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diff --git a/20.02/_workload_factory_8cpp_source.xhtml b/20.02/_workload_factory_8cpp_source.xhtml new file mode 100644 index 0000000000..134323a15e --- /dev/null +++ b/20.02/_workload_factory_8cpp_source.xhtml @@ -0,0 +1,361 @@ +<!-- 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/backends/backendsCommon/WorkloadFactory.cpp Source File</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">20.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_workload_factory_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">WorkloadFactory.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_workload_factory_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include <<a class="code" href="_layer_8hpp.xhtml">Layer.hpp</a>></span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include <<a class="code" href="_layers_fwd_8hpp.xhtml">LayersFwd.hpp</a>></span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_types_8hpp.xhtml">armnn/Types.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_layer_support_8hpp.xhtml">armnn/LayerSupport.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_i_layer_support_8hpp.xhtml">armnn/ILayerSupport.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_registry_8hpp.xhtml">armnn/BackendRegistry.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_workload_factory_8hpp.xhtml">backendsCommon/WorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</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="l00016"></a><span class="lineno"> 16</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="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <<a class="code" href="_workload_factory_8hpp.xhtml">backendsCommon/WorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include <<a class="code" href="_workload_test_utils_8hpp.xhtml">backendsCommon/test/WorkloadTestUtils.hpp</a>></span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include <boost/cast.hpp></span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="preprocessor">#include <boost/iterator/transform_iterator.hpp></span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> </div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include <cstring></span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include <sstream></span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> {</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> {</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="keyword">const</span> TensorInfo OverrideDataType(<span class="keyword">const</span> TensorInfo& info, Optional<DataType> type)</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> {</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keywordflow">if</span> (!type)</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  {</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordflow">return</span> info;</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  }</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordflow">return</span> TensorInfo(info.GetShape(), type.value(), info.GetQuantizationScale(), info.GetQuantizationOffset());</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> }</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> } <span class="comment">// anonymous namespace</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_workload_factory.xhtml#a74dc9ec1a223eab8b072368b2dacee87"> 45</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a74dc9ec1a223eab8b072368b2dacee87">IWorkloadFactory::IsLayerSupported</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_backend_id.xhtml">BackendId</a>& backendId,</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>& connectableLayer,</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<DataType></a> dataType,</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  std::string& outReasonIfUnsupported)</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> {</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<std::string&></a> reason = outReasonIfUnsupported;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordtype">bool</span> result;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>& layer = *(boost::polymorphic_downcast<const Layer*>(&connectableLayer));</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>  <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="l00055"></a><span class="lineno"> 55</span>  <span class="keywordflow">if</span> (!backendRegistry.IsBackendRegistered(backendId))</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  {</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  std::stringstream ss;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  ss << connectableLayer.<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#afcc1c3a20bd2860e0ddd21674389246f">GetName</a>() << <span class="stringliteral">" is not supported on "</span> << backendId</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  << <span class="stringliteral">" because this backend is not registered."</span>;</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>  outReasonIfUnsupported = ss.str();</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">auto</span> backendFactory = backendRegistry.GetFactory(backendId);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keyword">auto</span> backendObject = backendFactory();</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">auto</span> layerSupportObject = backendObject->GetLayerSupport();</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>  <span class="keywordflow">switch</span>(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>())</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  {</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aa9a62e70841c4d06dd16306a85700d36">LayerType::Activation</a>:</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="keyword">auto</span> cLayer = boost::polymorphic_downcast<const ActivationLayer*>(&layer);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  result = layerSupportObject->IsActivationSupported(</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  OverrideDataType(input, dataType),</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  reason);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  }</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">LayerType::Addition</a>:</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</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_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  result = layerSupportObject->IsAdditionSupported(</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  OverrideDataType(input0, dataType),</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  OverrideDataType(input1, dataType),</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  reason);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordflow">break</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"> 95</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a2139684546b147c106b329f41547640c">LayerType::ArgMinMax</a>:</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  {</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const ArgMinMaxLayer*>(&layer);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">ArgMinMaxDescriptor</a>& descriptor = cLayer->GetParameters();</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  result = layerSupportObject->IsArgMinMaxSupported(</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  OverrideDataType(input, dataType),</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  OverrideDataType(output, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>),</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  descriptor,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  reason);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  }</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e">LayerType::BatchNormalization</a>:</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  {</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const BatchNormalizationLayer*>(&layer);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& mean = cLayer->m_Mean->GetTensorInfo();</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& var = cLayer->m_Variance->GetTensorInfo();</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& beta = cLayer->m_Beta->GetTensorInfo();</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_tensor_info.xhtml">TensorInfo</a>& gamma = cLayer->m_Gamma->GetTensorInfo();</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  result = layerSupportObject->IsBatchNormalizationSupported(</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  OverrideDataType(input, dataType),</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  OverrideDataType(mean, dataType),</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  OverrideDataType(var, dataType),</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  OverrideDataType(beta, dataType),</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  OverrideDataType(gamma, dataType),</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  reason);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  }</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a6ee06c6045d0c5b6565a247955ef0fc2">LayerType::BatchToSpaceNd</a>:</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  {</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const BatchToSpaceNdLayer*>(&layer);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  result = layerSupportObject->IsBatchToSpaceNdSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  reason);</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keywordflow">break</span>;</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">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4af6c0e3a1c3cfabd32ae8d3ae741fcf0a">LayerType::Comparison</a>:</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  {</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const ComparisonLayer*>(&layer);</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  result = layerSupportObject->IsComparisonSupported(OverrideDataType(input0, dataType),</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  OverrideDataType(input1, dataType),</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  OverrideDataType(output, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">DataType::Boolean</a>),</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  reason);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  }</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>:</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  {</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  result = layerSupportObject->IsConstantSupported(OverrideDataType(output, dataType), reason);</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  }</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a912a4b4d73726c282e3f79aa2c390d6c">LayerType::ConvertFp16ToFp32</a>:</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  result = layