span> </div><div class="line"><a name="l01520"></a><span class="lineno"> 1520</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_i_optimized_network.xhtml#af730a6ec3deb072dc2687089f3f77f9e">IOptimizedNetwork</a>(std::move(graph), options.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a71194277c60153a5f86539f5d39f01db">m_ModelOptions</a>),</div><div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>  &<a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a58ee539cf95c1e99fe4f54ef6e8bbd05">IOptimizedNetwork::Destroy</a>);</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>  <a class="code" href="classarmnn_1_1_i_optimized_network.xhtml">IOptimizedNetwork</a>* optNetObjPtr = optNet.get();</div><div class="line"><a name="l01524"></a><span class="lineno"> 1524</span> </div><div class="line"><a name="l01525"></a><span class="lineno"> 1525</span>  <span class="comment">// Get the optimized graph</span></div><div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& optGraph = optNetObjPtr-><a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a374d52340ec8dc02a819acc20fb5aa92">pOptimizedNetworkImpl</a>->GetGraph();</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>  <span class="comment">// Perform AddBroadcastReshapeLayer optimisation</span></div><div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>  <span class="keyword">using namespace </span>optimizations;</div><div class="line"><a name="l01530"></a><span class="lineno"> 1530</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#a4fc55afb4885278ad1510b2c4307af76">AddBroadcastReshapeLayer</a>()));</div><div class="line"><a name="l01531"></a><span class="lineno"> 1531</span> </div><div class="line"><a name="l01532"></a><span class="lineno"> 1532</span>  <span class="comment">// Infer the tensor infos for all output slots. Throws an exception on failure</span></div><div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>  optGraph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>();</div><div class="line"><a name="l01534"></a><span class="lineno"> 1534</span> </div><div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>  <span class="comment">// Perform optimisation passes</span></div><div class="line"><a name="l01536"></a><span class="lineno"> 1536</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="l01537"></a><span class="lineno"> 1537</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#aba7b0ca6192b8b58ecd517a82b4f378e">SquashEqualTransposeSiblings</a>(),</div><div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a29f8d97b2d74f99c88298881cd1d825b">SquashEqualReshapeSiblings</a>(),</div><div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#aa31127c77d2117f78d43ca2958dcae19">OptimizeInversePermutes</a>(),</div><div class="line"><a name="l01540"></a><span class="lineno"> 1540</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a2f9d1a13be2ac1c4213729a0ef181fc0">OptimizeInverseTransposes</a>(),</div><div class="line"><a name="l01541"></a><span class="lineno"> 1541</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#aafc70d5af99400ff5ea7991825658b2f">MovePermuteUp</a>(),</div><div class="line"><a name="l01542"></a><span class="lineno"> 1542</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a5918588fa316cf4c23f1cf02c81ee706">MoveTransposeUp</a>(),</div><div class="line"><a name="l01543"></a><span class="lineno"> 1543</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#ae0b1382e3af141896a46531c50e8863f">PermuteAsReshape</a>(),</div><div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#ad1aaeee71293f34d9f65d2dd2792830d">TransposeAsReshape</a>(),</div><div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a8341ca3512ebafb19d60eba44d40d9e4">OptimizeConsecutiveReshapes</a>(),</div><div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#add2180a15cdcf5a229de32bb956cb224">FoldPadIntoConvolution2d</a>(),</div><div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a17d1279f5f8e3b92c328b1ed3b6fd549">PermuteAndBatchToSpaceAsDepthToSpace</a>(),</div><div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a98f54d4391347d517c7a7869e7707203">TransposeAndBatchToSpaceAsDepthToSpace</a>(),</div><div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#aa52c06792e18dc13030e82476f706f9e">FuseBatchNormIntoConvolution2DFloat32</a>(),</div><div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a8a81178ddcebb93ec0c35b6e6284273c">FuseBatchNormIntoConvolution2DFloat16</a>(),</div><div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#a56e54a818166a2f4b2c1a7f76a3629ff">FuseBatchNormIntoDepthwiseConvolution2DFloat32</a>(),</div><div class="line"><a name="l01552"></a><span class="lineno"> 1552</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#ab40bb51feca46649eb9d00522bfe51f6">FuseBatchNormIntoDepthwiseConvolution2DFloat16</a>()));</div><div class="line"><a name="l01553"></a><span class="lineno"> 1553</span> </div><div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>  <span class="comment">// If Fp32 to Fp16 optimization is set convert Fp32 network to Fp16</span></div><div class="line"><a name="l01555"></a><span class="lineno"> 1555</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="l01556"></a><span class="lineno"> 1556</span>  {</div><div class="line"><a name="l01557"></a><span class="lineno"> 1557</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="l01558"></a><span class="lineno"> 1558</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="l01559"></a><span class="lineno"> 1559</span>  }</div><div class="line"><a name="l01560"></a><span class="lineno"> 1560</span> </div><div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>  <span class="comment">// If Fp32 to Bf16 optimization is set convert Fp32 network to Bf16</span></div><div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>  <span class="comment">// Convert input of Convolution2d and FullyConnected from Fp32 to Bf16</span></div><div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>  <span class="comment">// Only Constant weight of Convolution2d and FullyConnected are converted from Fp32 to Bf16</span></div><div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>  <span class="keywordflow">if</span> (options.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a11f463726addcc1d2845266997d79e9c">m_ReduceFp32ToBf16</a>)</div><div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>  {</div><div class="line"><a name="l01566"></a><span class="lineno"> 1566</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#aeb70f8fcf5180bdd5c94be7bb2f9d176">Fp32NetworkToBf16Converter</a>()));</div><div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>  }</div><div class="line"><a name="l01568"></a><span class="lineno"> 1568</span> </div><div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>  <span class="comment">// Initialize backend settings</span></div><div class="line"><a name="l01570"></a><span class="lineno"> 1570</span>  <a class="code" href="structarmnn_1_1_backend_settings.xhtml">BackendSettings</a> backendSettings(backendPreferences, deviceSpec);</div><div class="line"><a name="l01571"></a><span class="lineno"> 1571</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="l01572"></a><span class="lineno"> 1572</span>  {</div><div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>  std::stringstream failureMsg;</div><div class="line"><a name="l01574"></a><span class="lineno"> 1574</span>  failureMsg << <span class="stringliteral">"None of the preferred backends "</span> << backendPreferences</div><div class="line"><a name="l01575"></a><span class="lineno"> 1575</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="l01576"></a><span class="lineno"> 1576</span>  <a class="code" href="namespacearmnn.xhtml#a7658f93d899c8646515a29370e6aa994">ReportError</a>(failureMsg.str(), messages);</div><div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(failureMsg.str());</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"> 1580</span>  <span class="comment">// Create a map to temporarily hold initialized backend objects</span></div><div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>  <a class="code" href="classarmnn_1_1_tensor_handle_factory_registry.xhtml">TensorHandleFactoryRegistry</a> tensorHandleFactoryRegistry;</div><div class="line"><a name="l01582"></a><span class="lineno"> 1582</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="l01583"></a><span class="lineno"> 1583</span> </div><div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>  <span class="comment">// Assign an available backend to each layer</span></div><div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a> firstLayer = optGraph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2387033802383edbdc95f9bbb12a707e">begin</a>();</div><div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>  <a class="code" href="classarmnn_1_1_graph.xhtml#acc25db0641c1c22faf95af3bb49080c9">Graph::Iterator</a> lastLayer = optGraph.<a class="code" href="classarmnn_1_1_graph.xhtml#ab45dae688fc5d8983727abffa4389003">end</a>();</div><div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> assignBackendsResult = <a class="code" href="namespacearmnn.xhtml#a224df72b3d7a3bba8609bc167286e3f7">AssignBackends</a>(optNetObjPtr-><a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a374d52340ec8dc02a819acc20fb5aa92">pOptimizedNetworkImpl</a>.get(),</div><div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>  backendSettings,</div><div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>  firstLayer,</div><div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>  lastLayer,</div><div class="line"><a name="l01591"></a><span class="lineno"> 1591</span>  messages);</div><div class="line"><a name="l01592"></a><span class="lineno"> 1592</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="l01593"></a><span class="lineno"> 1593</span>  {</div><div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>  <span class="comment">// Failed to assign a backend to each layer</span></div><div class="line"><a name="l01595"></a><span class="lineno"> 1595</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Failed to assign a backend to each layer"</span>);</div><div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>  }</div><div class="line"><a name="l01597"></a><span class="lineno"> 1597</span> </div><div class="line"><a name="l01598"></a><span class="lineno"> 1598</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="l01599"></a><span class="lineno"> 1599</span>  <a class="code" href="namespacearmnn_1_1optimizations.xhtml#ae1509d340bc981b11101c3316ee8afd6">OptimizeInverseConversionsFp32</a>()));</div><div class="line"><a name="l01600"></a><span class="lineno"> 1600</span> </div><div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>  <span class="comment">// Apply the backend-specific optimizations</span></div><div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> backendOptimizationResult = <a class="code" href="namespacearmnn.xhtml#a9f31d956861d8277fa5f8fb877dbbb6c">ApplyBackendOptimizations</a>(optNetObjPtr-><a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a374d52340ec8dc02a819acc20fb5aa92">pOptimizedNetworkImpl</a>.get(),</div><div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>  backendSettings,</div><div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>  backends,</div><div class="line"><a name="l01605"></a><span class="lineno"> 1605</span>  options.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a71194277c60153a5f86539f5d39f01db">m_ModelOptions</a>,</div><div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>  messages);</div><div class="line"><a name="l01607"></a><span class="lineno"> 1607</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="l01608"></a><span class="lineno"> 1608</span>  {</div><div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>  <span class="comment">// Failed to apply the backend-specific optimizations</span></div><div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Failed to apply the backend-specific optimizations"</span>);</div><div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>  }</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>  <span class="comment">// If the debug flag is set, then insert a DebugLayer after each layer</span></div><div class="line"><a name="l01614"></a><span class="lineno"> 1614</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="l01615"></a><span class="lineno"> 1615</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="l01616"></a><span class="lineno"> 1616</span>  {</div><div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>  <a class="code" href="classarmnn_1_1_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="l01618"></a><span class="lineno"> 1618</span>  }</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="comment">// Calculate the compatibility strategies for tensor handles</span></div><div class="line"><a name="l01621"></a><span class="lineno"> 1621</span>  <a class="code" href="structarmnn_1_1_optimization_result.xhtml">OptimizationResult</a> strategyResult = <a class="code" href="namespacearmnn.xhtml#a86541d11fcad5246a78cbc21d637a504">SelectTensorHandleStrategy</a>(optGraph,</div><div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>  backends,</div><div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>  tensorHandleFactoryRegistry,</div><div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>  options.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a05c1bba6ba3ecc1339d4c4c10c0d8890">m_ImportEnabled</a>,</div><div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>  messages);</div><div class="line"><a name="l01626"></a><span class="lineno"> 1626</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="l01627"></a><span class="lineno"> 1627</span>  {</div><div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>  <span class="comment">// Failed to apply the backend-specific optimizations</span></div><div class="line"><a name="l01629"></a><span class="lineno"> 1629</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="l01630"></a><span class="lineno"> 1630</span>  }</div><div class="line"><a name="l01631"></a><span class="lineno"> 1631</span> </div><div class="line"><a name="l01632"></a><span class="lineno"> 1632</span>  <span class="comment">// Based on the tensor handle strategy determined above, insert copy layers where required.</span></div><div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>  optGraph.<a class="code" href="classarmnn_1_1_graph.xhtml#ad1bbee7bf5f93b792675886f57d3ebe0">AddCompatibilityLayers</a>(backends, tensorHandleFactoryRegistry);</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>  <span class="comment">// Convert constants</span></div><div class="line"><a name="l01636"></a><span class="lineno"> 1636</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="l01637"></a><span class="lineno"> 1637</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="l01638"></a><span class="lineno"> 1638</span> </div><div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>  <span class="comment">// Run backend specific optimizations (deprecated)</span></div><div class="line"><a name="l01640"></a><span class="lineno"> 1640</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="l01641"></a><span class="lineno"> 1641</span>  {</div><div class="line"><a name="l01642"></a><span class="lineno"> 1642</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="l01643"></a><span class="lineno"> 1643</span>  <span class="keyword">auto</span> backendPtr = factoryFun();</div><div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(backendPtr.get() != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l01645"></a><span class="lineno"> 1645</span> </div><div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>  <a class="code" href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>  <span class="keyword">auto</span> backendSpecificOptimizations = backendPtr->GetOptimizations();</div><div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>  <a class="code" href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="line"><a name="l01649"></a><span class="lineno"> 1649</span> </div><div class="line"><a name="l01650"></a><span class="lineno"> 1650</span>  <span class="keywordflow">if</span> (!backendSpecificOptimizations.empty())</div><div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>  {</div><div class="line"><a name="l01652"></a><span class="lineno"> 1652</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">Optimizer::Pass</a>(optNetObjPtr-><a class="code" href="classarmnn_1_1_i_optimized_network.xhtml#a374d52340ec8dc02a819acc20fb5aa92">pOptimizedNetworkImpl</a>->GetGraph(), backendSpecificOptimizations);</div><div class="line"><a name="l01653"></a><span class="lineno"> 1653</span>  }</div><div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>  }</div><div class="line"><a name="l01655"></a><span class="lineno"> 1655</span> </div><div class="line"><a name="l01656"></a><span class="lineno"> 1656</span>  <span class="keywordflow">return</span> optNet;</div><div class="line"><a name="l01657"></a><span class="lineno"> 1657</span> }</div><div class="line"><a name="l01658"></a><span class="lineno"> 1658</span> <span class="keywordtype">bool</span> NetworkImpl::GetShapeInferenceMethod()</div><div class="line"><a name="l01659"></a><span class="lineno"> 1659</span> {</div><div class="line"><a name="l01660"></a><span class="lineno"> 1660</span>  <span class="keywordflow">if</span> (m_NetworkOptions.size() > 0 && m_NetworkOptions[0].GetBackendId().Get() == <span class="stringliteral">"ShapeInferenceMethod"</span>)</div><div class="line"><a name="l01661"></a><span class="lineno"> 1661</span>  {</div><div class="line"><a name="l01662"></a><span class="lineno"> 1662</span>  <span class="keywordflow">return</span> m_NetworkOptions[0].GetOption(0).GetValue().AsBool();</div><div class="line"><a name="l01663"></a><span class="lineno"> 1663</span>  }</div><div class="line"><a name="l01664"></a><span class="lineno"> 1664</span> </div><div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l01666"></a><span class="lineno"> 1666</span> }</div><div class="line"><a name="l01667"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a55e83c091dbe02c2ca6d3b33a902ae02"> 1667</a></span> <a class="code" href="classarmnn_1_1_network_impl.xhtml#a55e83c091dbe02c2ca6d3b33a902ae02">NetworkImpl::NetworkImpl</a>(<a class="code" href="namespacearmnn.xhtml#a4de71c3661093e5c4ae7775114f43413">NetworkOptions</a> networkOptions)</div><div class="line"><a name="l01668"></a><span class="lineno"> 1668</span> : m_NetworkOptions(networkOptions),</div><div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>  m_Graph(<a class="code" href="namespacestd.xhtml">std</a>::make_unique<<a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>>(GetShapeInferenceMethod()))</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> </div><div class="line"><a name="l01672"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ad443897d51b291c83d81d809af07f4e0"> 1672</a></span> <a class="code" href="classarmnn_1_1_network_impl.xhtml#ad443897d51b291c83d81d809af07f4e0">NetworkImpl::~NetworkImpl</a>()</div><div class="line"><a name="l01673"></a><span class="lineno"> 1673</span> {</div><div class="line"><a name="l01674"></a><span class="lineno"> 1674</span> }</div><div class="line"><a name="l01675"></a><span class="lineno"> 1675</span> </div><div class="line"><a name="l01676"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#aff3fde909d22ed157046682e70129259"> 1676</a></span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">Status</a> <a class="code" href="classarmnn_1_1_network_impl.xhtml#aff3fde909d22ed157046682e70129259">NetworkImpl::PrintGraph</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>  m_Graph->Print();</div><div class="line"><a name="l01679"></a><span class="lineno"> 1679</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">Status::Success</a>;</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_network_impl.xhtml#aa6c1c42ea44777302e87ce0fad5ac510"> 1682</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#aa6c1c42ea44777302e87ce0fad5ac510">NetworkImpl::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="l01683"></a><span class="lineno"> 1683</span> {</div><div class="line"><a name="l01684"></a><span class="lineno"> 1684</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="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"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a9a9bcc00ae3d96343c93b437d6f77088"> 1687</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a9a9bcc00ae3d96343c93b437d6f77088">NetworkImpl::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="l01688"></a><span class="lineno"> 1688</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01689"></a><span class="lineno"> 1689</span> {</div><div class="line"><a name="l01690"></a><span class="lineno"> 1690</span>  <span class="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="l01691"></a><span class="lineno"> 1691</span> }</div><div class="line"><a name="l01692"></a><span class="lineno"> 1692</span> </div><div class="line"><a name="l01693"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ac7dca3e9f2ab2f2c64b42fc59a67188a"> 1693</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ac7dca3e9f2ab2f2c64b42fc59a67188a">NetworkImpl::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="l01694"></a><span class="lineno"> 1694</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01695"></a><span class="lineno"> 1695</span> {</div><div class="line"><a name="l01696"></a><span class="lineno"> 1696</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="l01697"></a><span class="lineno"> 1697</span> }</div><div class="line"><a name="l01698"></a><span class="lineno"> 1698</span> </div><div class="line"><a name="l01699"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a095a9b700dc857edc23c5d3bf088919f"> 1699</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a095a9b700dc857edc23c5d3bf088919f">NetworkImpl::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="l01700"></a><span class="lineno"> 1700</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01701"></a><span class="lineno"> 1701</span> {</div><div class="line"><a name="l01702"></a><span class="lineno"> 1702</span>  <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="l01703"></a><span class="lineno"> 1703</span> }</div><div class="line"><a name="l01704"></a><span class="lineno"> 1704</span> </div><div class="line"><a name="l01705"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#afc94c35c0bbe852a60046bf2e756b2e0"> 1705</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#afc94c35c0bbe852a60046bf2e756b2e0">NetworkImpl::AddFillLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fill_descriptor.xhtml">FillDescriptor</a>& fillDescriptor,</div><div class="line"><a name="l01706"></a><span class="lineno"> 1706</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01707"></a><span class="lineno"> 1707</span> {</div><div class="line"><a name="l01708"></a><span class="lineno"> 1708</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_fill_layer.xhtml">FillLayer</a>>(fillDescriptor, name);</div><div class="line"><a name="l01709"></a><span class="lineno"> 1709</span> }</div><div class="line"><a name="l01710"></a><span class="lineno"> 1710</span> </div><div class="line"><a name="l01711"></a><span class="lineno"> 1711</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* NetworkImpl::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="l01712"></a><span class="lineno"> 1712</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="l01713"></a><span class="lineno"> 1713</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="l01714"></a><span class="lineno"> 1714</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01715"></a><span class="lineno"> 1715</span> {</div><div class="line"><a name="l01716"></a><span class="lineno"> 1716</span>  <span class="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="l01717"></a><span class="lineno"> 1717</span>  {</div><div class="line"><a name="l01718"></a><span class="lineno"> 1718</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="l01719"></a><span class="lineno"> 1719</span>  }</div><div class="line"><a name="l01720"></a><span class="lineno"> 1720</span> </div><div class="line"><a name="l01721"></a><span class="lineno"> 1721</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="l01722"></a><span class="lineno"> 1722</span> </div><div class="line"><a name="l01723"></a><span class="lineno"> 1723</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="l01724"></a><span class="lineno"> 1724</span> </div><div class="line"><a name="l01725"></a><span class="lineno"> 1725</span>  <span class="keywordflow">if</span> (fullyConnectedDescriptor.m_BiasEnabled)</div><div class="line"><a name="l01726"></a><span class="lineno"> 1726</span>  {</div><div class="line"><a name="l01727"></a><span class="lineno"> 1727</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="l01728"></a><span class="lineno"> 1728</span>  }</div><div class="line"><a name="l01729"></a><span class="lineno"> 1729</span> </div><div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l01731"></a><span class="lineno"> 1731</span> }</div><div class="line"><a name="l01732"></a><span class="lineno"> 1732</span> </div><div class="line"><a name="l01733"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ae3ef3b97542241d331a38613ae189f3e"> 1733</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ae3ef3b97542241d331a38613ae189f3e">NetworkImpl::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="l01734"></a><span class="lineno"> 1734</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="l01735"></a><span class="lineno"> 1735</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="l01736"></a><span class="lineno"> 1736</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01737"></a><span class="lineno"> 1737</span> {</div><div class="line"><a name="l01738"></a><span class="lineno"> 1738</span>  <span class="keywordflow">return</span> AddFullyConnectedLayerImpl(fullyConnectedDescriptor, weights, biases, name);</div><div class="line"><a name="l01739"></a><span class="lineno"> 1739</span> }</div><div class="line"><a name="l01740"></a><span class="lineno"> 1740</span> </div><div class="line"><a name="l01741"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a44349b3cf3ff8d476d5f930946e89c47"> 1741</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ae3ef3b97542241d331a38613ae189f3e">NetworkImpl::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="l01742"></a><span class="lineno"> 1742</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="l01743"></a><span class="lineno"> 1743</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01744"></a><span class="lineno"> 1744</span> {</div><div class="line"><a name="l01745"></a><span class="lineno"> 1745</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> biases;</div><div class="line"><a name="l01746"></a><span class="lineno"> 1746</span>  <span class="keywordflow">return</span> AddFullyConnectedLayerImpl(fullyConnectedDescriptor, weights, biases, name);</div><div class="line"><a name="l01747"></a><span class="lineno"> 1747</span> }</div><div class="line"><a name="l01748"></a><span class="lineno"> 1748</span> </div><div class="line"><a name="l01749"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a5811dfe93a4938dbbc9e8dd266e339de"> 1749</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ae3ef3b97542241d331a38613ae189f3e">NetworkImpl::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="l01750"></a><span class="lineno"> 1750</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="l01751"></a><span class="lineno"> 1751</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="l01752"></a><span class="lineno"> 1752</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01753"></a><span class="lineno"> 1753</span> {</div><div class="line"><a name="l01754"></a><span class="lineno"> 1754</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> optionalBiases(biases);</div><div class="line"><a name="l01755"></a><span class="lineno"> 1755</span>  <span class="keywordflow">return</span> AddFullyConnectedLayerImpl(fullyConnectedDescriptor, weights, optionalBiases, name);</div><div class="line"><a name="l01756"></a><span class="lineno"> 1756</span> }</div><div class="line"><a name="l01757"></a><span class="lineno"> 1757</span> </div><div class="line"><a name="l01758"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#aea1059833739d3dccebb3a03ec35a1e6"> 1758</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#aea1059833739d3dccebb3a03ec35a1e6">NetworkImpl::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="l01759"></a><span class="lineno"> 1759</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01760"></a><span class="lineno"> 1760</span> {</div><div class="line"><a name="l01761"></a><span class="lineno"> 1761</span>  <span class="keywordflow">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="l01762"></a><span class="lineno"> 1762</span> }</div><div class="line"><a name="l01763"></a><span class="lineno"> 1763</span> </div><div class="line"><a name="l01764"></a><span class="lineno"> 1764</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* NetworkImpl::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="l01765"></a><span class="lineno"> 1765</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="l01766"></a><span class="lineno"> 1766</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="l01767"></a><span class="lineno"> 1767</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01768"></a><span class="lineno"> 1768</span> {</div><div class="line"><a name="l01769"></a><span class="lineno"> 1769</span>  <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="l01770"></a><span class="lineno"> 1770</span>  {</div><div class="line"><a name="l01771"></a><span class="lineno"> 1771</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="l01772"></a><span class="lineno"> 1772</span>  }</div><div class="line"><a name="l01773"></a><span class="lineno"> 1773</span> </div><div class="line"><a name="l01774"></a><span class="lineno"> 1774</span>  <span class="keyword">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="l01775"></a><span class="lineno"> 1775</span> </div><div class="line"><a name="l01776"></a><span class="lineno"> 1776</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="l01777"></a><span class="lineno"> 1777</span> </div><div class="line"><a name="l01778"></a><span class="lineno"> 1778</span>  <span class="keywordflow">if</span> (convolution2dDescriptor.m_BiasEnabled)</div><div class="line"><a name="l01779"></a><span class="lineno"> 1779</span>  {</div><div class="line"><a name="l01780"></a><span class="lineno"> 1780</span>  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="l01781"></a><span class="lineno"> 1781</span>  }</div><div class="line"><a name="l01782"></a><span class="lineno"> 1782</span> </div><div class="line"><a name="l01783"></a><span class="lineno"> 1783</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l01784"></a><span class="lineno"> 1784</span> }</div><div class="line"><a name="l01785"></a><span class="lineno"> 1785</span> </div><div class="line"><a name="l01786"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a178a72bbf254eff34a807a5ca27cb61f"> 1786</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a178a72bbf254eff34a807a5ca27cb61f">NetworkImpl::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="l01787"></a><span class="lineno"> 1787</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="l01788"></a><span class="lineno"> 1788</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="l01789"></a><span class="lineno"> 1789</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01790"></a><span class="lineno"> 1790</span> {</div><div class="line"><a name="l01791"></a><span class="lineno"> 1791</span>  <span class="keywordflow">return</span> AddConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l01792"></a><span class="lineno"> 1792</span> }</div><div class="line"><a name="l01793"></a><span class="lineno"> 1793</span> </div><div class="line"><a name="l01794"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#abaf4646307d946a74c1bf7bdc8efb83b"> 1794</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a178a72bbf254eff34a807a5ca27cb61f">NetworkImpl::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="l01795"></a><span class="lineno"> 1795</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="l01796"></a><span class="lineno"> 1796</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01797"></a><span class="lineno"> 1797</span> {</div><div class="line"><a name="l01798"></a><span class="lineno"> 1798</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> biases;</div><div class="line"><a name="l01799"></a><span class="lineno"> 1799</span>  <span class="keywordflow">return</span> AddConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l01800"></a><span class="lineno"> 1800</span> }</div><div class="line"><a name="l01801"></a><span class="lineno"> 1801</span> </div><div class="line"><a name="l01802"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#aa54008a5c8e4916bd1da8e0923a2e049"> 1802</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a178a72bbf254eff34a807a5ca27cb61f">NetworkImpl::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="l01803"></a><span class="lineno"> 1803</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="l01804"></a><span class="lineno"> 1804</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="l01805"></a><span class="lineno"> 1805</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01806"></a><span class="lineno"> 1806</span> {</div><div class="line"><a name="l01807"></a><span class="lineno"> 1807</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> optionalBiases(biases);</div><div class="line"><a name="l01808"></a><span class="lineno"> 1808</span>  <span class="keywordflow">return</span> AddConvolution2dLayerImpl(convolution2dDescriptor, weights, optionalBiases, name);</div><div class="line"><a name="l01809"></a><span class="lineno"> 1809</span> }</div><div class="line"><a name="l01810"></a><span class="lineno"> 1810</span> </div><div class="line"><a name="l01811"></a><span class="lineno"> 1811</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* NetworkImpl::AddDepthwiseConvolution2dLayerImpl(</div><div class="line"><a name="l01812"></a><span class="lineno"> 1812</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="l01813"></a><span class="lineno"> 1813</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="l01814"></a><span class="lineno"> 1814</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="l01815"></a><span class="lineno"> 1815</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01816"></a><span class="lineno"> 1816</span> {</div><div class="line"><a name="l01817"></a><span class="lineno"> 1817</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="l01818"></a><span class="lineno"> 1818</span>  {</div><div class="line"><a name="l01819"></a><span class="lineno"> 1819</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="l01820"></a><span class="lineno"> 1820</span>  }</div><div class="line"><a name="l01821"></a><span class="lineno"> 1821</span> </div><div class="line"><a name="l01822"></a><span class="lineno"> 1822</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="l01823"></a><span class="lineno"> 1823</span> </div><div class="line"><a name="l01824"></a><span class="lineno"> 1824</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="l01825"></a><span class="lineno"> 1825</span> </div><div class="line"><a name="l01826"></a><span class="lineno"> 1826</span>  <span class="keywordflow">if</span> (convolution2dDescriptor.m_BiasEnabled)</div><div class="line"><a name="l01827"></a><span class="lineno"> 1827</span>  {</div><div class="line"><a name="l01828"></a><span class="lineno"> 1828</span>  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="l01829"></a><span class="lineno"> 1829</span>  }</div><div class="line"><a name="l01830"></a><span class="lineno"> 1830</span> </div><div class="line"><a name="l01831"></a><span class="lineno"> 1831</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l01832"></a><span class="lineno"> 1832</span> }</div><div class="line"><a name="l01833"></a><span class="lineno"> 1833</span> </div><div class="line"><a name="l01834"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#af1853466264ac187607c96b501a74e2b"> 1834</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#af1853466264ac187607c96b501a74e2b">NetworkImpl::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="l01835"></a><span class="lineno"> 1835</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01836"></a><span class="lineno"> 1836</span> {</div><div class="line"><a name="l01837"></a><span class="lineno"> 1837</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="l01838"></a><span class="lineno"> 1838</span> }</div><div class="line"><a name="l01839"></a><span class="lineno"> 1839</span> </div><div class="line"><a name="l01840"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a58f85a122022527a525318473f93d4ef"> 1840</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a58f85a122022527a525318473f93d4ef">NetworkImpl::AddDepthwiseConvolution2dLayer</a>(</div><div class="line"><a name="l01841"></a><span class="lineno"> 1841</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="l01842"></a><span class="lineno"> 1842</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="l01843"></a><span class="lineno"> 1843</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="l01844"></a><span class="lineno"> 1844</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01845"></a><span class="lineno"> 1845</span> {</div><div class="line"><a name="l01846"></a><span class="lineno"> 1846</span>  <span class="keywordflow">return</span> AddDepthwiseConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l01847"></a><span class="lineno"> 1847</span> }</div><div class="line"><a name="l01848"></a><span class="lineno"> 1848</span> </div><div class="line"><a name="l01849"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a02b981a246785121fd822a2eb996e716"> 1849</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a58f85a122022527a525318473f93d4ef">NetworkImpl::AddDepthwiseConvolution2dLayer</a>(</div><div class="line"><a name="l01850"></a><span class="lineno"> 1850</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="l01851"></a><span class="lineno"> 1851</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="l01852"></a><span class="lineno"> 1852</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01853"></a><span class="lineno"> 1853</span> {</div><div class="line"><a name="l01854"></a><span class="lineno"> 1854</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> biases;</div><div class="line"><a name="l01855"></a><span class="lineno"> 1855</span>  <span class="keywordflow">return</span> AddDepthwiseConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name);</div><div class="line"><a name="l01856"></a><span class="lineno"> 1856</span> }</div><div class="line"><a name="l01857"></a><span class="lineno"> 1857</span> </div><div class="line"><a name="l01858"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#af326ea7544a5510e4d3465a3a842b4d4"> 1858</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a58f85a122022527a525318473f93d4ef">NetworkImpl::AddDepthwiseConvolution2dLayer</a>(</div><div class="line"><a name="l01859"></a><span class="lineno"> 1859</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="l01860"></a><span class="lineno"> 1860</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="l01861"></a><span class="lineno"> 1861</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="l01862"></a><span class="lineno"> 1862</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01863"></a><span class="lineno"> 1863</span> {</div><div class="line"><a name="l01864"></a><span class="lineno"> 1864</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> optionalBiases(biases);</div><div class="line"><a name="l01865"></a><span class="lineno"> 1865</span>  <span class="keywordflow">return</span> AddDepthwiseConvolution2dLayerImpl(convolution2dDescriptor, weights, optionalBiases, name);</div><div class="line"><a name="l01866"></a><span class="lineno"> 1866</span> }</div><div class="line"><a name="l01867"></a><span class="lineno"> 1867</span> </div><div class="line"><a name="l01868"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ac1134a94265293ea7347180260f787d2"> 1868</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ac1134a94265293ea7347180260f787d2">NetworkImpl::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="l01869"></a><span class="lineno"> 1869</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="l01870"></a><span class="lineno"> 1870</span> {</div><div class="line"><a name="l01871"></a><span class="lineno"> 1871</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="l01872"></a><span class="lineno"> 1872</span> </div><div class="line"><a name="l01873"></a><span class="lineno"> 1873</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="l01874"></a><span class="lineno"> 1874</span> </div><div class="line"><a name="l01875"></a><span class="lineno"> 1875</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l01876"></a><span class="lineno"> 1876</span> }</div><div class="line"><a name="l01877"></a><span class="lineno"> 1877</span> </div><div class="line"><a name="l01878"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a11f49d84f0cfd8df65f4d5206cd43b6d"> 1878</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a11f49d84f0cfd8df65f4d5206cd43b6d">NetworkImpl::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="l01879"></a><span class="lineno"> 1879</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01880"></a><span class="lineno"> 1880</span> {</div><div class="line"><a name="l01881"></a><span class="lineno"> 1881</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="l01882"></a><span class="lineno"> 1882</span> }</div><div class="line"><a name="l01883"></a><span class="lineno"> 1883</span> </div><div class="line"><a name="l01884"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ae913b4351b7027f37eb5657dd7867733"> 1884</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ae913b4351b7027f37eb5657dd7867733">NetworkImpl::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="l01885"></a><span class="lineno"> 1885</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01886"></a><span class="lineno"> 1886</span> {</div><div class="line"><a name="l01887"></a><span class="lineno"> 1887</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="l01888"></a><span class="lineno"> 1888</span> }</div><div class="line"><a name="l01889"></a><span class="lineno"> 1889</span> </div><div class="line"><a name="l01890"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#aa51350bdd4976f3dd5a4e9d00a906b2c"> 1890</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#aa51350bdd4976f3dd5a4e9d00a906b2c">NetworkImpl::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="l01891"></a><span class="lineno"> 1891</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01892"></a><span class="lineno"> 1892</span> {</div><div class="line"><a name="l01893"></a><span class="lineno"> 1893</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="l01894"></a><span class="lineno"> 1894</span> }</div><div class="line"><a name="l01895"></a><span class="lineno"> 1895</span> </div><div class="line"><a name="l01896"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#adc8c1c505bca8233fe238b3b7fb80200"> 1896</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#adc8c1c505bca8233fe238b3b7fb80200">NetworkImpl::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="l01897"></a><span class="lineno"> 1897</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01898"></a><span class="lineno"> 1898</span> {</div><div class="line"><a name="l01899"></a><span class="lineno"> 1899</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="l01900"></a><span class="lineno"> 1900</span> }</div><div class="line"><a name="l01901"></a><span class="lineno"> 1901</span> </div><div class="line"><a name="l01902"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a6c5376053e1f875776d7bc36fd0b7d45"> 1902</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a6c5376053e1f875776d7bc36fd0b7d45">NetworkImpl::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="l01903"></a><span class="lineno"> 1903</span> normalizationDescriptor,</div><div class="line"><a name="l01904"></a><span class="lineno"> 1904</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01905"></a><span class="lineno"> 1905</span> {</div><div class="line"><a name="l01906"></a><span class="lineno"> 1906</span>  <span class="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="l01907"></a><span class="lineno"> 1907</span> }</div><div class="line"><a name="l01908"></a><span class="lineno"> 1908</span> </div><div class="line"><a name="l01909"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a8de6b047fcaff95df48dca683e1f3aa4"> 1909</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a8de6b047fcaff95df48dca683e1f3aa4">NetworkImpl::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="l01910"></a><span class="lineno"> 1910</span> {</div><div class="line"><a name="l01911"></a><span class="lineno"> 1911</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="l01912"></a><span class="lineno"> 1912</span> }</div><div class="line"><a name="l01913"></a><span class="lineno"> 1913</span> </div><div class="line"><a name="l01914"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a30528a3bd85a0dba158bd14e252bd68a"> 1914</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a30528a3bd85a0dba158bd14e252bd68a">NetworkImpl::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="l01915"></a><span class="lineno"> 1915</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01916"></a><span class="lineno"> 1916</span> {</div><div class="line"><a name="l01917"></a><span class="lineno"> 1917</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="l01918"></a><span class="lineno"> 1918</span> }</div><div class="line"><a name="l01919"></a><span class="lineno"> 1919</span> </div><div class="line"><a name="l01920"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a6f6d81d8a4f1f85f3616e8306760061c"> 1920</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a6f6d81d8a4f1f85f3616e8306760061c">NetworkImpl::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="l01921"></a><span class="lineno"> 1921</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01922"></a><span class="lineno"> 1922</span> {</div><div class="line"><a name="l01923"></a><span class="lineno"> 1923</span>  <span class="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="l01924"></a><span class="lineno"> 1924</span> }</div><div class="line"><a name="l01925"></a><span class="lineno"> 1925</span> </div><div class="line"><a name="l01926"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a57590d7777211673d2052f702f0b07a1"> 1926</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a57590d7777211673d2052f702f0b07a1">NetworkImpl::AddMaximumLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01927"></a><span class="lineno"> 1927</span> {</div><div class="line"><a name="l01928"></a><span class="lineno"> 1928</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="l01929"></a><span class="lineno"> 1929</span> }</div><div class="line"><a name="l01930"></a><span class="lineno"> 1930</span> </div><div class="line"><a name="l01931"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a4bfd8dee1a0315b651e977c672c0847c"> 1931</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a4bfd8dee1a0315b651e977c672c0847c">NetworkImpl::AddMinimumLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01932"></a><span class="lineno"> 1932</span> {</div><div class="line"><a name="l01933"></a><span class="lineno"> 1933</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="l01934"></a><span class="lineno"> 1934</span> }</div><div class="line"><a name="l01935"></a><span class="lineno"> 1935</span> </div><div class="line"><a name="l01936"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a34aa5f1a405a6886f79c97d53f9f65fd"> 1936</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a34aa5f1a405a6886f79c97d53f9f65fd">NetworkImpl::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="l01937"></a><span class="lineno"> 1937</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01938"></a><span class="lineno"> 1938</span> {</div><div class="line"><a name="l01939"></a><span class="lineno"> 1939</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network_impl.xhtml#aea1059833739d3dccebb3a03ec35a1e6">AddConcatLayer</a>(mergerDescriptor, name);</div><div class="line"><a name="l01940"></a><span class="lineno"> 1940</span> }</div><div class="line"><a name="l01941"></a><span class="lineno"> 1941</span> </div><div class="line"><a name="l01942"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a030e8e7c1f6980ec9b2ac06b683ee74e"> 1942</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a030e8e7c1f6980ec9b2ac06b683ee74e">NetworkImpl::AddAbsLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span> * name)</div><div class="line"><a name="l01943"></a><span class="lineno"> 1943</span> {</div><div class="line"><a name="l01944"></a><span class="lineno"> 1944</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network_impl.xhtml#a095a9b700dc857edc23c5d3bf088919f">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="l01945"></a><span class="lineno"> 1945</span> }</div><div class="line"><a name="l01946"></a><span class="lineno"> 1946</span> </div><div class="line"><a name="l01947"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a39f1b38d89c4de186742eafcbb3b1319"> 1947</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a39f1b38d89c4de186742eafcbb3b1319">NetworkImpl::AddAdditionLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01948"></a><span class="lineno"> 1948</span> {</div><div class="line"><a name="l01949"></a><span class="lineno"> 1949</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="l01950"></a><span class="lineno"> 1950</span> }</div><div class="line"><a name="l01951"></a><span class="lineno"> 1951</span> </div><div class="line"><a name="l01952"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#abb59f6ba9988dae88e0f48e68d87fc32"> 1952</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#abb59f6ba9988dae88e0f48e68d87fc32">NetworkImpl::AddMultiplicationLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01953"></a><span class="lineno"> 1953</span> {</div><div class="line"><a name="l01954"></a><span class="lineno"> 1954</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="l01955"></a><span class="lineno"> 1955</span> }</div><div class="line"><a name="l01956"></a><span class="lineno"> 1956</span> </div><div class="line"><a name="l01957"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#af5790069aa11fd1c5bb2e17cecb06528"> 1957</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#af5790069aa11fd1c5bb2e17cecb06528">NetworkImpl::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="l01958"></a><span class="lineno"> 1958</span> {</div><div class="line"><a name="l01959"></a><span class="lineno"> 1959</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="l01960"></a><span class="lineno"> 1960</span> }</div><div class="line"><a name="l01961"></a><span class="lineno"> 1961</span> </div><div class="line"><a name="l01962"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a8f798e19187ac7ae6ae6153ee64ab645"> 1962</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a8f798e19187ac7ae6ae6153ee64ab645">NetworkImpl::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="l01963"></a><span class="lineno"> 1963</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="l01964"></a><span class="lineno"> 1964</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="l01965"></a><span class="lineno"> 1965</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="l01966"></a><span class="lineno"> 1966</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="l01967"></a><span class="lineno"> 1967</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01968"></a><span class="lineno"> 1968</span> {</div><div class="line"><a name="l01969"></a><span class="lineno"> 1969</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="l01970"></a><span class="lineno"> 1970</span> </div><div class="line"><a name="l01971"></a><span class="lineno"> 1971</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="l01972"></a><span class="lineno"> 1972</span>  layer->m_Variance = std::make_unique<ScopedCpuTensorHandle>(variance);</div><div class="line"><a name="l01973"></a><span class="lineno"> 1973</span>  layer->m_Beta = std::make_unique<ScopedCpuTensorHandle>(beta);</div><div class="line"><a name="l01974"></a><span class="lineno"> 1974</span>  layer->m_Gamma = std::make_unique<ScopedCpuTensorHandle>(gamma);</div><div class="line"><a name="l01975"></a><span class="lineno"> 1975</span> </div><div class="line"><a name="l01976"></a><span class="lineno"> 1976</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l01977"></a><span class="lineno"> 1977</span> }</div><div class="line"><a name="l01978"></a><span class="lineno"> 1978</span> </div><div class="line"><a name="l01979"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a25563024ec66627ee83727244a53e944"> 1979</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a25563024ec66627ee83727244a53e944">NetworkImpl::AddRankLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01980"></a><span class="lineno"> 1980</span> {</div><div class="line"><a name="l01981"></a><span class="lineno"> 1981</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_rank_layer.xhtml">RankLayer</a>>(name);</div><div class="line"><a name="l01982"></a><span class="lineno"> 1982</span> }</div><div class="line"><a name="l01983"></a><span class="lineno"> 1983</span> </div><div class="line"><a name="l01984"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ae0cfae1ea51669892608a1a060d24fa0"> 1984</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ae0cfae1ea51669892608a1a060d24fa0">NetworkImpl::AddReduceLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_reduce_descriptor.xhtml">ReduceDescriptor</a>& reduceDescriptor,</div><div class="line"><a name="l01985"></a><span class="lineno"> 1985</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01986"></a><span class="lineno"> 1986</span> {</div><div class="line"><a name="l01987"></a><span class="lineno"> 1987</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_reduce_layer.xhtml">ReduceLayer</a>>(reduceDescriptor, name);</div><div class="line"><a name="l01988"></a><span class="lineno"> 1988</span> }</div><div class="line"><a name="l01989"></a><span class="lineno"> 1989</span> </div><div class="line"><a name="l01990"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#acc9f9b91636c0714d96a3cba92c624f9"> 1990</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#acc9f9b91636c0714d96a3cba92c624f9">NetworkImpl::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="l01991"></a><span class="lineno"> 1991</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l01992"></a><span class="lineno"> 1992</span> {</div><div class="line"><a name="l01993"></a><span class="lineno"> 1993</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">ResizeDescriptor</a> resizeDescriptor;</div><div class="line"><a name="l01994"></a><span class="lineno"> 1994</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="l01995"></a><span class="lineno"> 1995</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="l01996"></a><span class="lineno"> 1996</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="l01997"></a><span class="lineno"> 1997</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="l01998"></a><span class="lineno"> 1998</span>  resizeDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#ae1a4b3b6c60552509b89747cebb900a2">m_AlignCorners</a> = descriptor.<a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#ae1a4b3b6c60552509b89747cebb900a2">m_AlignCorners</a>;</div><div class="line"><a name="l01999"></a><span class="lineno"> 1999</span>  resizeDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a4022d5107338aaf5eb7abebf78a1360b">m_HalfPixelCenters</a> = descriptor.<a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#a4022d5107338aaf5eb7abebf78a1360b">m_HalfPixelCenters</a>;</div><div class="line"><a name="l02000"></a><span class="lineno"> 2000</span> </div><div class="line"><a name="l02001"></a><span class="lineno"> 2001</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="l02002"></a><span class="lineno"> 2002</span> }</div><div class="line"><a name="l02003"></a><span class="lineno"> 2003</span> </div><div class="line"><a name="l02004"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ad97411f1fcb2c30c212483d8c673506f"> 2004</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ad97411f1fcb2c30c212483d8c673506f">NetworkImpl::AddResizeLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">ResizeDescriptor</a>& resizeDescriptor, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02005"></a><span class="lineno"> 2005</span> {</div><div class="line"><a name="l02006"></a><span class="lineno"> 2006</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="l02007"></a><span class="lineno"> 2007</span> }</div><div class="line"><a name="l02008"></a><span class="lineno"> 2008</span> </div><div class="line"><a name="l02009"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#abd61d3e7ab67551c75bc219bbc4baeb5"> 2009</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#abd61d3e7ab67551c75bc219bbc4baeb5">NetworkImpl::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="l02010"></a><span class="lineno"> 2010</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02011"></a><span class="lineno"> 2011</span> {</div><div class="line"><a name="l02012"></a><span class="lineno"> 2012</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="l02013"></a><span class="lineno"> 2013</span> }</div><div class="line"><a name="l02014"></a><span class="lineno"> 2014</span> </div><div class="line"><a name="l02015"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#aaff51346dadec2c1430abf007fed4cc9"> 2015</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#aaff51346dadec2c1430abf007fed4cc9">NetworkImpl::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="l02016"></a><span class="lineno"> 2016</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02017"></a><span class="lineno"> 2017</span> {</div><div class="line"><a name="l02018"></a><span class="lineno"> 2018</span>  <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="l02019"></a><span class="lineno"> 2019</span> }</div><div class="line"><a name="l02020"></a><span class="lineno"> 2020</span> </div><div class="line"><a name="l02021"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a83b33973ca12078166b2436b313627b9"> 2021</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a83b33973ca12078166b2436b313627b9">NetworkImpl::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="l02022"></a><span class="lineno"> 2022</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02023"></a><span class="lineno"> 2023</span> {</div><div class="line"><a name="l02024"></a><span class="lineno"> 2024</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="l02025"></a><span class="lineno"> 2025</span> }</div><div class="line"><a name="l02026"></a><span class="lineno"> 2026</span> </div><div class="line"><a name="l02027"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a1aa567f46c30960851c02847dc7b4215"> 2027</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a1aa567f46c30960851c02847dc7b4215">NetworkImpl::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="l02028"></a><span class="lineno"> 2028</span> {</div><div class="line"><a name="l02029"></a><span class="lineno"> 2029</span>  <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_constant_layer.xhtml">ConstantLayer</a>>(name);</div><div class="line"><a name="l02030"></a><span class="lineno"> 2030</span> </div><div class="line"><a name="l02031"></a><span class="lineno"> 2031</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="l02032"></a><span class="lineno"> 2032</span> </div><div class="line"><a name="l02033"></a><span class="lineno"> 2033</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l02034"></a><span class="lineno"> 2034</span> }</div><div class="line"><a name="l02035"></a><span class="lineno"> 2035</span> </div><div class="line"><a name="l02036"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a8a3380be13fba749fc4208214b049347"> 2036</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a8a3380be13fba749fc4208214b049347">NetworkImpl::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="l02037"></a><span class="lineno"> 2037</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02038"></a><span class="lineno"> 2038</span> {</div><div class="line"><a name="l02039"></a><span class="lineno"> 2039</span>  <span class="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="l02040"></a><span class="lineno"> 2040</span> }</div><div class="line"><a name="l02041"></a><span class="lineno"> 2041</span> </div><div class="line"><a name="l02042"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a72b9d30e9d555bb5c35460b62faedf0d"> 2042</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a72b9d30e9d555bb5c35460b62faedf0d">NetworkImpl::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="l02043"></a><span class="lineno"> 2043</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02044"></a><span class="lineno"> 2044</span> {</div><div class="line"><a name="l02045"></a><span class="lineno"> 2045</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="l02046"></a><span class="lineno"> 2046</span> }</div><div class="line"><a name="l02047"></a><span class="lineno"> 2047</span> </div><div class="line"><a name="l02048"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a19bad0cc50526ca9f4f84a688812cdf5"> 2048</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a19bad0cc50526ca9f4f84a688812cdf5">NetworkImpl::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="l02049"></a><span class="lineno"> 2049</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02050"></a><span class="lineno"> 2050</span> {</div><div class="line"><a name="l02051"></a><span class="lineno"> 2051</span>  <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="l02052"></a><span class="lineno"> 2052</span> }</div><div class="line"><a name="l02053"></a><span class="lineno"> 2053</span> </div><div class="line"><a name="l02054"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a435ea88480b8645026dd45fd692663a1"> 2054</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a435ea88480b8645026dd45fd692663a1">NetworkImpl::AddFloorLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02055"></a><span class="lineno"> 2055</span> {</div><div class="line"><a name="l02056"></a><span class="lineno"> 2056</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="l02057"></a><span class="lineno"> 2057</span> }</div><div class="line"><a name="l02058"></a><span class="lineno"> 2058</span> </div><div class="line"><a name="l02059"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a0a2fdd4f442952c97a8f24de6700473a"> 2059</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a0a2fdd4f442952c97a8f24de6700473a">NetworkImpl::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="l02060"></a><span class="lineno"> 2060</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="l02061"></a><span class="lineno"> 2061</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02062"></a><span class="lineno"> 2062</span> {</div><div class="line"><a name="l02063"></a><span class="lineno"> 2063</span>  <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="l02064"></a><span class="lineno"> 2064</span> </div><div class="line"><a name="l02065"></a><span class="lineno"> 2065</span>  <span class="comment">//Lstm Basic Parameters</span></div><div class="line"><a name="l02066"></a><span class="lineno"> 2066</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="l02067"></a><span class="lineno"> 2067</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="l02068"></a><span class="lineno"> 2068</span>  layer->m_BasicParameters.m_InputToCellWeights =</div><div class="line"><a name="l02069"></a><span class="lineno"> 2069</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="l02070"></a><span class="lineno"> 2070</span>  layer->m_BasicParameters.m_InputToOutputWeights =</div><div class="line"><a name="l02071"></a><span class="lineno"> 2071</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="l02072"></a><span class="lineno"> 2072</span>  layer->m_BasicParameters.m_RecurrentToForgetWeights =</div><div class="line"><a name="l02073"></a><span class="lineno"> 2073</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="l02074"></a><span class="lineno"> 2074</span>  layer->m_BasicParameters.m_RecurrentToCellWeights =</div><div class="line"><a name="l02075"></a><span class="lineno"> 2075</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="l02076"></a><span class="lineno"> 2076</span>  layer->m_BasicParameters.m_RecurrentToOutputWeights =</div><div class="line"><a name="l02077"></a><span class="lineno"> 2077</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="l02078"></a><span class="lineno"> 2078</span>  layer->m_BasicParameters.m_ForgetGateBias =</div><div class="line"><a name="l02079"></a><span class="lineno"> 2079</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="l02080"></a><span class="lineno"> 2080</span>  layer->m_BasicParameters.m_CellBias =</div><div class="line"><a name="l02081"></a><span class="lineno"> 2081</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="l02082"></a><span class="lineno"> 2082</span>  layer->m_BasicParameters.m_OutputGateBias =</div><div class="line"><a name="l02083"></a><span class="lineno"> 2083</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="l02084"></a><span class="lineno"> 2084</span> </div><div class="line"><a name="l02085"></a><span class="lineno"> 2085</span>  <span class="comment">//Lstm Cifg parameters</span></div><div class="line"><a name="l02086"></a><span class="lineno"> 2086</span>  <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div><div class="line"><a name="l02087"></a><span class="lineno"> 2087</span>  {</div><div class="line"><a name="l02088"></a><span class="lineno"> 2088</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="l02089"></a><span class="lineno"> 2089</span>  {</div><div class="line"><a name="l02090"></a><span class="lineno"> 2090</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="l02091"></a><span class="lineno"> 2091</span>  <span class="stringliteral">"when CIFG is disabled."</span>);</div><div class="line"><a name="l02092"></a><span class="lineno"> 2092</span>  }</div><div class="line"><a name="l02093"></a><span class="lineno"> 2093</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="l02094"></a><span class="lineno"> 2094</span>  {</div><div class="line"><a name="l02095"></a><span class="lineno"> 2095</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="l02096"></a><span class="lineno"> 2096</span>  <span class="stringliteral">"AddLstmLayer: Recurrent To Input Weights cannot be NULL "</span></div><div class="line"><a name="l02097"></a><span class="lineno"> 2097</span>  <span class="stringliteral">"when CIFG is disabled."</span>);</div><div class="line"><a name="l02098"></a><span class="lineno"> 2098</span>  }</div><div class="line"><a name="l02099"></a><span class="lineno"> 2099</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="l02100"></a><span class="lineno"> 2100</span>  {</div><div class="line"><a name="l02101"></a><span class="lineno"> 2101</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="l02102"></a><span class="lineno"> 2102</span>  <span class="stringliteral">"when CIFG is disabled."</span>);</div><div class="line"><a name="l02103"></a><span class="lineno"> 2103</span>  }</div><div class="line"><a name="l02104"></a><span class="lineno"> 2104</span>  layer->m_CifgParameters.m_InputToInputWeights =</div><div class="line"><a name="l02105"></a><span class="lineno"> 2105</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="l02106"></a><span class="lineno"> 2106</span>  layer->m_CifgParameters.m_RecurrentToInputWeights =</div><div class="line"><a name="l02107"></a><span class="lineno"> 2107</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="l02108"></a><span class="lineno"> 2108</span>  layer->m_CifgParameters.m_InputGateBias =</div><div class="line"><a name="l02109"></a><span class="lineno"> 2109</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="l02110"></a><span class="lineno"> 2110</span>  }</div><div class="line"><a name="l02111"></a><span class="lineno"> 2111</span> </div><div class="line"><a name="l02112"></a><span class="lineno"> 2112</span>  <span class="comment">//Lstm projection parameters</span></div><div class="line"><a name="l02113"></a><span class="lineno"> 2113</span>  <span class="keywordflow">if</span>(descriptor.m_ProjectionEnabled)</div><div class="line"><a name="l02114"></a><span class="lineno"> 2114</span>  {</div><div class="line"><a name="l02115"></a><span class="lineno"> 2115</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="l02116"></a><span class="lineno"> 2116</span>  {</div><div class="line"><a name="l02117"></a><span class="lineno"> 2117</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="l02118"></a><span class="lineno"> 2118</span>  <span class="stringliteral">"when projection is enabled."</span>);</div><div class="line"><a name="l02119"></a><span class="lineno"> 2119</span>  }</div><div class="line"><a name="l02120"></a><span class="lineno"> 2120</span>  layer->m_ProjectionParameters.m_ProjectionWeights =</div><div class="line"><a name="l02121"></a><span class="lineno"> 2121</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="l02122"></a><span class="lineno"> 2122</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="l02123"></a><span class="lineno"> 2123</span>  {</div><div class="line"><a name="l02124"></a><span class="lineno"> 2124</span>  layer->m_ProjectionParameters.m_ProjectionBias =</div><div class="line"><a name="l02125"></a><span class="lineno"> 2125</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="l02126"></a><span class="lineno"> 2126</span>  }</div><div class="line"><a name="l02127"></a><span class="lineno"> 2127</span>  }</div><div class="line"><a name="l02128"></a><span class="lineno"> 2128</span> </div><div class="line"><a name="l02129"></a><span class="lineno"> 2129</span>  <span class="comment">//Lstm Peephole params</span></div><div class="line"><a name="l02130"></a><span class="lineno"> 2130</span>  <span class="keywordflow">if</span>(descriptor.m_PeepholeEnabled)</div><div class="line"><a name="l02131"></a><span class="lineno"> 2131</span>  {</div><div class="line"><a name="l02132"></a><span class="lineno"> 2132</span>  <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div><div class="line"><a name="l02133"></a><span class="lineno"> 2133</span>  {</div><div class="line"><a name="l02134"></a><span class="lineno"> 2134</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="l02135"></a><span class="lineno"> 2135</span>  {</div><div class="line"><a name="l02136"></a><span class="lineno"> 2136</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 Input Weights cannot be NULL "</span></div><div class="line"><a name="l02137"></a><span class="lineno"> 2137</span>  <span class="stringliteral">"when Peephole is enabled and CIFG disabled."</span>);</div><div class="line"><a name="l02138"></a><span class="lineno"> 2138</span>  }</div><div class="line"><a name="l02139"></a><span class="lineno"> 2139</span> </div><div class="line"><a name="l02140"></a><span class="lineno"> 2140</span>  layer->m_PeepholeParameters.m_CellToInputWeights =</div><div class="line"><a name="l02141"></a><span class="lineno"> 2141</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="l02142"></a><span class="lineno"> 2142</span>  }</div><div class="line"><a name="l02143"></a><span class="lineno"> 2143</span> </div><div class="line"><a name="l02144"></a><span class="lineno"> 2144</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="l02145"></a><span class="lineno"> 2145</span>  {</div><div class="line"><a name="l02146"></a><span class="lineno"> 2146</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="l02147"></a><span class="lineno"> 2147</span>  <span class="stringliteral">"when Peephole is enabled."</span>);</div><div class="line"><a name="l02148"></a><span class="lineno"> 2148</span>  }</div><div class="line"><a name="l02149"></a><span class="lineno"> 2149</span>  <span class="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="l02150"></a><span class="lineno"> 2150</span>  {</div><div class="line"><a name="l02151"></a><span class="lineno"> 2151</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="l02152"></a><span class="lineno"> 2152</span>  <span class="stringliteral">"when Peephole is enabled."</span>);</div><div class="line"><a name="l02153"></a><span class="lineno"> 2153</span>  }</div><div class="line"><a name="l02154"></a><span class="lineno"> 2154</span> </div><div class="line"><a name="l02155"></a><span class="lineno"> 2155</span>  layer->m_PeepholeParameters.m_CellToForgetWeights =</div><div class="line"><a name="l02156"></a><span class="lineno"> 2156</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="l02157"></a><span class="lineno"> 2157</span>  layer->m_PeepholeParameters.m_CellToOutputWeights =</div><div class="line"><a name="l02158"></a><span class="lineno"> 2158</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="l02159"></a><span class="lineno"> 2159</span>  }</div><div class="line"><a name="l02160"></a><span class="lineno"> 2160</span> </div><div class="line"><a name="l02161"></a><span class="lineno"> 2161</span>  <span class="comment">//Lstm Layer Normalization params</span></div><div class="line"><a name="l02162"></a><span class="lineno"> 2162</span>  <span class="keywordflow">if</span>(descriptor.m_LayerNormEnabled)</div><div class="line"><a name="l02163"></a><span class="lineno"> 2163</span>  {</div><div class="line"><a name="l02164"></a><span class="lineno"> 2164</span>  <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div><div class="line"><a name="l02165"></a><span class="lineno"> 2165</span>  {</div><div class="line"><a name="l02166"></a><span class="lineno"> 2166</span>  <span class="keywordflow">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="l02167"></a><span class="lineno"> 2167</span>  {</div><div class="line"><a name="l02168"></a><span class="lineno"> 2168</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="l02169"></a><span class="lineno"> 2169</span>  <span class="stringliteral">"when layer normalization is enabled and CIFG disabled."</span>);</div><div class="line"><a name="l02170"></a><span class="lineno"> 2170</span>  }</div><div class="line"><a name="l02171"></a><span class="lineno"> 2171</span>  layer->m_LayerNormParameters.m_InputLayerNormWeights =</div><div class="line"><a name="l02172"></a><span class="lineno"> 2172</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="l02173"></a><span class="lineno"> 2173</span>  }</div><div class="line"><a name="l02174"></a><span class="lineno"> 2174</span> </div><div class="line"><a name="l02175"></a><span class="lineno"> 2175</span>  <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="l02176"></a><span class="lineno"> 2176</span>  {</div><div class="line"><a name="l02177"></a><span class="lineno"> 2177</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="l02178"></a><span class="lineno"> 2178</span>  <span class="stringliteral">"when layer normalization is enabled."</span>);</div><div class="line"><a name="l02179"></a><span class="lineno"> 2179</span>  }</div><div class="line"><a name="l02180"></a><span class="lineno"> 2180</span>  <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="l02181"></a><span class="lineno"> 2181</span>  {</div><div class="line"><a name="l02182"></a><span class="lineno"> 2182</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="l02183"></a><span class="lineno"> 2183</span>  <span class="stringliteral">"when layer normalization is enabled."</span>);</div><div class="line"><a name="l02184"></a><span class="lineno"> 2184</span>  }</div><div class="line"><a name="l02185"></a><span class="lineno"> 2185</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="l02186"></a><span class="lineno"> 2186</span>  {</div><div class="line"><a name="l02187"></a><span class="lineno"> 2187</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="l02188"></a><span class="lineno"> 2188</span>  <span class="stringliteral">"when layer normalization is enabled."</span>);</div><div class="line"><a name="l02189"></a><span class="lineno"> 2189</span>  }</div><div class="line"><a name="l02190"></a><span class="lineno"> 2190</span>  layer->m_LayerNormParameters.m_ForgetLayerNormWeights =</div><div class="line"><a name="l02191"></a><span class="lineno"> 2191</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="l02192"></a><span class="lineno"> 2192</span>  layer->m_LayerNormParameters.m_CellLayerNormWeights =</div><div class="line"><a name="l02193"></a><span class="lineno"> 2193</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="l02194"></a><span class="lineno"> 2194</span>  layer->m_LayerNormParameters.m_OutputLayerNormWeights =</div><div class="line"><a name="l02195"></a><span class="lineno"> 2195</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="l02196"></a><span class="lineno"> 2196</span>  }</div><div class="line"><a name="l02197"></a><span class="lineno"> 2197</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l02198"></a><span class="lineno"> 2198</span> }</div><div class="line"><a name="l02199"></a><span class="lineno"> 2199</span> </div><div class="line"><a name="l02200"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a0aeb4e528cf6ba4b7caca14a94fbcafe"> 2200</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a0aeb4e528cf6ba4b7caca14a94fbcafe">NetworkImpl::AddDivisionLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02201"></a><span class="lineno"> 2201</span> {</div><div class="line"><a name="l02202"></a><span class="lineno"> 2202</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_division_layer.xhtml">DivisionLayer</a>>(name);</div><div class="line"><a name="l02203"></a><span class="lineno"> 2203</span> }</div><div class="line"><a name="l02204"></a><span class="lineno"> 2204</span> </div><div class="line"><a name="l02205"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#af13795cdf49e63d8bc3cb409592cdb9d"> 2205</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#af13795cdf49e63d8bc3cb409592cdb9d">NetworkImpl::AddSubtractionLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02206"></a><span class="lineno"> 2206</span> {</div><div class="line"><a name="l02207"></a><span class="lineno"> 2207</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="l02208"></a><span class="lineno"> 2208</span> }</div><div class="line"><a name="l02209"></a><span class="lineno"> 2209</span> </div><div class="line"><a name="l02210"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ad4726f9b7dd11db250d2a494a8a39494"> 2210</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ad4726f9b7dd11db250d2a494a8a39494">NetworkImpl::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="l02211"></a><span class="lineno"> 2211</span> {</div><div class="line"><a name="l02212"></a><span class="lineno"> 2212</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="l02213"></a><span class="lineno"> 2213</span> }</div><div class="line"><a name="l02214"></a><span class="lineno"> 2214</span> </div><div class="line"><a name="l02215"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a6e2df484ecc65bc82712590b96e04df4"> 2215</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a6e2df484ecc65bc82712590b96e04df4">NetworkImpl::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="l02216"></a><span class="lineno"> 2216</span> {</div><div class="line"><a name="l02217"></a><span class="lineno"> 2217</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="l02218"></a><span class="lineno"> 2218</span> }</div><div class="line"><a name="l02219"></a><span class="lineno"> 2219</span> </div><div class="line"><a name="l02220"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a0b426a3feffc76e66d73b5761806e899"> 2220</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a> *<a class="code" href="classarmnn_1_1_network_impl.xhtml#a0b426a3feffc76e66d73b5761806e899">NetworkImpl::AddQuantizeLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span> *name)</div><div class="line"><a name="l02221"></a><span class="lineno"> 2221</span> {</div><div class="line"><a name="l02222"></a><span class="lineno"> 2222</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="l02223"></a><span class="lineno"> 2223</span> }</div><div class="line"><a name="l02224"></a><span class="lineno"> 2224</span> </div><div class="line"><a name="l02225"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a357aca04172ed22fa32e5a69122b0fec"> 2225</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a357aca04172ed22fa32e5a69122b0fec">NetworkImpl::AddDequantizeLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02226"></a><span class="lineno"> 2226</span> {</div><div class="line"><a name="l02227"></a><span class="lineno"> 2227</span>  <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="l02228"></a><span class="lineno"> 2228</span> }</div><div class="line"><a name="l02229"></a><span class="lineno"> 2229</span> </div><div class="line"><a name="l02230"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ac5c93cad39a690af862d49ffaec0d3c0"> 2230</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ac5c93cad39a690af862d49ffaec0d3c0">NetworkImpl::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="l02231"></a><span class="lineno"> 2231</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02232"></a><span class="lineno"> 2232</span> {</div><div class="line"><a name="l02233"></a><span class="lineno"> 2233</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="l02234"></a><span class="lineno"> 2234</span> }</div><div class="line"><a name="l02235"></a><span class="lineno"> 2235</span> </div><div class="line"><a name="l02236"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a9fcd8cc35c8ae7d092705e7c4c2a7c69"> 2236</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a9fcd8cc35c8ae7d092705e7c4c2a7c69">NetworkImpl::AddGreaterLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02237"></a><span class="lineno"> 2237</span> {</div><div class="line"><a name="l02238"></a><span class="lineno"> 2238</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network_impl.xhtml#ac7dca3e9f2ab2f2c64b42fc59a67188a">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="l02239"></a><span class="lineno"> 2239</span> }</div><div class="line"><a name="l02240"></a><span class="lineno"> 2240</span> </div><div class="line"><a name="l02241"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a7ba52238d75f06ff59a0d2ba613acefe"> 2241</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a7ba52238d75f06ff59a0d2ba613acefe">NetworkImpl::AddEqualLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02242"></a><span class="lineno"> 2242</span> {</div><div class="line"><a name="l02243"></a><span class="lineno"> 2243</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network_impl.xhtml#ac7dca3e9f2ab2f2c64b42fc59a67188a">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="l02244"></a><span class="lineno"> 2244</span> }</div><div class="line"><a name="l02245"></a><span class="lineno"> 2245</span> </div><div class="line"><a name="l02246"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ae2f5193942457daafa733998f3e61449"> 2246</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ae2f5193942457daafa733998f3e61449">NetworkImpl::AddRsqrtLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span> * name)</div><div class="line"><a name="l02247"></a><span class="lineno"> 2247</span> {</div><div class="line"><a name="l02248"></a><span class="lineno"> 2248</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network_impl.xhtml#a095a9b700dc857edc23c5d3bf088919f">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="l02249"></a><span class="lineno"> 2249</span> }</div><div class="line"><a name="l02250"></a><span class="lineno"> 2250</span> </div><div class="line"><a name="l02251"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a31f19249d1491464736b08b967be68b4"> 2251</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a31f19249d1491464736b08b967be68b4">NetworkImpl::AddGatherLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02252"></a><span class="lineno"> 2252</span> {</div><div class="line"><a name="l02253"></a><span class="lineno"> 2253</span>  <a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">GatherDescriptor</a> gatherDescriptor{};</div><div class="line"><a name="l02254"></a><span class="lineno"> 2254</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_network_impl.xhtml#a31f19249d1491464736b08b967be68b4">AddGatherLayer</a>(gatherDescriptor, name);</div><div class="line"><a name="l02255"></a><span class="lineno"> 2255</span> }</div><div class="line"><a name="l02256"></a><span class="lineno"> 2256</span> </div><div class="line"><a name="l02257"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#aaf5e9645806f49d0fcd7ac07ba187f4e"> 2257</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a31f19249d1491464736b08b967be68b4">NetworkImpl::AddGatherLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">GatherDescriptor</a>& gatherDescriptor,</div><div class="line"><a name="l02258"></a><span class="lineno"> 2258</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02259"></a><span class="lineno"> 2259</span> {</div><div class="line"><a name="l02260"></a><span class="lineno"> 2260</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_gather_layer.xhtml">GatherLayer</a>>(gatherDescriptor, name);</div><div class="line"><a name="l02261"></a><span class="lineno"> 2261</span> }</div><div class="line"><a name="l02262"></a><span class="lineno"> 2262</span> </div><div class="line"><a name="l02263"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a0f19808bdada45222e72edf7671a275a"> 2263</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a0f19808bdada45222e72edf7671a275a">NetworkImpl::AddMergeLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02264"></a><span class="lineno"> 2264</span> {</div><div class="line"><a name="l02265"></a><span class="lineno"> 2265</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="l02266"></a><span class="lineno"> 2266</span> }</div><div class="line"><a name="l02267"></a><span class="lineno"> 2267</span> </div><div class="line"><a name="l02268"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a26e69cda5fe9642f9198c24ae5fdf9bc"> 2268</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a26e69cda5fe9642f9198c24ae5fdf9bc">NetworkImpl::AddSwitchLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02269"></a><span class="lineno"> 2269</span> {</div><div class="line"><a name="l02270"></a><span class="lineno"> 2270</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="l02271"></a><span class="lineno"> 2271</span> }</div><div class="line"><a name="l02272"></a><span class="lineno"> 2272</span> </div><div class="line"><a name="l02273"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a6d614a503a34ea3712b388aa4340ddbe"> 2273</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a6d614a503a34ea3712b388aa4340ddbe">NetworkImpl::AddPreluLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02274"></a><span class="lineno"> 2274</span> {</div><div class="line"><a name="l02275"></a><span class="lineno"> 2275</span>  <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="l02276"></a><span class="lineno"> 2276</span> }</div><div class="line"><a name="l02277"></a><span class="lineno"> 2277</span> </div><div class="line"><a name="l02278"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a41fd7b56923d5625bac2cbfebed1a393"> 2278</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a41fd7b56923d5625bac2cbfebed1a393">NetworkImpl::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="l02279"></a><span class="lineno"> 2279</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="l02280"></a><span class="lineno"> 2280</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="l02281"></a><span class="lineno"> 2281</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02282"></a><span class="lineno"> 2282</span> {</div><div class="line"><a name="l02283"></a><span class="lineno"> 2283</span>  <span class="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="l02284"></a><span class="lineno"> 2284</span>  {</div><div class="line"><a name="l02285"></a><span class="lineno"> 2285</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="l02286"></a><span class="lineno"> 2286</span>  }</div><div class="line"><a name="l02287"></a><span class="lineno"> 2287</span> </div><div class="line"><a name="l02288"></a><span class="lineno"> 2288</span>  <span class="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="l02289"></a><span class="lineno"> 2289</span> </div><div class="line"><a name="l02290"></a><span class="lineno"> 2290</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="l02291"></a><span class="lineno"> 2291</span> </div><div class="line"><a name="l02292"></a><span class="lineno"> 2292</span>  <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</div><div class="line"><a name="l02293"></a><span class="lineno"> 2293</span>  {</div><div class="line"><a name="l02294"></a><span class="lineno"> 2294</span>  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="l02295"></a><span class="lineno"> 2295</span>  }</div><div class="line"><a name="l02296"></a><span class="lineno"> 2296</span> </div><div class="line"><a name="l02297"></a><span class="lineno"> 2297</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l02298"></a><span class="lineno"> 2298</span> }</div><div class="line"><a name="l02299"></a><span class="lineno"> 2299</span> </div><div class="line"><a name="l02300"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#ab067ba4ee9416d93abb8a52f3dc8feba"> 2300</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#ab067ba4ee9416d93abb8a52f3dc8feba">NetworkImpl::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="l02301"></a><span class="lineno"> 2301</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02302"></a><span class="lineno"> 2302</span> {</div><div class="line"><a name="l02303"></a><span class="lineno"> 2303</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="l02304"></a><span class="lineno"> 2304</span> }</div><div class="line"><a name="l02305"></a><span class="lineno"> 2305</span> </div><div class="line"><a name="l02306"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a446181daeb60b49cbcfd9f907f974ec1"> 2306</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a446181daeb60b49cbcfd9f907f974ec1">NetworkImpl::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="l02307"></a><span class="lineno"> 2307</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02308"></a><span class="lineno"> 2308</span> {</div><div class="line"><a name="l02309"></a><span class="lineno"> 2309</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="l02310"></a><span class="lineno"> 2310</span> }</div><div class="line"><a name="l02311"></a><span class="lineno"> 2311</span> </div><div class="line"><a name="l02312"></a><span class="lineno"> 2312</span> </div><div class="line"><a name="l02313"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a74894d085e78ff80f45fc09dd2381f08"> 2313</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a74894d085e78ff80f45fc09dd2381f08">NetworkImpl::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="l02314"></a><span class="lineno"> 2314</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02315"></a><span class="lineno"> 2315</span> {</div><div class="line"><a name="l02316"></a><span class="lineno"> 2316</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="l02317"></a><span class="lineno"> 2317</span> }</div><div class="line"><a name="l02318"></a><span class="lineno"> 2318</span> </div><div class="line"><a name="l02319"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a40067b05f30a3ab65568c826df7a8ea7"> 2319</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a40067b05f30a3ab65568c826df7a8ea7">NetworkImpl::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="l02320"></a><span class="lineno"> 2320</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02321"></a><span class="lineno"> 2321</span> {</div><div class="line"><a name="l02322"></a><span class="lineno"> 2322</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="l02323"></a><span class="lineno"> 2323</span> </div><div class="line"><a name="l02324"></a><span class="lineno"> 2324</span>  <span class="comment">// InputToX weights</span></div><div class="line"><a name="l02325"></a><span class="lineno"> 2325</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="l02326"></a><span class="lineno"> 2326</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="l02327"></a><span class="lineno"> 2327</span>  layer->m_QuantizedLstmParameters.m_InputToForgetWeights =</div><div class="line"><a name="l02328"></a><span class="lineno"> 2328</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="l02329"></a><span class="lineno"> 2329</span>  layer->m_QuantizedLstmParameters.m_InputToCellWeights =</div><div class="line"><a name="l02330"></a><span class="lineno"> 2330</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="l02331"></a><span class="lineno"> 2331</span>  layer->m_QuantizedLstmParameters.m_InputToOutputWeights =</div><div class="line"><a name="l02332"></a><span class="lineno"> 2332</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="l02333"></a><span class="lineno"> 2333</span> </div><div class="line"><a name="l02334"></a><span class="lineno"> 2334</span>  <span class="comment">// RecurrentToX weights</span></div><div class="line"><a name="l02335"></a><span class="lineno"> 2335</span>  layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights =</div><div class="line"><a name="l02336"></a><span class="lineno"> 2336</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="l02337"></a><span class="lineno"> 2337</span>  layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights =</div><div class="line"><a name="l02338"></a><span class="lineno"> 2338</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="l02339"></a><span class="lineno"> 2339</span>  layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights =</div><div class="line"><a name="l02340"></a><span class="lineno"> 2340</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="l02341"></a><span class="lineno"> 2341</span>  layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights =</div><div class="line"><a name="l02342"></a><span class="lineno"> 2342</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="l02343"></a><span class="lineno"> 2343</span> </div><div class="line"><a name="l02344"></a><span class="lineno"> 2344</span>  <span class="comment">// Bias</span></div><div class="line"><a name="l02345"></a><span class="lineno"> 2345</span>  layer->m_QuantizedLstmParameters.m_InputGateBias =</div><div class="line"><a name="l02346"></a><span class="lineno"> 2346</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="l02347"></a><span class="lineno"> 2347</span>  layer->m_QuantizedLstmParameters.m_ForgetGateBias =</div><div class="line"><a name="l02348"></a><span class="lineno"> 2348</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="l02349"></a><span class="lineno"> 2349</span>  layer->m_QuantizedLstmParameters.m_CellBias =</div><div class="line"><a name="l02350"></a><span class="lineno"> 2350</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="l02351"></a><span class="lineno"> 2351</span>  layer->m_QuantizedLstmParameters.m_OutputGateBias =</div><div class="line"><a name="l02352"></a><span class="lineno"> 2352</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="l02353"></a><span class="lineno"> 2353</span> </div><div class="line"><a name="l02354"></a><span class="lineno"> 2354</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l02355"></a><span class="lineno"> 2355</span> }</div><div class="line"><a name="l02356"></a><span class="lineno"> 2356</span> </div><div class="line"><a name="l02357"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a2acbae0b9e98c94b843677484775c86a"> 2357</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a2acbae0b9e98c94b843677484775c86a">NetworkImpl::AddQLstmLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml">QLstmDescriptor</a>& descriptor,</div><div class="line"><a name="l02358"></a><span class="lineno"> 2358</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="l02359"></a><span class="lineno"> 2359</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02360"></a><span class="lineno"> 2360</span> {</div><div class="line"><a name="l02361"></a><span class="lineno"> 2361</span>  <span class="keyword">const</span> <span class="keyword">auto</span> layer = m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_q_lstm_layer.xhtml">QLstmLayer</a>>(descriptor, name);</div><div class="line"><a name="l02362"></a><span class="lineno"> 2362</span> </div><div class="line"><a name="l02363"></a><span class="lineno"> 2363</span>  <span class="comment">// QLstm Basic Parameters</span></div><div class="line"><a name="l02364"></a><span class="lineno"> 2364</span>  layer-><a class="code" href="classarmnn_1_1_q_lstm_layer.xhtml#aada2b9060461ecf785d483eee0dc071a">m_BasicParameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_basic_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">m_InputToForgetWeights</a> =</div><div class="line"><a name="l02365"></a><span class="lineno"> 2365</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="l02366"></a><span class="lineno"> 2366</span>  layer->m_BasicParameters.m_InputToCellWeights =</div><div class="line"><a name="l02367"></a><span class="lineno"> 2367</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="l02368"></a><span class="lineno"> 2368</span>  layer->m_BasicParameters.m_InputToOutputWeights =</div><div class="line"><a name="l02369"></a><span class="lineno"> 2369</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="l02370"></a><span class="lineno"> 2370</span>  layer->m_BasicParameters.m_RecurrentToForgetWeights =</div><div class="line"><a name="l02371"></a><span class="lineno"> 2371</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="l02372"></a><span class="lineno"> 2372</span>  layer->m_BasicParameters.m_RecurrentToCellWeights =</div><div class="line"><a name="l02373"></a><span class="lineno"> 2373</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="l02374"></a><span class="lineno"> 2374</span>  layer->m_BasicParameters.m_RecurrentToOutputWeights =</div><div class="line"><a name="l02375"></a><span class="lineno"> 2375</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="l02376"></a><span class="lineno"> 2376</span>  layer->m_BasicParameters.m_ForgetGateBias =</div><div class="line"><a name="l02377"></a><span class="lineno"> 2377</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="l02378"></a><span class="lineno"> 2378</span>  layer->m_BasicParameters.m_CellBias =</div><div class="line"><a name="l02379"></a><span class="lineno"> 2379</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="l02380"></a><span class="lineno"> 2380</span>  layer->m_BasicParameters.m_OutputGateBias =</div><div class="line"><a name="l02381"></a><span class="lineno"> 2381</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="l02382"></a><span class="lineno"> 2382</span> </div><div class="line"><a name="l02383"></a><span class="lineno"> 2383</span>  <span class="comment">// QLstm Cifg parameters</span></div><div class="line"><a name="l02384"></a><span class="lineno"> 2384</span>  <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div><div class="line"><a name="l02385"></a><span class="lineno"> 2385</span>  {</div><div class="line"><a name="l02386"></a><span class="lineno"> 2386</span>  <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="l02387"></a><span class="lineno"> 2387</span>  {</div><div class="line"><a name="l02388"></a><span class="lineno"> 2388</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddQLstmLayer: Input To Input Weights cannot be NULL"</span>);</div><div class="line"><a name="l02389"></a><span class="lineno"> 2389</span>  }</div><div class="line"><a name="l02390"></a><span class="lineno"> 2390</span> </div><div class="line"><a name="l02391"></a><span class="lineno"> 2391</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="l02392"></a><span class="lineno"> 2392</span>  {</div><div class="line"><a name="l02393"></a><span class="lineno"> 2393</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="l02394"></a><span class="lineno"> 2394</span>  <span class="stringliteral">"AddQLstmLayer: Recurrent To Input Weights cannot be NULL"</span>);</div><div class="line"><a name="l02395"></a><span class="lineno"> 2395</span>  }</div><div class="line"><a name="l02396"></a><span class="lineno"> 2396</span> </div><div class="line"><a name="l02397"></a><span class="lineno"> 2397</span>  <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="l02398"></a><span class="lineno"> 2398</span>  {</div><div class="line"><a name="l02399"></a><span class="lineno"> 2399</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddQLstmLayer: Input Gate Bias cannot be NULL"</span>);</div><div class="line"><a name="l02400"></a><span class="lineno"> 2400</span>  }</div><div class="line"><a name="l02401"></a><span class="lineno"> 2401</span> </div><div class="line"><a name="l02402"></a><span class="lineno"> 2402</span>  layer->m_CifgParameters.m_InputToInputWeights =</div><div class="line"><a name="l02403"></a><span class="lineno"> 2403</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="l02404"></a><span class="lineno"> 2404</span>  layer->m_CifgParameters.m_RecurrentToInputWeights =</div><div class="line"><a name="l02405"></a><span class="lineno"> 2405</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="l02406"></a><span class="lineno"> 2406</span>  layer->m_CifgParameters.m_InputGateBias =</div><div class="line"><a name="l02407"></a><span class="lineno"> 2407</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="l02408"></a><span class="lineno"> 2408</span>  }</div><div class="line"><a name="l02409"></a><span class="lineno"> 2409</span> </div><div class="line"><a name="l02410"></a><span class="lineno"> 2410</span>  <span class="comment">// QLstm Projection parameters</span></div><div class="line"><a name="l02411"></a><span class="lineno"> 2411</span>  <span class="keywordflow">if</span>(descriptor.m_ProjectionEnabled)</div><div class="line"><a name="l02412"></a><span class="lineno"> 2412</span>  {</div><div class="line"><a name="l02413"></a><span class="lineno"> 2413</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="l02414"></a><span class="lineno"> 2414</span>  {</div><div class="line"><a name="l02415"></a><span class="lineno"> 2415</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddQLstmLayer: Projection Weights cannot be NULL"</span>);</div><div class="line"><a name="l02416"></a><span class="lineno"> 2416</span>  }</div><div class="line"><a name="l02417"></a><span class="lineno"> 2417</span> </div><div class="line"><a name="l02418"></a><span class="lineno"> 2418</span>  layer->m_ProjectionParameters.m_ProjectionWeights =</div><div class="line"><a name="l02419"></a><span class="lineno"> 2419</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="l02420"></a><span class="lineno"> 2420</span> </div><div class="line"><a name="l02421"></a><span class="lineno"> 2421</span>  <span class="comment">// Projection bias is optional even if projection is enabled</span></div><div class="line"><a name="l02422"></a><span class="lineno"> 2422</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="l02423"></a><span class="lineno"> 2423</span>  {</div><div class="line"><a name="l02424"></a><span class="lineno"> 2424</span>  layer->m_ProjectionParameters.m_ProjectionBias =</div><div class="line"><a name="l02425"></a><span class="lineno"> 2425</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="l02426"></a><span class="lineno"> 2426</span>  }</div><div class="line"><a name="l02427"></a><span class="lineno"> 2427</span> </div><div class="line"><a name="l02428"></a><span class="lineno"> 2428</span>  }</div><div class="line"><a name="l02429"></a><span class="lineno"> 2429</span> </div><div class="line"><a name="l02430"></a><span class="lineno"> 2430</span>  <span class="comment">// QLstm Peephole params</span></div><div class="line"><a name="l02431"></a><span class="lineno"> 2431</span>  <span class="keywordflow">if</span>(descriptor.m_PeepholeEnabled)</div><div class="line"><a name="l02432"></a><span class="lineno"> 2432</span>  {</div><div class="line"><a name="l02433"></a><span class="lineno"> 2433</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="l02434"></a><span class="lineno"> 2434</span>  {</div><div class="line"><a name="l02435"></a><span class="lineno"> 2435</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddQLstmLayer: Cell To Forget Weights cannot be NULL"</span>);</div><div class="line"><a name="l02436"></a><span class="lineno"> 2436</span>  }</div><div class="line"><a name="l02437"></a><span class="lineno"> 2437</span> </div><div class="line"><a name="l02438"></a><span class="lineno"> 2438</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="l02439"></a><span class="lineno"> 2439</span>  {</div><div class="line"><a name="l02440"></a><span class="lineno"> 2440</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddQLstmLayer: Cell To Output Weights cannot be NULL"</span>);</div><div class="line"><a name="l02441"></a><span class="lineno"> 2441</span>  }</div><div class="line"><a name="l02442"></a><span class="lineno"> 2442</span> </div><div class="line"><a name="l02443"></a><span class="lineno"> 2443</span>  <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div><div class="line"><a name="l02444"></a><span class="lineno"> 2444</span>  {</div><div class="line"><a name="l02445"></a><span class="lineno"> 2445</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="l02446"></a><span class="lineno"> 2446</span>  {</div><div class="line"><a name="l02447"></a><span class="lineno"> 2447</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddQLstmLayer: Cell To Input Weights cannot be NULL"</span>);</div><div class="line"><a name="l02448"></a><span class="lineno"> 2448</span>  }</div><div class="line"><a name="l02449"></a><span class="lineno"> 2449</span> </div><div class="line"><a name="l02450"></a><span class="lineno"> 2450</span>  layer->m_PeepholeParameters.m_CellToInputWeights =</div><div class="line"><a name="l02451"></a><span class="lineno"> 2451</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="l02452"></a><span class="lineno"> 2452</span>  }</div><div class="line"><a name="l02453"></a><span class="lineno"> 2453</span> </div><div class="line"><a name="l02454"></a><span class="lineno"> 2454</span>  layer->m_PeepholeParameters.m_CellToForgetWeights =</div><div class="line"><a name="l02455"></a><span class="lineno"> 2455</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="l02456"></a><span class="lineno"> 2456</span>  layer->m_PeepholeParameters.m_CellToOutputWeights =</div><div class="line"><a name="l02457"></a><span class="lineno"> 2457</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="l02458"></a><span class="lineno"> 2458</span>  }</div><div class="line"><a name="l02459"></a><span class="lineno"> 2459</span> </div><div class="line"><a name="l02460"></a><span class="lineno"> 2460</span>  <span class="comment">// QLstm Layer Normalization params</span></div><div class="line"><a name="l02461"></a><span class="lineno"> 2461</span>  <span class="keywordflow">if</span>(descriptor.m_LayerNormEnabled)</div><div class="line"><a name="l02462"></a><span class="lineno"> 2462</span>  {</div><div class="line"><a name="l02463"></a><span class="lineno"> 2463</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="l02464"></a><span class="lineno"> 2464</span>  {</div><div class="line"><a name="l02465"></a><span class="lineno"> 2465</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddQLstmLayer: Forget layer normalization weights cannot be NULL"</span>);</div><div class="line"><a name="l02466"></a><span class="lineno"> 2466</span>  }</div><div class="line"><a name="l02467"></a><span class="lineno"> 2467</span> </div><div class="line"><a name="l02468"></a><span class="lineno"> 2468</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="l02469"></a><span class="lineno"> 2469</span>  {</div><div class="line"><a name="l02470"></a><span class="lineno"> 2470</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddQLstmLayer: Cell layer normalization weights cannot be NULL"</span>);</div><div class="line"><a name="l02471"></a><span class="lineno"> 2471</span>  }</div><div class="line"><a name="l02472"></a><span class="lineno"> 2472</span> </div><div class="line"><a name="l02473"></a><span class="lineno"> 2473</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="l02474"></a><span class="lineno"> 2474</span>  {</div><div class="line"><a name="l02475"></a><span class="lineno"> 2475</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddQLstmLayer: Output layer normalization weights cannot be NULL"</span>);</div><div class="line"><a name="l02476"></a><span class="lineno"> 2476</span>  }</div><div class="line"><a name="l02477"></a><span class="lineno"> 2477</span> </div><div class="line"><a name="l02478"></a><span class="lineno"> 2478</span>  <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div><div class="line"><a name="l02479"></a><span class="lineno"> 2479</span>  {</div><div class="line"><a name="l02480"></a><span class="lineno"> 2480</span>  <span class="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="l02481"></a><span class="lineno"> 2481</span>  {</div><div class="line"><a name="l02482"></a><span class="lineno"> 2482</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"AddQLstmLayer: Input layer normalization weights cannot be NULL"</span>);</div><div class="line"><a name="l02483"></a><span class="lineno"> 2483</span>  }</div><div class="line"><a name="l02484"></a><span class="lineno"> 2484</span> </div><div class="line"><a name="l02485"></a><span class="lineno"> 2485</span>  layer->m_LayerNormParameters.m_InputLayerNormWeights =</div><div class="line"><a name="l02486"></a><span class="lineno"> 2486</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="l02487"></a><span class="lineno"> 2487</span>  }</div><div class="line"><a name="l02488"></a><span class="lineno"> 2488</span> </div><div class="line"><a name="l02489"></a><span class="lineno"> 2489</span>  layer->m_LayerNormParameters.m_ForgetLayerNormWeights =</div><div class="line"><a name="l02490"></a><span class="lineno"> 2490</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="l02491"></a><span class="lineno"> 2491</span>  layer->m_LayerNormParameters.m_CellLayerNormWeights =</div><div class="line"><a name="l02492"></a><span class="lineno"> 2492</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="l02493"></a><span class="lineno"> 2493</span>  layer->m_LayerNormParameters.m_OutputLayerNormWeights =</div><div class="line"><a name="l02494"></a><span class="lineno"> 2494</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="l02495"></a><span class="lineno"> 2495</span>  }</div><div class="line"><a name="l02496"></a><span class="lineno"> 2496</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l02497"></a><span class="lineno"> 2497</span> }</div><div class="line"><a name="l02498"></a><span class="lineno"> 2498</span> </div><div class="line"><a name="l02499"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a1ff7534e1254dfb3ef8288194cca7ce3"> 2499</a></span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <a class="code" href="classarmnn_1_1_network_impl.xhtml#a1ff7534e1254dfb3ef8288194cca7ce3">NetworkImpl::AddLogicalBinaryLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_logical_binary_descriptor.xhtml">LogicalBinaryDescriptor</a>& logicalBinaryDescriptor,</div><div class="line"><a name="l02500"></a><span class="lineno"> 2500</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l02501"></a><span class="lineno"> 2501</span> {</div><div class="line"><a name="l02502"></a><span class="lineno"> 2502</span>  <span class="keywordflow">return</span> m_Graph->AddLayer<<a class="code" href="classarmnn_1_1_logical_binary_layer.xhtml">LogicalBinaryLayer</a>>(logicalBinaryDescriptor, name);</div><div class="line"><a name="l02503"></a><span class="lineno"> 2503</span> }</div><div class="line"><a name="l02504"></a><span class="lineno"> 2504</span> </div><div class="line"><a name="l02505"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a1163a712898cd2c368ef2e4510fc36c3"> 2505</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_network_impl.xhtml#a1163a712898cd2c368ef2e4510fc36c3">NetworkImpl::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="l02506"></a><span class="lineno"> 2506</span> <span class="keyword"></span>{</div><div class="line"><a name="l02507"></a><span class="lineno"> 2507</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> layer : <a class="code" href="classarmnn_1_1_network_impl.xhtml#afe0a4f719f9752a405e71878da7012ba">GetGraph</a>())</div><div class="line"><a name="l02508"></a><span class="lineno"> 2508</span>  {</div><div class="line"><a name="l02509"></a><span class="lineno"> 2509</span>  layer->Accept(visitor);</div><div class="line"><a name="l02510"></a><span class="lineno"> 2510</span>  };</div><div class="line"><a name="l02511"></a><span class="lineno"> 2511</span> }</div><div class="line"><a name="l02512"></a><span class="lineno"> 2512</span> </div><div class="line"><a name="l02513"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_impl.xhtml#a72032c65bf8b8acf09b564b7d80078c5"> 2513</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_network_impl.xhtml#a72032c65bf8b8acf09b564b7d80078c5">NetworkImpl::ExecuteStrategy</a>(<a class="code" href="classarmnn_1_1_i_strategy.xhtml">IStrategy</a>& strategy)<span class="keyword"> const</span></div><div class="line"><a name="l02514"></a><span class="lineno"> 2514</span> <span class="keyword"></span>{</div><div class="line"><a name="l02515"></a><span class="lineno"> 2515</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> layer : <a class="code" href="classarmnn_1_1_network_impl.xhtml#afe0a4f719f9752a405e71878da7012ba">GetGraph</a>())</div><div class="line"><a name="l02516"></a><span class="lineno"> 2516</span>  {</div><div class="line"><a name="l02517"></a><span class="lineno"> 2517</span>  layer->ExecuteStrategy(strategy);</div><div class="line"><a name="l02518"></a><span class="lineno"> 2518</span>  };</div><div class="line"><a name="l02519"></a><span class="lineno"> 2519</span> }</div><div class="line"><a name="l02520"></a><span class="lineno"> 2520</span> </div><div class="line"><a name="l02521"></a><span class="lineno"><a class="line" href="classarmnn_1_1_optimized_network_impl.xhtml#afc73993a557309c43043aa0592fd7981"> 2521</a></span> <a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml#afc73993a557309c43043aa0592fd7981">OptimizedNetworkImpl::OptimizedNetworkImpl</a>(std::unique_ptr<Graph> graph)</div><div class="line"><a name="l02522"></a><span class="lineno"> 2522</span>  : m_Graph(<a class="code" href="namespacestd.xhtml">std</a>::move(graph)), m_Guid(profiling::<a class="code" href="classarmnn_1_1profiling_1_1_profiling_service.xhtml">ProfilingService</a>::GetNextGuid())</div><div class="line"><a name="l02523"></a><span class="lineno"> 2523</span> {</div><div class="line"><a name="l02524"></a><span class="lineno"> 2524</span> }</div><div class="line"><a name="l02525"></a><span class="lineno"> 2525</span> </div><div class="line"><a name="l02526"></a><span class="lineno"><a class="line" href="classarmnn_1_1_optimized_network_impl.xhtml#a9a2e9e1491ef82892e7ea2308957ff44"> 2526</a></span> <a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml#afc73993a557309c43043aa0592fd7981">OptimizedNetworkImpl::OptimizedNetworkImpl</a>(std::unique_ptr<Graph> graph, <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#a5b6893cda5b69359a4244c06054da18f">ModelOptions</a>& modelOptions)</div><div class="line"><a name="l02527"></a><span class="lineno"> 2527</span>  : m_Graph(<a class="code" href="namespacestd.xhtml">std</a>::move(graph)), m_Guid(profiling::<a class="code" href="classarmnn_1_1profiling_1_1_profiling_service.xhtml">ProfilingService</a>::GetNextGuid()), m_ModelOptions(modelOptions)</div><div class="line"><a name="l02528"></a><span class="lineno"> 2528</span> {</div><div class="line"><a name="l02529"></a><span class="lineno"> 2529</span> }</div><div class="line"><a name="l02530"></a><span class="lineno"> 2530</span> </div><div class="line"><a name="l02531"></a><span class="lineno"><a class="line" href="classarmnn_1_1_optimized_network_impl.xhtml#a06d0b70cbc134b412ff7715d9db1617b"> 2531</a></span> <a class="code" href="classarmnn_1_1_optimized_network_impl.xhtml#a06d0b70cbc134b412ff7715d9db1617b">OptimizedNetworkImpl::~OptimizedNetworkImpl</a>()</div><div class="line"><a name="l02532"></a><span class="lineno"> 2532</span> {</div><div class="line"><a name="l02533"></a><span class="lineno"> 2533</span> }</div><div class="line"><a name="l02534"></a><span class="lineno"> 2534</span> </div><div class="line"><a name="l02535"></a><span class="lineno"> 2535</span> } <span class="comment">// namespace armnn</span></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#l00067">SquashEqualSiblings.hpp:67</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#l00563">Network.cpp:563</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2387033802383edbdc95f9bbb12a707e"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2387033802383edbdc95f9bbb12a707e">armnn::Graph::begin</a></div><div class="ttdeci">Iterator begin()</div><div class="ttdoc">Returns iterator pointing to the beginning of the list. Lowercase for range-based for loops...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00162">Graph.hpp:162</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_af13795cdf49e63d8bc3cb409592cdb9d"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#af13795cdf49e63d8bc3cb409592cdb9d">armnn::INetwork::AddSubtractionLayer</a></div><div class="ttdeci">IConnectableLayer * AddSubtractionLayer(const char *name=nullptr)</div><div class="ttdoc">Adds a subtraction layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00376">Network.cpp:376</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#l00454">Descriptors.hpp:454</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="classarmnn_1_1_network_impl_xhtml_ae0cfae1ea51669892608a1a060d24fa0"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ae0cfae1ea51669892608a1a060d24fa0">armnn::NetworkImpl::AddReduceLayer</a></div><div class="ttdeci">IConnectableLayer * AddReduceLayer(const ReduceDescriptor &reduceDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01984">Network.cpp:1984</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="structarmnn_1_1_optimizer_options_xhtml_a71194277c60153a5f86539f5d39f01db"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a71194277c60153a5f86539f5d39f01db">armnn::OptimizerOptions::m_ModelOptions</a></div><div class="ttdeci">ModelOptions m_ModelOptions</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00168">INetwork.hpp:168</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_ae2f5193942457daafa733998f3e61449"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ae2f5193942457daafa733998f3e61449">armnn::NetworkImpl::AddRsqrtLayer</a></div><div class="ttdeci">IConnectableLayer * AddRsqrtLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02246">Network.cpp:2246</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_aa51350bdd4976f3dd5a4e9d00a906b2c"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#aa51350bdd4976f3dd5a4e9d00a906b2c">armnn::INetwork::AddActivationLayer</a></div><div class="ttdeci">IConnectableLayer * AddActivationLayer(const ActivationDescriptor &activationDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds an activation layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00218">Network.cpp:218</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_bilinear_descriptor_xhtml_a4022d5107338aaf5eb7abebf78a1360b"><div class="ttname"><a href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#a4022d5107338aaf5eb7abebf78a1360b">armnn::ResizeBilinearDescriptor::m_HalfPixelCenters</a></div><div class="ttdeci">bool m_HalfPixelCenters</div><div class="ttdoc">Half Pixel Centers. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00790">Descriptors.hpp:790</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_bilinear_descriptor_xhtml_ae1a4b3b6c60552509b89747cebb900a2"><div class="ttname"><a href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#ae1a4b3b6c60552509b89747cebb900a2">armnn::ResizeBilinearDescriptor::m_AlignCorners</a></div><div class="ttdeci">bool m_AlignCorners</div><div class="ttdoc">Aligned corners. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00788">Descriptors.hpp:788</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#l00046">ITensorHandleFactory.hpp:46</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="namespacearmnn_xhtml_a224df72b3d7a3bba8609bc167286e3f7"><div class="ttname"><a href="namespacearmnn.xhtml#a224df72b3d7a3bba8609bc167286e3f7">armnn::AssignBackends</a></div><div class="ttdeci">OptimizationResult AssignBackends(OptimizedNetworkImpl *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#l00869">Network.cpp:869</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#l00054">BackendRegistry.cpp:54</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#l00515">Network.cpp:515</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#l00206">Descriptors.hpp:206</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#l00062">INetwork.hpp:62</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#l00043">OptimizeInversePermutes.hpp:43</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#l00083">ITensorHandleFactory.hpp:83</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#l00201">NetworkUtils.cpp:201</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#l00506">Descriptors.hpp:506</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a72032c65bf8b8acf09b564b7d80078c5"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a72032c65bf8b8acf09b564b7d80078c5">armnn::INetwork::ExecuteStrategy</a></div><div class="ttdeci">void ExecuteStrategy(IStrategy &strategy) const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00500">Network.cpp:500</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#l00181">Layer.cpp:181</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="classarmnn_1_1_optimized_network_impl_xhtml_aff3fde909d22ed157046682e70129259"><div class="ttname"><a href="classarmnn_1_1_optimized_network_impl.xhtml#aff3fde909d22ed157046682e70129259">armnn::OptimizedNetworkImpl::PrintGraph</a></div><div class="ttdeci">virtual Status PrintGraph()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00552">Network.cpp:552</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#l00129">NetworkUtils.cpp:129</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_ad97411f1fcb2c30c212483d8c673506f"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ad97411f1fcb2c30c212483d8c673506f">armnn::NetworkImpl::AddResizeLayer</a></div><div class="ttdeci">IConnectableLayer * AddResizeLayer(const ResizeDescriptor &resizeDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02004">Network.cpp:2004</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimized_network_impl_xhtml_a06d0b70cbc134b412ff7715d9db1617b"><div class="ttname"><a href="classarmnn_1_1_optimized_network_impl.xhtml#a06d0b70cbc134b412ff7715d9db1617b">armnn::OptimizedNetworkImpl::~OptimizedNetworkImpl</a></div><div class="ttdeci">virtual ~OptimizedNetworkImpl()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02531">Network.cpp:2531</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#l01213">Descriptors.hpp:1213</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00187">Tensor.hpp:187</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="classarmnn_1_1_i_network_xhtml_a41fd7b56923d5625bac2cbfebed1a393"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a41fd7b56923d5625bac2cbfebed1a393">armnn::INetwork::AddTransposeConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddTransposeConvolution2dLayer(const TransposeConvolution2dDescriptor &descriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)</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#l00450">Network.cpp:450</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a0b426a3feffc76e66d73b5761806e899"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a0b426a3feffc76e66d73b5761806e899">armnn::NetworkImpl::AddQuantizeLayer</a></div><div class="ttdeci">IConnectableLayer * AddQuantizeLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02220">Network.cpp:2220</a></div></div> +<div class="ttc" id="_utils_8hpp_xhtml"><div class="ttname"><a href="_utils_8hpp.xhtml">Utils.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_ae3ef3b97542241d331a38613ae189f3e"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ae3ef3b97542241d331a38613ae189f3e">armnn::NetworkImpl::AddFullyConnectedLayer</a></div><div class="ttdeci">IConnectableLayer * AddFullyConnectedLayer(const FullyConnectedDescriptor &fullyConnectedDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01733">Network.cpp:1733</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="classarmnn_1_1_i_network_xhtml_a2acbae0b9e98c94b843677484775c86a"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a2acbae0b9e98c94b843677484775c86a">armnn::INetwork::AddQLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddQLstmLayer(const QLstmDescriptor &descriptor, const LstmInputParams &params, const char *name=nullptr)</div><div class="ttdoc">Add a QLstm layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00482">Network.cpp:482</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_impl_xhtml_a25563024ec66627ee83727244a53e944"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a25563024ec66627ee83727244a53e944">armnn::NetworkImpl::AddRankLayer</a></div><div class="ttdeci">IConnectableLayer * AddRankLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01979">Network.cpp:1979</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="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#l00832">Descriptors.hpp:832</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#l01239">Network.cpp:1239</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#l00045">OptimizeInversePermutes.hpp:45</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a39f1b38d89c4de186742eafcbb3b1319"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a39f1b38d89c4de186742eafcbb3b1319">armnn::NetworkImpl::AddAdditionLayer</a></div><div class="ttdeci">IConnectableLayer * AddAdditionLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01947">Network.cpp:1947</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#l00104">PermuteAndBatchToSpaceAsDepthToSpace.hpp:104</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="namespacearmnn_1_1optimizations_xhtml_a56e54a818166a2f4b2c1a7f76a3629ff"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a56e54a818166a2f4b2c1a7f76a3629ff">armnn::optimizations::FuseBatchNormIntoDepthwiseConvolution2DFloat32</a></div><div class="ttdeci">OptimizeForExclusiveConnection< DepthwiseConvolution2dLayer, BatchNormalizationLayer, FuseBatchNorm< DepthwiseConvolution2dLayer, armnn::DataType::Float32 > > FuseBatchNormIntoDepthwiseConvolution2DFloat32</div><div class="ttdef"><b>Definition:</b> <a href="_fuse_batch_norm_8hpp_source.xhtml#l00197">FuseBatchNorm.hpp:197</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a1aa567f46c30960851c02847dc7b4215"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a1aa567f46c30960851c02847dc7b4215">armnn::INetwork::AddConstantLayer</a></div><div class="ttdeci">IConnectableLayer * AddConstantLayer(const ConstTensor &input, const char *name=nullptr)</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#l00331">Network.cpp:331</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#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a58f85a122022527a525318473f93d4ef"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a58f85a122022527a525318473f93d4ef">armnn::INetwork::AddDepthwiseConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddDepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor &convolution2dDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)</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#l00115">Network.cpp:115</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#l01229">Network.cpp:1229</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#l00078">Descriptors.hpp:78</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a030e8e7c1f6980ec9b2ac06b683ee74e"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a030e8e7c1f6980ec9b2ac06b683ee74e">armnn::NetworkImpl::AddAbsLayer</a></div><div class="ttdeci">IConnectableLayer * AddAbsLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01942">Network.cpp:1942</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="classarmnn_utils_1_1_floating_point_converter_xhtml_af9e9df90cb6319b0406acf9a3bc27667"><div class="ttname"><a href="classarmnn_utils_1_1_floating_point_converter.xhtml#af9e9df90cb6319b0406acf9a3bc27667">armnnUtils::FloatingPointConverter::ConvertBFloat16ToFloat32</a></div><div class="ttdeci">static void ConvertBFloat16ToFloat32(const void *srcBFloat16Buffer, size_t numElements, float *dstFloat32Buffer)</div><div class="ttdef"><b>Definition:</b> <a href="_floating_point_converter_8cpp_source.xhtml#l00061">FloatingPointConverter.cpp:61</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#l01127">Network.cpp:1127</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_ae913b4351b7027f37eb5657dd7867733"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ae913b4351b7027f37eb5657dd7867733">armnn::NetworkImpl::AddPooling2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddPooling2dLayer(const Pooling2dDescriptor &pooling2dDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01884">Network.cpp:1884</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a55e83c091dbe02c2ca6d3b33a902ae02"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a55e83c091dbe02c2ca6d3b33a902ae02">armnn::NetworkImpl::NetworkImpl</a></div><div class="ttdeci">NetworkImpl(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01667">Network.cpp:1667</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a5210b3df77e7a51ab369b577de821aa2"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a5210b3df77e7a51ab369b577de821aa2">armnn::INetwork::AddStackLayer</a></div><div class="ttdeci">IConnectableLayer * AddStackLayer(const StackDescriptor &descriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a stack layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00464">Network.cpp:464</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#l00782">Descriptors.hpp:782</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#l00786">Descriptors.hpp:786</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a5b6893cda5b69359a4244c06054da18f"><div class="ttname"><a href="namespacearmnn.xhtml#a5b6893cda5b69359a4244c06054da18f">armnn::ModelOptions</a></div><div class="ttdeci">std::vector< BackendOptions > ModelOptions</div><div class="ttdef"><b>Definition:</b> <a href="_backend_options_8hpp_source.xhtml#l00017">BackendOptions.hpp:17</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a1163a712898cd2c368ef2e4510fc36c3"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a1163a712898cd2c368ef2e4510fc36c3">armnn::INetwork::Accept</a></div><div class="ttdeci">void Accept(ILayerVisitor &visitor) const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00495">Network.cpp:495</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="classarmnn_1_1_network_impl_xhtml_a0f19808bdada45222e72edf7671a275a"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a0f19808bdada45222e72edf7671a275a">armnn::NetworkImpl::AddMergeLayer</a></div><div class="ttdeci">IConnectableLayer * AddMergeLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02263">Network.cpp:2263</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_ae2f5193942457daafa733998f3e61449"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ae2f5193942457daafa733998f3e61449">armnn::INetwork::AddRsqrtLayer</a></div><div class="ttdeci">IConnectableLayer * AddRsqrtLayer(const char *name=nullptr)</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#l00423">Network.cpp:423</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#l00408">Descriptors.hpp:408</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_i_network_xhtml_a0b426a3feffc76e66d73b5761806e899"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a0b426a3feffc76e66d73b5761806e899">armnn::INetwork::AddQuantizeLayer</a></div><div class="ttdeci">IConnectableLayer * AddQuantizeLayer(const char *name=nullptr)</div><div class="ttdoc">Add a quantize layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00397">Network.cpp:397</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="classarmnn_1_1_i_network_xhtml_a4bfd8dee1a0315b651e977c672c0847c"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a4bfd8dee1a0315b651e977c672c0847c">armnn::INetwork::AddMinimumLayer</a></div><div class="ttdeci">IConnectableLayer * AddMinimumLayer(const char *name=nullptr)</div><div class="ttdoc">Add a Minimum layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00408">Network.cpp:408</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a40067b05f30a3ab65568c826df7a8ea7"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a40067b05f30a3ab65568c826df7a8ea7">armnn::NetworkImpl::AddQuantizedLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddQuantizedLstmLayer(const QuantizedLstmInputParams &params, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02319">Network.cpp:2319</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_aaff51346dadec2c1430abf007fed4cc9"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#aaff51346dadec2c1430abf007fed4cc9">armnn::INetwork::AddL2NormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddL2NormalizationLayer(const L2NormalizationDescriptor &desc, const char *name=nullptr)</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#l00319">Network.cpp:319</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#l01254">Descriptors.hpp:1254</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_impl_xhtml_a1aa567f46c30960851c02847dc7b4215"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a1aa567f46c30960851c02847dc7b4215">armnn::NetworkImpl::AddConstantLayer</a></div><div class="ttdeci">IConnectableLayer * AddConstantLayer(const ConstTensor &input, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02027">Network.cpp:2027</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a095a9b700dc857edc23c5d3bf088919f"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a095a9b700dc857edc23c5d3bf088919f">armnn::NetworkImpl::AddElementwiseUnaryLayer</a></div><div class="ttdeci">IConnectableLayer * AddElementwiseUnaryLayer(const ElementwiseUnaryDescriptor &elementwiseUnaryDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01699">Network.cpp:1699</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a0f19808bdada45222e72edf7671a275a"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a0f19808bdada45222e72edf7671a275a">armnn::INetwork::AddMergeLayer</a></div><div class="ttdeci">IConnectableLayer * AddMergeLayer(const char *name=nullptr)</div><div class="ttdoc">Adds a merge layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00246">Network.cpp:246</a></div></div> +<div class="ttc" id="classarmnn_1_1profiling_1_1_profiling_guid_xhtml"><div class="ttname"><a href="classarmnn_1_1profiling_1_1_profiling_guid.xhtml">armnn::profiling::ProfilingGuid</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00291">Types.hpp:291</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a11f49d84f0cfd8df65f4d5206cd43b6d"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a11f49d84f0cfd8df65f4d5206cd43b6d">armnn::INetwork::AddPermuteLayer</a></div><div class="ttdeci">IConnectableLayer * AddPermuteLayer(const PermuteDescriptor &permuteDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a permute layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00200">Network.cpp:200</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="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#l00821">Descriptors.hpp:821</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_aff3fde909d22ed157046682e70129259"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#aff3fde909d22ed157046682e70129259">armnn::INetwork::PrintGraph</a></div><div class="ttdeci">Status PrintGraph()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00045">Network.cpp:45</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a6c5376053e1f875776d7bc36fd0b7d45"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a6c5376053e1f875776d7bc36fd0b7d45">armnn::NetworkImpl::AddNormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddNormalizationLayer(const NormalizationDescriptor &normalizationDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01902">Network.cpp:1902</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_aff3fde909d22ed157046682e70129259"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#aff3fde909d22ed157046682e70129259">armnn::NetworkImpl::PrintGraph</a></div><div class="ttdeci">Status PrintGraph()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01676">Network.cpp:1676</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a8de6b047fcaff95df48dca683e1f3aa4"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a8de6b047fcaff95df48dca683e1f3aa4">armnn::INetwork::AddSliceLayer</a></div><div class="ttdeci">IConnectableLayer * AddSliceLayer(const SliceDescriptor &sliceDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a slice layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00230">Network.cpp:230</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="namespacearmnn_1_1optimizations_xhtml_ab40bb51feca46649eb9d00522bfe51f6"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#ab40bb51feca46649eb9d00522bfe51f6">armnn::optimizations::FuseBatchNormIntoDepthwiseConvolution2DFloat16</a></div><div class="ttdeci">OptimizeForExclusiveConnection< DepthwiseConvolution2dLayer, BatchNormalizationLayer, FuseBatchNorm< DepthwiseConvolution2dLayer, armnn::DataType::Float16 > > FuseBatchNormIntoDepthwiseConvolution2DFloat16</div><div class="ttdef"><b>Definition:</b> <a href="_fuse_batch_norm_8hpp_source.xhtml#l00202">FuseBatchNorm.hpp:202</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_i_network_xhtml_a435ea88480b8645026dd45fd692663a1"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a435ea88480b8645026dd45fd692663a1">armnn::INetwork::AddFloorLayer</a></div><div class="ttdeci">IConnectableLayer * AddFloorLayer(const char *name=nullptr)</div><div class="ttdoc">Adds a floor layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00355">Network.cpp:355</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_ae913b4351b7027f37eb5657dd7867733"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ae913b4351b7027f37eb5657dd7867733">armnn::INetwork::AddPooling2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddPooling2dLayer(const Pooling2dDescriptor &pooling2dDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a pooling layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00212">Network.cpp:212</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_impl_xhtml_ad4726f9b7dd11db250d2a494a8a39494"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ad4726f9b7dd11db250d2a494a8a39494">armnn::NetworkImpl::AddMeanLayer</a></div><div class="ttdeci">IConnectableLayer * AddMeanLayer(const MeanDescriptor &meanDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02210">Network.cpp:2210</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#l00015">ReshapeLayer.hpp:15</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="classarmnn_1_1_network_impl_xhtml_a72032c65bf8b8acf09b564b7d80078c5"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a72032c65bf8b8acf09b564b7d80078c5">armnn::NetworkImpl::ExecuteStrategy</a></div><div class="ttdeci">void ExecuteStrategy(IStrategy &strategy) const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02513">Network.cpp:2513</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_1_1optimizations_xhtml_a8a81178ddcebb93ec0c35b6e6284273c"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a8a81178ddcebb93ec0c35b6e6284273c">armnn::optimizations::FuseBatchNormIntoConvolution2DFloat16</a></div><div class="ttdeci">OptimizeForExclusiveConnection< Convolution2dLayer, BatchNormalizationLayer, FuseBatchNorm< Convolution2dLayer, armnn::DataType::Float16 > > FuseBatchNormIntoConvolution2DFloat16</div><div class="ttdef"><b>Definition:</b> <a href="_fuse_batch_norm_8hpp_source.xhtml#l00192">FuseBatchNorm.hpp:192</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="namespacearmnn_1_1optimizations_xhtml_aa52c06792e18dc13030e82476f706f9e"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#aa52c06792e18dc13030e82476f706f9e">armnn::optimizations::FuseBatchNormIntoConvolution2DFloat32</a></div><div class="ttdeci">OptimizeForExclusiveConnection< Convolution2dLayer, BatchNormalizationLayer, FuseBatchNorm< Convolution2dLayer, armnn::DataType::Float32 > > FuseBatchNormIntoConvolution2DFloat32</div><div class="ttdef"><b>Definition:</b> <a href="_fuse_batch_norm_8hpp_source.xhtml#l00187">FuseBatchNorm.hpp:187</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#l00202">Logging.hpp:202</a></div></div> +<div class="ttc" id="structarmnn_1_1_q_lstm_basic_parameters_xhtml_a5a0d8af26a6aad1e5be521ea7dc550eb"><div class="ttname"><a href="structarmnn_1_1_q_lstm_basic_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">armnn::QLstmBasicParameters::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 [num_units, inputSize] (QSymmS8)...</div><div class="ttdef"><b>Definition:</b> <a href="_q_lstm_layer_8hpp_source.xhtml#l00017">QLstmLayer.hpp:17</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a4bfd8dee1a0315b651e977c672c0847c"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a4bfd8dee1a0315b651e977c672c0847c">armnn::NetworkImpl::AddMinimumLayer</a></div><div class="ttdeci">IConnectableLayer * AddMinimumLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01931">Network.cpp:1931</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_afc94c35c0bbe852a60046bf2e756b2e0"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#afc94c35c0bbe852a60046bf2e756b2e0">armnn::INetwork::AddFillLayer</a></div><div class="ttdeci">IConnectableLayer * AddFillLayer(const FillDescriptor &fillDescriptor, const char *name=nullptr)</div><div class="ttdoc">Add an Fill layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00168">Network.cpp:168</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#l00178">INetwork.hpp:178</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="classarmnn_1_1_network_impl_xhtml_a19bad0cc50526ca9f4f84a688812cdf5"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a19bad0cc50526ca9f4f84a688812cdf5">armnn::NetworkImpl::AddSpaceToDepthLayer</a></div><div class="ttdeci">IConnectableLayer * AddSpaceToDepthLayer(const SpaceToDepthDescriptor &spaceToDepthDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02048">Network.cpp:2048</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="classarmnn_1_1_convert_bf16_to_fp32_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_convert_bf16_to_fp32_layer.xhtml">armnn::ConvertBf16ToFp32Layer</a></div><div class="ttdoc">This layer converts data type BFloat16 to Float32. </div><div class="ttdef"><b>Definition:</b> <a href="_convert_bf16_to_fp32_layer_8hpp_source.xhtml#l00014">ConvertBf16ToFp32Layer.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e">armnn::LayerType::FullyConnected</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a1759754ccb88ecc9af44f3aae6e244ee"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">armnn::LstmInputParams::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00046">LstmParams.hpp:46</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a33d586a0d9bbb1f12ac7a3ba8d03e21e"><div class="ttname"><a href="namespacearmnn.xhtml#a33d586a0d9bbb1f12ac7a3ba8d03e21e">armnn::ConvertBf16ToFp32Weight</a></div><div class="ttdeci">LayerT * ConvertBf16ToFp32Weight(Layer *l)</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_xhtml_a4de71c3661093e5c4ae7775114f43413"><div class="ttname"><a href="namespacearmnn.xhtml#a4de71c3661093e5c4ae7775114f43413">armnn::NetworkOptions</a></div><div class="ttdeci">std::vector< BackendOptions > NetworkOptions</div><div class="ttdef"><b>Definition:</b> <a href="_backend_options_8hpp_source.xhtml#l00015">BackendOptions.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml_a11f463726addcc1d2845266997d79e9c"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a11f463726addcc1d2845266997d79e9c">armnn::OptimizerOptions::m_ReduceFp32ToBf16</a></div><div class="ttdeci">bool m_ReduceFp32ToBf16</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00159">INetwork.hpp:159</a></div></div> +<div class="ttc" id="structarmnn_1_1_logical_binary_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_logical_binary_descriptor.xhtml">armnn::LogicalBinaryDescriptor</a></div><div class="ttdoc">A LogicalBinaryDescriptor for the LogicalBinaryLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01284">Descriptors.hpp:1284</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a178a72bbf254eff34a807a5ca27cb61f"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a178a72bbf254eff34a807a5ca27cb61f">armnn::INetwork::AddConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddConvolution2dLayer(const Convolution2dDescriptor &convolution2dDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)</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#l00077">Network.cpp:77</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#l00070">SquashEqualSiblings.hpp:70</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimized_network_impl_xhtml_a49800ad35ea869aa5569519760d3b339"><div class="ttname"><a href="classarmnn_1_1_optimized_network_impl.xhtml#a49800ad35ea869aa5569519760d3b339">armnn::OptimizedNetworkImpl::GetGraph</a></div><div class="ttdeci">Graph & GetGraph()</div><div class="ttdef"><b>Definition:</b> <a href="_optimized_network_impl_8hpp_source.xhtml#l00021">OptimizedNetworkImpl.hpp:21</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a83b33973ca12078166b2436b313627b9"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a83b33973ca12078166b2436b313627b9">armnn::INetwork::AddLogSoftmaxLayer</a></div><div class="ttdeci">IConnectableLayer * AddLogSoftmaxLayer(const LogSoftmaxDescriptor &logSoftmaxDescriptor, const char *name=nullptr)</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#l00325">Network.cpp:325</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_af760179196d57e2ddbc64b989fb72586"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#af760179196d57e2ddbc64b989fb72586">armnn::INetwork::~INetwork</a></div><div class="ttdeci">~INetwork()</div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_ad97411f1fcb2c30c212483d8c673506f"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ad97411f1fcb2c30c212483d8c673506f">armnn::INetwork::AddResizeLayer</a></div><div class="ttdeci">IConnectableLayer * AddResizeLayer(const ResizeDescriptor &resizeDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a resize layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00301">Network.cpp:301</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_aa51350bdd4976f3dd5a4e9d00a906b2c"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#aa51350bdd4976f3dd5a4e9d00a906b2c">armnn::NetworkImpl::AddActivationLayer</a></div><div class="ttdeci">IConnectableLayer * AddActivationLayer(const ActivationDescriptor &activationDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01890">Network.cpp:1890</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#l00174">SubgraphView.cpp:174</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#l00021">BackendSettings.hpp:21</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#l00077">MoveTransposeUp.hpp:77</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="classarmnn_1_1_i_network_xhtml_a9a9bcc00ae3d96343c93b437d6f77088"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a9a9bcc00ae3d96343c93b437d6f77088">armnn::INetwork::AddBatchToSpaceNdLayer</a></div><div class="ttdeci">IConnectableLayer * AddBatchToSpaceNdLayer(const BatchToSpaceNdDescriptor &batchToSpaceNdDescriptor, const char *name=nullptr)</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#l00206">Network.cpp:206</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#l00587">Network.cpp:587</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) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div> +<div class="ttc" id="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="classarmnn_1_1_i_network_xhtml_a0aeb4e528cf6ba4b7caca14a94fbcafe"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a0aeb4e528cf6ba4b7caca14a94fbcafe">armnn::INetwork::AddDivisionLayer</a></div><div class="ttdeci">IConnectableLayer * AddDivisionLayer(const char *name=nullptr)</div><div class="ttdoc">Adds a division layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00371">Network.cpp:371</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#l00270">Layer.hpp:270</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#l00046">BackendSettings.hpp:46</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_reduce_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_reduce_layer.xhtml">armnn::ReduceLayer</a></div><div class="ttdoc">This layer represents a reduction operation. </div><div class="ttdef"><b>Definition:</b> <a href="_reduce_layer_8hpp_source.xhtml#l00013">ReduceLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a58f85a122022527a525318473f93d4ef"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a58f85a122022527a525318473f93d4ef">armnn::NetworkImpl::AddDepthwiseConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddDepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor &convolution2dDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01840">Network.cpp:1840</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a83b33973ca12078166b2436b313627b9"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a83b33973ca12078166b2436b313627b9">armnn::NetworkImpl::AddLogSoftmaxLayer</a></div><div class="ttdeci">IConnectableLayer * AddLogSoftmaxLayer(const LogSoftmaxDescriptor &logSoftmaxDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02021">Network.cpp:2021</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#l00884">Descriptors.hpp:884</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#l00015">PermuteLayer.hpp:15</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="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#l00314">Layer.hpp:314</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_i_network_xhtml_ae3ef3b97542241d331a38613ae189f3e"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ae3ef3b97542241d331a38613ae189f3e">armnn::INetwork::AddFullyConnectedLayer</a></div><div class="ttdeci">IConnectableLayer * AddFullyConnectedLayer(const FullyConnectedDescriptor &fullyConnectedDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)</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#l00175">Network.cpp:175</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#l00673">Descriptors.hpp:673</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="classarmnn_1_1_optimized_network_impl_xhtml_a26794f014974a6f963a8925de07bffeb"><div class="ttname"><a href="classarmnn_1_1_optimized_network_impl.xhtml#a26794f014974a6f963a8925de07bffeb">armnn::OptimizedNetworkImpl::SerializeToDot</a></div><div class="ttdeci">virtual Status SerializeToDot(std::ostream &stream) const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00558">Network.cpp:558</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#l00061">OptimizeConsecutiveReshapes.hpp:61</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_ad4726f9b7dd11db250d2a494a8a39494"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ad4726f9b7dd11db250d2a494a8a39494">armnn::INetwork::AddMeanLayer</a></div><div class="ttdeci">IConnectableLayer * AddMeanLayer(const MeanDescriptor &meanDescriptor, const char *name=nullptr)</div><div class="ttdoc">Add a Mean layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00386">Network.cpp:386</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml">armnn::NetworkImpl</a></div><div class="ttdoc">Private implementation of INetwork. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00031">Network.hpp:31</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#l00210">Types.hpp:210</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_i_network_xhtml_aa6c1c42ea44777302e87ce0fad5ac510"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#aa6c1c42ea44777302e87ce0fad5ac510">armnn::INetwork::AddInputLayer</a></div><div class="ttdeci">IConnectableLayer * AddInputLayer(LayerBindingId id, const char *name=nullptr)</div><div class="ttdoc">Adds an input layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00050">Network.cpp:50</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#l00180">TypesUtils.hpp:180</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_ac5c93cad39a690af862d49ffaec0d3c0"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ac5c93cad39a690af862d49ffaec0d3c0">armnn::INetwork::AddStridedSliceLayer</a></div><div class="ttdeci">IConnectableLayer * AddStridedSliceLayer(const StridedSliceDescriptor &stridedSliceDescriptor, const char *name=nullptr)</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#l00402">Network.cpp:402</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#l00794">Descriptors.hpp:794</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#l01024">Descriptors.hpp:1024</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#l00161">IBackendInternal.cpp:161</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a19bad0cc50526ca9f4f84a688812cdf5"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a19bad0cc50526ca9f4f84a688812cdf5">armnn::INetwork::AddSpaceToDepthLayer</a></div><div class="ttdeci">IConnectableLayer * AddSpaceToDepthLayer(const SpaceToDepthDescriptor &spaceToDepthDescriptor, const char *name=nullptr)</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#l00349">Network.cpp:349</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="_polymorphic_downcast_8hpp_xhtml"><div class="ttname"><a href="_polymorphic_downcast_8hpp.xhtml">PolymorphicDowncast.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a30528a3bd85a0dba158bd14e252bd68a"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a30528a3bd85a0dba158bd14e252bd68a">armnn::INetwork::AddSoftmaxLayer</a></div><div class="ttdeci">IConnectableLayer * AddSoftmaxLayer(const SoftmaxDescriptor &softmaxDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a softmax layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00234">Network.cpp:234</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#l00153">INetwork.hpp:153</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#l00306">Network.hpp:306</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="classarmnn_1_1_network_impl_xhtml_a34aa5f1a405a6886f79c97d53f9f65fd"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a34aa5f1a405a6886f79c97d53f9f65fd">armnn::NetworkImpl::AddMergerLayer</a></div><div class="ttdeci">IConnectableLayer * AddMergerLayer(const MergerDescriptor &mergerDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01936">Network.cpp:1936</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_strategy_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_strategy.xhtml">armnn::IStrategy</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_strategy_8hpp_source.xhtml#l00013">IStrategy.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_optimized_network_xhtml_ab986223ec7e4f04929cb47c74a27aa93"><div class="ttname"><a href="classarmnn_1_1_i_optimized_network.xhtml#ab986223ec7e4f04929cb47c74a27aa93">armnn::IOptimizedNetwork::GetGuid</a></div><div class="ttdeci">profiling::ProfilingGuid GetGuid() const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00547">Network.cpp:547</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a435ea88480b8645026dd45fd692663a1"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a435ea88480b8645026dd45fd692663a1">armnn::NetworkImpl::AddFloorLayer</a></div><div class="ttdeci">IConnectableLayer * AddFloorLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02054">Network.cpp:2054</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#l00975">Descriptors.hpp:975</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#l00156">INetwork.hpp:156</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_abb59f6ba9988dae88e0f48e68d87fc32"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#abb59f6ba9988dae88e0f48e68d87fc32">armnn::NetworkImpl::AddMultiplicationLayer</a></div><div class="ttdeci">IConnectableLayer * AddMultiplicationLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01952">Network.cpp:1952</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#l00102">PermuteAndBatchToSpaceAsDepthToSpace.hpp:102</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a2acbae0b9e98c94b843677484775c86a"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a2acbae0b9e98c94b843677484775c86a">armnn::NetworkImpl::AddQLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddQLstmLayer(const QLstmDescriptor &descriptor, const LstmInputParams &params, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02357">Network.cpp:2357</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#l00077">MovePermuteUp.hpp:77</a></div></div> +<div class="ttc" id="classarmnn_1_1_logical_binary_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_logical_binary_layer.xhtml">armnn::LogicalBinaryLayer</a></div><div class="ttdoc">This layer represents a Logical Binary operation. </div><div class="ttdef"><b>Definition:</b> <a href="_logical_binary_layer_8hpp_source.xhtml#l00014">LogicalBinaryLayer.hpp:14</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#l00046">ConstantLayer.hpp:46</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_impl_xhtml_ac5c93cad39a690af862d49ffaec0d3c0"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ac5c93cad39a690af862d49ffaec0d3c0">armnn::NetworkImpl::AddStridedSliceLayer</a></div><div class="ttdeci">IConnectableLayer * AddStridedSliceLayer(const StridedSliceDescriptor &stridedSliceDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02230">Network.cpp:2230</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_i_network_xhtml_a4353fa80ece13e3b1664881c27f5a67c"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a4353fa80ece13e3b1664881c27f5a67c">armnn::INetwork::pNetworkImpl</a></div><div class="ttdeci">std::unique_ptr< NetworkImpl > pNetworkImpl</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00693">INetwork.hpp:693</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_i_optimized_network_xhtml_af730a6ec3deb072dc2687089f3f77f9e"><div class="ttname"><a href="classarmnn_1_1_i_optimized_network.xhtml#af730a6ec3deb072dc2687089f3f77f9e">armnn::IOptimizedNetwork::IOptimizedNetwork</a></div><div class="ttdeci">IOptimizedNetwork(std::unique_ptr< Graph > graph)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00521">Network.cpp:521</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_acc9f9b91636c0714d96a3cba92c624f9"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#acc9f9b91636c0714d96a3cba92c624f9">armnn::INetwork::AddResizeBilinearLayer</a></div><div class="ttdeci">IConnectableLayer * AddResizeBilinearLayer(const ResizeBilinearDescriptor &resizeDesc, const char *name=nullptr)</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#l00287">Network.cpp:287</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_optimized_network_xhtml_a22df7404d1196068ad18d0286f9b9425"><div class="ttname"><a href="classarmnn_1_1_i_optimized_network.xhtml#a22df7404d1196068ad18d0286f9b9425">armnn::IOptimizedNetwork::Optimize</a></div><div class="ttdeci">friend IOptimizedNetworkPtr Optimize(const INetwork &inNetwork, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options, Optional< std::vector< std::string > &> messages)</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</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_i_tensor_handle_factory_xhtml_a73fbbe9df988c8cabddea04a8dcb9323"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a73fbbe9df988c8cabddea04a8dcb9323">armnn::ITensorHandleFactory::GetCapabilities</a></div><div class="ttdeci">virtual std::vector< Capability > GetCapabilities(const IConnectableLayer *layer, const IConnectableLayer *connectedLayer, CapabilityClass capabilityClass)</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00088">ITensorHandleFactory.hpp:88</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_aa6c1c42ea44777302e87ce0fad5ac510"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#aa6c1c42ea44777302e87ce0fad5ac510">armnn::NetworkImpl::AddInputLayer</a></div><div class="ttdeci">IConnectableLayer * AddInputLayer(LayerBindingId id, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01682">Network.cpp:1682</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_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a6512859957de2cf2a5fe4dccb07bd9da"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a6512859957de2cf2a5fe4dccb07bd9da">armnn::LayerType::ConvertFp32ToBf16</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#l00155">ConvertConstants.hpp:155</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#l00077">TransposeAsReshape.hpp:77</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#l00911">Descriptors.hpp:911</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="classarmnn_1_1_i_network_xhtml_a0a2fdd4f442952c97a8f24de6700473a"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a0a2fdd4f442952c97a8f24de6700473a">armnn::INetwork::AddLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddLstmLayer(const LstmDescriptor &descriptor, const LstmInputParams &params, const char *name=nullptr)</div><div class="ttdoc">Add a Lstm layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00364">Network.cpp:364</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a41fd7b56923d5625bac2cbfebed1a393"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a41fd7b56923d5625bac2cbfebed1a393">armnn::NetworkImpl::AddTransposeConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddTransposeConvolution2dLayer(const TransposeConvolution2dDescriptor &descriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02278">Network.cpp:2278</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00015">Assert.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a25563024ec66627ee83727244a53e944"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a25563024ec66627ee83727244a53e944">armnn::INetwork::AddRankLayer</a></div><div class="ttdeci">IConnectableLayer * AddRankLayer(const char *name=nullptr)</div><div class="ttdoc">Adds a rank layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00282">Network.cpp:282</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="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="namespacearmnn_xhtml_a9f31d956861d8277fa5f8fb877dbbb6c"><div class="ttname"><a href="namespacearmnn.xhtml#a9f31d956861d8277fa5f8fb877dbbb6c">armnn::ApplyBackendOptimizations</a></div><div class="ttdeci">OptimizationResult ApplyBackendOptimizations(OptimizedNetworkImpl *optNetObjPtr, BackendSettings &backendSettings, BackendsMap &backends, const ModelOptions &modelOptions, Optional< std::vector< std::string > &> errMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01028">Network.cpp:1028</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="classarmnn_1_1_network_impl_xhtml_a6d614a503a34ea3712b388aa4340ddbe"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a6d614a503a34ea3712b388aa4340ddbe">armnn::NetworkImpl::AddPreluLayer</a></div><div class="ttdeci">IConnectableLayer * AddPreluLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02273">Network.cpp:2273</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#l00607">Descriptors.hpp:607</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#l00469">Tensor.cpp:469</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#l00056">Descriptors.hpp:56</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a047ca888c43bd7fb5702853bf72410d0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">armnn::TensorInfo::GetQuantizationScale</a></div><div class="ttdeci">float GetQuantizationScale() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00452">Tensor.cpp:452</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_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#l00194">Tensor.hpp:194</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#l00163">Descriptors.hpp:163</a></div></div> +<div class="ttc" id="structarmnn_1_1_reduce_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_reduce_descriptor.xhtml">armnn::ReduceDescriptor</a></div><div class="ttdoc">A ReduceDescriptor for the REDUCE operators. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01304">Descriptors.hpp:1304</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#l00699">INetwork.hpp:699</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_ac1134a94265293ea7347180260f787d2"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ac1134a94265293ea7347180260f787d2">armnn::NetworkImpl::AddDetectionPostProcessLayer</a></div><div class="ttdeci">IConnectableLayer * AddDetectionPostProcessLayer(const DetectionPostProcessDescriptor &descriptor, const ConstTensor &anchors, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01868">Network.cpp:1868</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#l00304">Network.hpp:304</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#l00389">Descriptors.hpp:389</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#l00402">Descriptors.hpp:402</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#l00314">Tensor.hpp:314</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_i_network_xhtml_abd61d3e7ab67551c75bc219bbc4baeb5"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#abd61d3e7ab67551c75bc219bbc4baeb5">armnn::INetwork::AddInstanceNormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddInstanceNormalizationLayer(const InstanceNormalizationDescriptor &desc, const char *name=nullptr)</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#l00313">Network.cpp:313</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#l00220">Layer.hpp:220</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</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#l00816">Descriptors.hpp:816</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_adf69fa0e439ddb632462b42253d67b6a"><div class="ttname"><a href="namespacearmnn.xhtml#adf69fa0e439ddb632462b42253d67b6a">armnn::InsertConvertBf16ToFp32LayersBefore</a></div><div class="ttdeci">std::vector< ConvertBf16ToFp32Layer * > InsertConvertBf16ToFp32LayersBefore(Graph &graph, Layer &layer, bool expectCorrectInputType)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.xhtml#l00051">NetworkUtils.cpp:51</a></div></div> +<div class="ttc" id="structarmnn_1_1_gather_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_gather_descriptor.xhtml">armnn::GatherDescriptor</a></div><div class="ttdoc">A GatherDescriptor for the GatherLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00742">Descriptors.hpp:742</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">armnn::LayerType::Convolution2d</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_i_optimized_network_xhtml_a374d52340ec8dc02a819acc20fb5aa92"><div class="ttname"><a href="classarmnn_1_1_i_optimized_network.xhtml#a374d52340ec8dc02a819acc20fb5aa92">armnn::IOptimizedNetwork::pOptimizedNetworkImpl</a></div><div class="ttdeci">std::unique_ptr< OptimizedNetworkImpl > pOptimizedNetworkImpl</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00725">INetwork.hpp:725</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a0aeb4e528cf6ba4b7caca14a94fbcafe"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a0aeb4e528cf6ba4b7caca14a94fbcafe">armnn::NetworkImpl::AddDivisionLayer</a></div><div class="ttdeci">IConnectableLayer * AddDivisionLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02200">Network.cpp:2200</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_i_network_xhtml_af5790069aa11fd1c5bb2e17cecb06528"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#af5790069aa11fd1c5bb2e17cecb06528">armnn::INetwork::AddOutputLayer</a></div><div class="ttdeci">IConnectableLayer * AddOutputLayer(LayerBindingId id, const char *name=nullptr)</div><div class="ttdoc">Adds an output layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00359">Network.cpp:359</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#l00174">INetwork.hpp:174</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a4022d5107338aaf5eb7abebf78a1360b"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#a4022d5107338aaf5eb7abebf78a1360b">armnn::ResizeDescriptor::m_HalfPixelCenters</a></div><div class="ttdeci">bool m_HalfPixelCenters</div><div class="ttdoc">Half Pixel Centers. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00827">Descriptors.hpp:827</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_adc8c1c505bca8233fe238b3b7fb80200"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#adc8c1c505bca8233fe238b3b7fb80200">armnn::NetworkImpl::AddArgMinMaxLayer</a></div><div class="ttdeci">IConnectableLayer * AddArgMinMaxLayer(const ArgMinMaxDescriptor &desc, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01896">Network.cpp:1896</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_af5790069aa11fd1c5bb2e17cecb06528"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#af5790069aa11fd1c5bb2e17cecb06528">armnn::NetworkImpl::AddOutputLayer</a></div><div class="ttdeci">IConnectableLayer * AddOutputLayer(LayerBindingId id, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01957">Network.cpp:1957</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_network_impl_xhtml_a357aca04172ed22fa32e5a69122b0fec"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a357aca04172ed22fa32e5a69122b0fec">armnn::NetworkImpl::AddDequantizeLayer</a></div><div class="ttdeci">IConnectableLayer * AddDequantizeLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02225">Network.cpp:2225</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00464">Tensor.cpp:464</a></div></div> +<div class="ttc" id="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="classarmnn_1_1_network_impl_xhtml_aea1059833739d3dccebb3a03ec35a1e6"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#aea1059833739d3dccebb3a03ec35a1e6">armnn::NetworkImpl::AddConcatLayer</a></div><div class="ttdeci">IConnectableLayer * AddConcatLayer(const ConcatDescriptor &concatDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01758">Network.cpp:1758</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div> +<div class="ttc" id="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#l01054">Descriptors.hpp:1054</a></div></div> +<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml">armnn::QLstmDescriptor</a></div><div class="ttdoc">A QLstmDescriptor for the QLstmLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01153">Descriptors.hpp:1153</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#l00067">BackendSettings.hpp:67</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#l00200">Types.hpp:200</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a26e69cda5fe9642f9198c24ae5fdf9bc"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a26e69cda5fe9642f9198c24ae5fdf9bc">armnn::NetworkImpl::AddSwitchLayer</a></div><div class="ttdeci">IConnectableLayer * AddSwitchLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02268">Network.cpp:2268</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#l01246">WorkloadFactory.cpp:1246</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a7ba52238d75f06ff59a0d2ba613acefe"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a7ba52238d75f06ff59a0d2ba613acefe">armnn::INetwork::AddEqualLayer</a></div><div class="ttdeci">IConnectableLayer * AddEqualLayer(const char *name=nullptr)</div><div class="ttdoc">Add a Equal layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00418">Network.cpp:418</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#l00110">INetwork.hpp:110</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a030e8e7c1f6980ec9b2ac06b683ee74e"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a030e8e7c1f6980ec9b2ac06b683ee74e">armnn::INetwork::AddAbsLayer</a></div><div class="ttdeci">IConnectableLayer * AddAbsLayer(const char *name=nullptr)</div><div class="ttdoc">Add absolute layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00257">Network.cpp:257</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_optimized_network_xhtml_a437cc59f5247f213adf34e84696f60da"><div class="ttname"><a href="classarmnn_1_1_i_optimized_network.xhtml#a437cc59f5247f213adf34e84696f60da">armnn::IOptimizedNetwork::~IOptimizedNetwork</a></div><div class="ttdeci">~IOptimizedNetwork()</div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_af13795cdf49e63d8bc3cb409592cdb9d"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#af13795cdf49e63d8bc3cb409592cdb9d">armnn::NetworkImpl::AddSubtractionLayer</a></div><div class="ttdeci">IConnectableLayer * AddSubtractionLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02205">Network.cpp:2205</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_acc9f9b91636c0714d96a3cba92c624f9"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#acc9f9b91636c0714d96a3cba92c624f9">armnn::NetworkImpl::AddResizeBilinearLayer</a></div><div class="ttdeci">IConnectableLayer * AddResizeBilinearLayer(const ResizeBilinearDescriptor &resizeDesc, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01990">Network.cpp:1990</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#l00025">Descriptors.hpp:25</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a1ff7534e1254dfb3ef8288194cca7ce3"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a1ff7534e1254dfb3ef8288194cca7ce3">armnn::NetworkImpl::AddLogicalBinaryLayer</a></div><div class="ttdeci">IConnectableLayer * AddLogicalBinaryLayer(const LogicalBinaryDescriptor &logicalBinaryDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02499">Network.cpp:2499</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#l00290">Network.hpp:290</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8ae358a041b4adc33577e8b4c07b8d23"><div class="ttname"><a href="namespacearmnn.xhtml#a8ae358a041b4adc33577e8b4c07b8d23">armnn::InsertConvertFp32ToBf16LayersAfter</a></div><div class="ttdeci">std::vector< ConvertFp32ToBf16Layer * > InsertConvertFp32ToBf16LayersAfter(Graph &graph, Layer &layer)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.xhtml#l00168">NetworkUtils.cpp:168</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#l00269">Layer.hpp:269</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#l00784">Descriptors.hpp:784</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="classarmnn_1_1_network_impl_xhtml_a1163a712898cd2c368ef2e4510fc36c3"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a1163a712898cd2c368ef2e4510fc36c3">armnn::NetworkImpl::Accept</a></div><div class="ttdeci">void Accept(ILayerVisitor &visitor) const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02505">Network.cpp:2505</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a8f798e19187ac7ae6ae6153ee64ab645"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a8f798e19187ac7ae6ae6153ee64ab645">armnn::INetwork::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)</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#l00272">Network.cpp:272</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a2d936beb0fcf3c5d22ff332f0812b05e"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a2d936beb0fcf3c5d22ff332f0812b05e">armnn::INetwork::INetwork</a></div><div class="ttdeci">INetwork(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00041">Network.cpp:41</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#l00818">Descriptors.hpp:818</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#l01001">Descriptors.hpp:1001</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a72b9d30e9d555bb5c35460b62faedf0d"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a72b9d30e9d555bb5c35460b62faedf0d">armnn::INetwork::AddSpaceToBatchNdLayer</a></div><div class="ttdeci">IConnectableLayer * AddSpaceToBatchNdLayer(const SpaceToBatchNdDescriptor &spaceToBatchNdDescriptor, const char *name=nullptr)</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#l00343">Network.cpp:343</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_optimized_network_impl_xhtml"><div class="ttname"><a href="classarmnn_1_1_optimized_network_impl.xhtml">armnn::OptimizedNetworkImpl</a></div><div class="ttdef"><b>Definition:</b> <a href="_optimized_network_impl_8hpp_source.xhtml#l00009">OptimizedNetworkImpl.hpp:9</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#l00085">ITensorHandleFactory.hpp:85</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_network_impl_xhtml_a74894d085e78ff80f45fc09dd2381f08"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a74894d085e78ff80f45fc09dd2381f08">armnn::NetworkImpl::AddStandInLayer</a></div><div class="ttdeci">IConnectableLayer * AddStandInLayer(const StandInDescriptor &descriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02313">Network.cpp:2313</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="_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#l00015">TransposeLayer.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a11f49d84f0cfd8df65f4d5206cd43b6d"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a11f49d84f0cfd8df65f4d5206cd43b6d">armnn::NetworkImpl::AddPermuteLayer</a></div><div class="ttdeci">IConnectableLayer * AddPermuteLayer(const PermuteDescriptor &permuteDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01878">Network.cpp:1878</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml_a05c1bba6ba3ecc1339d4c4c10c0d8890"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a05c1bba6ba3ecc1339d4c4c10c0d8890">armnn::OptimizerOptions::m_ImportEnabled</a></div><div class="ttdeci">bool m_ImportEnabled</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00165">INetwork.hpp:165</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#l00293">Network.hpp:293</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_ad443897d51b291c83d81d809af07f4e0"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ad443897d51b291c83d81d809af07f4e0">armnn::NetworkImpl::~NetworkImpl</a></div><div class="ttdeci">~NetworkImpl()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01672">Network.cpp:1672</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_i_network_xhtml_ac7dca3e9f2ab2f2c64b42fc59a67188a"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ac7dca3e9f2ab2f2c64b42fc59a67188a">armnn::INetwork::AddComparisonLayer</a></div><div class="ttdeci">IConnectableLayer * AddComparisonLayer(const ComparisonDescriptor &comparisonDescriptor, const char *name=nullptr)</div><div class="ttdoc">Add a Comparison layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00063">Network.cpp:63</a></div></div> +<div class="ttc" id="classarmnn_1_1_q_lstm_layer_xhtml_aada2b9060461ecf785d483eee0dc071a"><div class="ttname"><a href="classarmnn_1_1_q_lstm_layer.xhtml#aada2b9060461ecf785d483eee0dc071a">armnn::QLstmLayer::m_BasicParameters</a></div><div class="ttdeci">QLstmBasicParameters m_BasicParameters</div><div class="ttdef"><b>Definition:</b> <a href="_q_lstm_layer_8hpp_source.xhtml#l00083">QLstmLayer.hpp:83</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#l00432">Graph.cpp:432</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_aaff51346dadec2c1430abf007fed4cc9"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#aaff51346dadec2c1430abf007fed4cc9">armnn::NetworkImpl::AddL2NormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddL2NormalizationLayer(const L2NormalizationDescriptor &desc, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02015">Network.cpp:2015</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_adc8c1c505bca8233fe238b3b7fb80200"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#adc8c1c505bca8233fe238b3b7fb80200">armnn::INetwork::AddArgMinMaxLayer</a></div><div class="ttdeci">IConnectableLayer * AddArgMinMaxLayer(const ArgMinMaxDescriptor &desc, const char *name=nullptr)</div><div class="ttdoc">Adds an ArgMinMax layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00056">Network.cpp:56</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#l00602">Network.cpp:602</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="classarmnn_1_1_i_network_xhtml_a6f6d81d8a4f1f85f3616e8306760061c"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a6f6d81d8a4f1f85f3616e8306760061c">armnn::INetwork::AddSplitterLayer</a></div><div class="ttdeci">IConnectableLayer * AddSplitterLayer(const ViewsDescriptor &splitterDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a splitter layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00240">Network.cpp:240</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#l00171">Layer.cpp:171</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#l00852">Descriptors.hpp:852</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_i_optimized_network_xhtml_aff3fde909d22ed157046682e70129259"><div class="ttname"><a href="classarmnn_1_1_i_optimized_network.xhtml#aff3fde909d22ed157046682e70129259">armnn::IOptimizedNetwork::PrintGraph</a></div><div class="ttdeci">Status PrintGraph()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00537">Network.cpp:537</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#l00066">PermuteAsReshape.hpp:66</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#l00305">Network.hpp:305</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_xhtml_a10c50bc964cc8cc559eebcd7df5a8af3aa47abd1077ef632a38ada05b6edbf389"><div class="ttname"><a href="namespacearmnn.xhtml#a10c50bc964cc8cc559eebcd7df5a8af3aa47abd1077ef632a38ada05b6edbf389">armnn::CapabilityClass::PaddingRequired</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#l00069">SquashEqualSiblings.hpp:69</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#l00099">ITensorHandleFactory.hpp:99</a></div></div> +<div class="ttc" id="classarmnn_1_1_q_lstm_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_q_lstm_layer.xhtml">armnn::QLstmLayer</a></div><div class="ttdoc">This layer represents a QLstm operation. </div><div class="ttdef"><b>Definition:</b> <a href="_q_lstm_layer_8hpp_source.xhtml#l00079">QLstmLayer.hpp:79</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a39f1b38d89c4de186742eafcbb3b1319"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a39f1b38d89c4de186742eafcbb3b1319">armnn::INetwork::AddAdditionLayer</a></div><div class="ttdeci">IConnectableLayer * AddAdditionLayer(const char *name=nullptr)</div><div class="ttdoc">Adds an addition layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00262">Network.cpp:262</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="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#l00020">BackendSettings.hpp:20</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="_assert_8hpp_xhtml"><div class="ttname"><a href="_assert_8hpp.xhtml">Assert.hpp</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#l00049">ProfilingService.hpp:49</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_ab067ba4ee9416d93abb8a52f3dc8feba"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ab067ba4ee9416d93abb8a52f3dc8feba">armnn::NetworkImpl::AddTransposeLayer</a></div><div class="ttdeci">IConnectableLayer * AddTransposeLayer(const TransposeDescriptor &transposeDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02300">Network.cpp:2300</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="classarmnn_1_1_scoped_cpu_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">armnn::ScopedCpuTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.xhtml#l00106">CpuTensorHandle.hpp:106</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a8a3380be13fba749fc4208214b049347"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a8a3380be13fba749fc4208214b049347">armnn::INetwork::AddReshapeLayer</a></div><div class="ttdeci">IConnectableLayer * AddReshapeLayer(const ReshapeDescriptor &reshapeDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a reshape layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00337">Network.cpp:337</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="classarmnn_1_1_i_network_xhtml_a6e2df484ecc65bc82712590b96e04df4"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a6e2df484ecc65bc82712590b96e04df4">armnn::INetwork::AddPadLayer</a></div><div class="ttdeci">IConnectableLayer * AddPadLayer(const PadDescriptor &padDescriptor, const char *name=nullptr)</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#l00391">Network.cpp:391</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#l00154">ConvertConstants.hpp:154</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_ae1a4b3b6c60552509b89747cebb900a2"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#ae1a4b3b6c60552509b89747cebb900a2">armnn::ResizeDescriptor::m_AlignCorners</a></div><div class="ttdeci">bool m_AlignCorners</div><div class="ttdoc">Aligned corners. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00825">Descriptors.hpp:825</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#l00098">Descriptors.hpp:98</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#l00255">SubgraphViewSelector.cpp:255</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a8a3380be13fba749fc4208214b049347"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a8a3380be13fba749fc4208214b049347">armnn::NetworkImpl::AddReshapeLayer</a></div><div class="ttdeci">IConnectableLayer * AddReshapeLayer(const ReshapeDescriptor &reshapeDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02036">Network.cpp:2036</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="classarmnn_1_1_network_impl_xhtml_a57590d7777211673d2052f702f0b07a1"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a57590d7777211673d2052f702f0b07a1">armnn::NetworkImpl::AddMaximumLayer</a></div><div class="ttdeci">IConnectableLayer * AddMaximumLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01926">Network.cpp:1926</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00529">Graph.cpp:529</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#l01009">Network.cpp:1009</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#l01147">Network.cpp:1147</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="classarmnn_1_1_network_impl_xhtml_a446181daeb60b49cbcfd9f907f974ec1"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a446181daeb60b49cbcfd9f907f974ec1">armnn::NetworkImpl::AddStackLayer</a></div><div class="ttdeci">IConnectableLayer * AddStackLayer(const StackDescriptor &stackDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02306">Network.cpp:2306</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_network_impl_xhtml_a30528a3bd85a0dba158bd14e252bd68a"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a30528a3bd85a0dba158bd14e252bd68a">armnn::NetworkImpl::AddSoftmaxLayer</a></div><div class="ttdeci">IConnectableLayer * AddSoftmaxLayer(const SoftmaxDescriptor &softmaxDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01914">Network.cpp:1914</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_network_impl_xhtml_a9fcd8cc35c8ae7d092705e7c4c2a7c69"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a9fcd8cc35c8ae7d092705e7c4c2a7c69">armnn::NetworkImpl::AddGreaterLayer</a></div><div class="ttdeci">IConnectableLayer * AddGreaterLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02236">Network.cpp:2236</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#l00041">ITensorHandleFactory.hpp:41</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a6c5376053e1f875776d7bc36fd0b7d45"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a6c5376053e1f875776d7bc36fd0b7d45">armnn::INetwork::AddNormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddNormalizationLayer(const NormalizationDescriptor &normalizationDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a normalization layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00224">Network.cpp:224</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#l00022">BackendSettings.hpp:22</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a7ba52238d75f06ff59a0d2ba613acefe"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a7ba52238d75f06ff59a0d2ba613acefe">armnn::NetworkImpl::AddEqualLayer</a></div><div class="ttdeci">IConnectableLayer * AddEqualLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02241">Network.cpp:2241</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_afc94c35c0bbe852a60046bf2e756b2e0"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#afc94c35c0bbe852a60046bf2e756b2e0">armnn::NetworkImpl::AddFillLayer</a></div><div class="ttdeci">IConnectableLayer * AddFillLayer(const FillDescriptor &fillDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01705">Network.cpp:1705</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="classarmnn_1_1_graph_xhtml_ab45dae688fc5d8983727abffa4389003"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#ab45dae688fc5d8983727abffa4389003">armnn::Graph::end</a></div><div class="ttdeci">Iterator end()</div><div class="ttdoc">Returns iterator pointing to the end of the list. Lowercase for range-based for loops. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00164">Graph.hpp:164</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_impl_xhtml_afe0a4f719f9752a405e71878da7012ba"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#afe0a4f719f9752a405e71878da7012ba">armnn::NetworkImpl::GetGraph</a></div><div class="ttdeci">const Graph & GetGraph() const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00037">Network.hpp:37</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#l00661">Network.cpp:661</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_optimized_network_impl_xhtml_afc73993a557309c43043aa0592fd7981"><div class="ttname"><a href="classarmnn_1_1_optimized_network_impl.xhtml#afc73993a557309c43043aa0592fd7981">armnn::OptimizedNetworkImpl::OptimizedNetworkImpl</a></div><div class="ttdeci">OptimizedNetworkImpl(std::unique_ptr< Graph > graph)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02521">Network.cpp:2521</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a435d3651482bbfcc11263b4e4e0c900f"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">armnn::LstmInputParams::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00044">LstmParams.hpp:44</a></div></div> +<div class="ttc" id="structarmnn_1_1_mean_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml">armnn::MeanDescriptor</a></div><div class="ttdoc">A MeanDescriptor for the MeanLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00951">Descriptors.hpp:951</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#l00044">ITensorHandleFactory.hpp:44</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_optimized_network_xhtml_a26794f014974a6f963a8925de07bffeb"><div class="ttname"><a href="classarmnn_1_1_i_optimized_network.xhtml#a26794f014974a6f963a8925de07bffeb">armnn::IOptimizedNetwork::SerializeToDot</a></div><div class="ttdeci">Status SerializeToDot(std::ostream &stream) const</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00542">Network.cpp:542</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a72b9d30e9d555bb5c35460b62faedf0d"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a72b9d30e9d555bb5c35460b62faedf0d">armnn::NetworkImpl::AddSpaceToBatchNdLayer</a></div><div class="ttdeci">IConnectableLayer * AddSpaceToBatchNdLayer(const SpaceToBatchNdDescriptor &spaceToBatchNdDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02042">Network.cpp:2042</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a40067b05f30a3ab65568c826df7a8ea7"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a40067b05f30a3ab65568c826df7a8ea7">armnn::INetwork::AddQuantizedLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddQuantizedLstmLayer(const QuantizedLstmInputParams &params, const char *name=nullptr)</div><div class="ttdoc">Add a QuantizedLstm layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00476">Network.cpp:476</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_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_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#l00318">Layer.hpp:318</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="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#l00087">ConvertFp32NetworkToFp16.hpp:87</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#l01263">Descriptors.hpp:1263</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#l01076">Descriptors.hpp:1076</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_impl_xhtml_ac7dca3e9f2ab2f2c64b42fc59a67188a"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ac7dca3e9f2ab2f2c64b42fc59a67188a">armnn::NetworkImpl::AddComparisonLayer</a></div><div class="ttdeci">IConnectableLayer * AddComparisonLayer(const ComparisonDescriptor &comparisonDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01693">Network.cpp:1693</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a86541d11fcad5246a78cbc21d637a504"><div class="ttname"><a href="namespacearmnn.xhtml#a86541d11fcad5246a78cbc21d637a504">armnn::SelectTensorHandleStrategy</a></div><div class="ttdeci">OptimizationResult SelectTensorHandleStrategy(Graph &optGraph, BackendsMap &backends, TensorHandleFactoryRegistry &registry, bool importEnabled, Optional< std::vector< std::string > &> errMessages)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01434">Network.cpp:1434</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#l00169">SubgraphView.cpp:169</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#l00575">Network.cpp:575</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="classarmnn_1_1_convert_fp32_to_bf16_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">armnn::ConvertFp32ToBf16Layer</a></div><div class="ttdoc">This layer converts data type Float32 to BFloat16. </div><div class="ttdef"><b>Definition:</b> <a href="_convert_fp32_to_bf16_layer_8hpp_source.xhtml#l00014">ConvertFp32ToBf16Layer.hpp:14</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#l00480">Tensor.cpp:480</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a26e69cda5fe9642f9198c24ae5fdf9bc"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a26e69cda5fe9642f9198c24ae5fdf9bc">armnn::INetwork::AddSwitchLayer</a></div><div class="ttdeci">IConnectableLayer * AddSwitchLayer(const char *name=nullptr)</div><div class="ttdoc">Adds a switch layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00440">Network.cpp:440</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_ac1134a94265293ea7347180260f787d2"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ac1134a94265293ea7347180260f787d2">armnn::INetwork::AddDetectionPostProcessLayer</a></div><div class="ttdeci">IConnectableLayer * AddDetectionPostProcessLayer(const DetectionPostProcessDescriptor &descriptor, const ConstTensor &anchors, const char *name=nullptr)</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#l00152">Network.cpp:152</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a230005513ac5eee1f3944b1960b6f2ed"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a230005513ac5eee1f3944b1960b6f2ed">armnn::INetwork::CreateRaw</a></div><div class="ttdeci">static INetwork * CreateRaw(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00505">Network.cpp:505</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a34aa5f1a405a6886f79c97d53f9f65fd"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a34aa5f1a405a6886f79c97d53f9f65fd">armnn::INetwork::AddMergerLayer</a></div><div class="ttdeci">IConnectableLayer * AddMergerLayer(const MergerDescriptor &mergerDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a concat layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00251">Network.cpp:251</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_abb59f6ba9988dae88e0f48e68d87fc32"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#abb59f6ba9988dae88e0f48e68d87fc32">armnn::INetwork::AddMultiplicationLayer</a></div><div class="ttdeci">IConnectableLayer * AddMultiplicationLayer(const char *name=nullptr)</div><div class="ttdoc">Adds a multiplication layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00267">Network.cpp:267</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a74894d085e78ff80f45fc09dd2381f08"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a74894d085e78ff80f45fc09dd2381f08">armnn::INetwork::AddStandInLayer</a></div><div class="ttdeci">IConnectableLayer * AddStandInLayer(const StandInDescriptor &descriptor, const char *name=nullptr)</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#l00470">Network.cpp:470</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#l00173">INetwork.hpp:173</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a8f798e19187ac7ae6ae6153ee64ab645"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a8f798e19187ac7ae6ae6153ee64ab645">armnn::NetworkImpl::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)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01962">Network.cpp:1962</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_ae0cfae1ea51669892608a1a060d24fa0"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ae0cfae1ea51669892608a1a060d24fa0">armnn::INetwork::AddReduceLayer</a></div><div class="ttdeci">IConnectableLayer * AddReduceLayer(const ReduceDescriptor &reduceDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a reduce layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00307">Network.cpp:307</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a095a9b700dc857edc23c5d3bf088919f"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a095a9b700dc857edc23c5d3bf088919f">armnn::INetwork::AddElementwiseUnaryLayer</a></div><div class="ttdeci">IConnectableLayer * AddElementwiseUnaryLayer(const ElementwiseUnaryDescriptor &elementwiseUnaryDescriptor, const char *name=nullptr)</div><div class="ttdoc">Add an ElementwiseUnary layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00161">Network.cpp:161</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a4fc55afb4885278ad1510b2c4307af76"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a4fc55afb4885278ad1510b2c4307af76">armnn::optimizations::AddBroadcastReshapeLayer</a></div><div class="ttdeci">OptimizeForType< Layer, AddBroadcastReshapeLayerImpl > AddBroadcastReshapeLayer</div><div class="ttdef"><b>Definition:</b> <a href="_add_broadcast_reshape_layer_8hpp_source.xhtml#l00082">AddBroadcastReshapeLayer.hpp:82</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a31f19249d1491464736b08b967be68b4"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a31f19249d1491464736b08b967be68b4">armnn::NetworkImpl::AddGatherLayer</a></div><div class="ttdeci">IConnectableLayer * AddGatherLayer(const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02251">Network.cpp:2251</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a357aca04172ed22fa32e5a69122b0fec"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a357aca04172ed22fa32e5a69122b0fec">armnn::INetwork::AddDequantizeLayer</a></div><div class="ttdeci">IConnectableLayer * AddDequantizeLayer(const char *name=nullptr)</div><div class="ttdoc">Adds a Dequantize layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00146">Network.cpp:146</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#l00329">Descriptors.hpp:329</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="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#l00018">BackendSettings.hpp:18</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#l00567">Descriptors.hpp:567</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a6d614a503a34ea3712b388aa4340ddbe"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a6d614a503a34ea3712b388aa4340ddbe">armnn::INetwork::AddPreluLayer</a></div><div class="ttdeci">IConnectableLayer * AddPreluLayer(const char *name=nullptr)</div><div class="ttdoc">Adds a PReLU layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00445">Network.cpp:445</a></div></div> +<div class="ttc" id="classarmnn_1_1_rank_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_rank_layer.xhtml">armnn::RankLayer</a></div><div class="ttdef"><b>Definition:</b> <a href="_rank_layer_8hpp_source.xhtml#l00013">RankLayer.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a9fcd8cc35c8ae7d092705e7c4c2a7c69"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a9fcd8cc35c8ae7d092705e7c4c2a7c69">armnn::INetwork::AddGreaterLayer</a></div><div class="ttdeci">IConnectableLayer * AddGreaterLayer(const char *name=nullptr)</div><div class="ttdoc">Add a Greater layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00413">Network.cpp:413</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_af1853466264ac187607c96b501a74e2b"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#af1853466264ac187607c96b501a74e2b">armnn::NetworkImpl::AddDepthToSpaceLayer</a></div><div class="ttdeci">IConnectableLayer * AddDepthToSpaceLayer(const DepthToSpaceDescriptor &depthToSpaceDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01834">Network.cpp:1834</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a57590d7777211673d2052f702f0b07a1"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a57590d7777211673d2052f702f0b07a1">armnn::INetwork::AddMaximumLayer</a></div><div class="ttdeci">IConnectableLayer * AddMaximumLayer(const char *name=nullptr)</div><div class="ttdoc">Add a Maximum layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00381">Network.cpp:381</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#l00823">Descriptors.hpp:823</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#l00511">Descriptors.hpp:511</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#l00645">Descriptors.hpp:645</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_impl_xhtml_a178a72bbf254eff34a807a5ca27cb61f"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a178a72bbf254eff34a807a5ca27cb61f">armnn::NetworkImpl::AddConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddConvolution2dLayer(const Convolution2dDescriptor &convolution2dDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01786">Network.cpp:1786</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a6f6d81d8a4f1f85f3616e8306760061c"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a6f6d81d8a4f1f85f3616e8306760061c">armnn::NetworkImpl::AddSplitterLayer</a></div><div class="ttdeci">IConnectableLayer * AddSplitterLayer(const ViewsDescriptor &splitterDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01920">Network.cpp:1920</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a9a9bcc00ae3d96343c93b437d6f77088"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a9a9bcc00ae3d96343c93b437d6f77088">armnn::NetworkImpl::AddBatchToSpaceNdLayer</a></div><div class="ttdeci">IConnectableLayer * AddBatchToSpaceNdLayer(const BatchToSpaceNdDescriptor &batchToSpaceNdDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01687">Network.cpp:1687</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#l00762">Descriptors.hpp:762</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a0a2fdd4f442952c97a8f24de6700473a"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a0a2fdd4f442952c97a8f24de6700473a">armnn::NetworkImpl::AddLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddLstmLayer(const LstmDescriptor &descriptor, const LstmInputParams &params, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02059">Network.cpp:2059</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_impl_xhtml_a6e2df484ecc65bc82712590b96e04df4"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a6e2df484ecc65bc82712590b96e04df4">armnn::NetworkImpl::AddPadLayer</a></div><div class="ttdeci">IConnectableLayer * AddPadLayer(const PadDescriptor &padDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02215">Network.cpp:2215</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_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00510">Network.cpp:510</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a7dfc9717e76257867ad0a9239f210df0"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a7dfc9717e76257867ad0a9239f210df0">armnn::INetwork::AddLogicalBinaryLayer</a></div><div class="ttdeci">IConnectableLayer * AddLogicalBinaryLayer(const LogicalBinaryDescriptor &descriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a Logical Binary layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00489">Network.cpp:489</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a31f19249d1491464736b08b967be68b4"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a31f19249d1491464736b08b967be68b4">armnn::INetwork::AddGatherLayer</a></div><div class="ttdeci">IConnectableLayer * AddGatherLayer(const char *name=nullptr)</div><div class="ttdoc">Add Gather layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00428">Network.cpp:428</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a738d3243c1dc564304d78908c6112e4f"><div class="ttname"><a href="namespacearmnn.xhtml#a738d3243c1dc564304d78908c6112e4f">armnn::CalculateEdgeStrategy</a></div><div class="ttdeci">EdgeStrategy CalculateEdgeStrategy(BackendsMap &backends, ITensorHandleFactory::FactoryId srcFactoryId, const Layer &layer, const Layer &connectedLayer, TensorHandleFactoryRegistry &registry, bool importEnabled)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01348">Network.cpp:1348</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#l00532">Network.cpp:532</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_aea1059833739d3dccebb3a03ec35a1e6"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#aea1059833739d3dccebb3a03ec35a1e6">armnn::INetwork::AddConcatLayer</a></div><div class="ttdeci">IConnectableLayer * AddConcatLayer(const ConcatDescriptor &concatDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a concatenation layer to the network. </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_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#l00086">ITensorHandleFactory.hpp:86</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="namespacearmnn_1_1optimizations_xhtml_aeb70f8fcf5180bdd5c94be7bb2f9d176"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#aeb70f8fcf5180bdd5c94be7bb2f9d176">armnn::optimizations::Fp32NetworkToBf16Converter</a></div><div class="ttdeci">OptimizeForType< Layer, ConvertFp32NetworkToBf16Impl > Fp32NetworkToBf16Converter</div><div class="ttdef"><b>Definition:</b> <a href="_convert_fp32_network_to_bf16_8hpp_source.xhtml#l00075">ConvertFp32NetworkToBf16.hpp:75</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#l00139">Descriptors.hpp:139</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="namespacearmnn_xhtml_addb6b14dd1b632263ffe77430259a7c4"><div class="ttname"><a href="namespacearmnn.xhtml#addb6b14dd1b632263ffe77430259a7c4">armnn::GetLayerTypeAsCString</a></div><div class="ttdeci">const char * 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_graph_xhtml_ad1bbee7bf5f93b792675886f57d3ebe0"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#ad1bbee7bf5f93b792675886f57d3ebe0">armnn::Graph::AddCompatibilityLayers</a></div><div class="ttdeci">void AddCompatibilityLayers(std::map< BackendId, std::unique_ptr< class IBackendInternal >> &backends, TensorHandleFactoryRegistry &registry)</div><div class="ttdoc">Modifies the graph in-place, removing edges connecting layers using different compute devices...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00300">Graph.cpp:300</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#l00061">BackendSettings.hpp:61</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#l00045">ITensorHandleFactory.hpp:45</a></div></div> +<div class="ttc" id="classarmnn_1_1_fill_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_fill_layer.xhtml">armnn::FillLayer</a></div><div class="ttdoc">This layer represents a fill operation. </div><div class="ttdef"><b>Definition:</b> <a href="_fill_layer_8hpp_source.xhtml#l00013">FillLayer.hpp:13</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#l00460">Descriptors.hpp:460</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#l00210">Layer.hpp:210</a></div></div> +<div class="ttc" id="structarmnn_1_1_fill_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fill_descriptor.xhtml">armnn::FillDescriptor</a></div><div class="ttdoc">A FillDescriptor for the FillLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00723">Descriptors.hpp:723</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#l00626">Descriptors.hpp:626</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a2ba4c46787312a2467153f40c542851a"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a2ba4c46787312a2467153f40c542851a">armnn::LayerType::ConvertBf16ToFp32</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_ab067ba4ee9416d93abb8a52f3dc8feba"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#ab067ba4ee9416d93abb8a52f3dc8feba">armnn::INetwork::AddTransposeLayer</a></div><div class="ttdeci">IConnectableLayer * AddTransposeLayer(const TransposeDescriptor &transposeDescriptor, const char *name=nullptr)</div><div class="ttdoc">Adds a transpose layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00458">Network.cpp:458</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00192">Tensor.hpp:192</a></div></div> +<div class="ttc" id="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#l00310">Network.hpp:310</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#l00118">Descriptors.hpp:118</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a8de6b047fcaff95df48dca683e1f3aa4"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a8de6b047fcaff95df48dca683e1f3aa4">armnn::NetworkImpl::AddSliceLayer</a></div><div class="ttdeci">IConnectableLayer * AddSliceLayer(const SliceDescriptor &sliceDescriptor, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01909">Network.cpp:1909</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_af1853466264ac187607c96b501a74e2b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#af1853466264ac187607c96b501a74e2b">armnn::INetwork::AddDepthToSpaceLayer</a></div><div class="ttdeci">IConnectableLayer * AddDepthToSpaceLayer(const DepthToSpaceDescriptor &depthToSpaceDescriptor, const char *name=nullptr)</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#l00108">Network.cpp:108</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="ttdoc">When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00419">Types.hpp:419</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="classarmnn_1_1_network_impl_xhtml_abd61d3e7ab67551c75bc219bbc4baeb5"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#abd61d3e7ab67551c75bc219bbc4baeb5">armnn::NetworkImpl::AddInstanceNormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddInstanceNormalizationLayer(const InstanceNormalizationDescriptor &desc, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02009">Network.cpp:2009</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 Thu Feb 25 2021 17:27:29 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> |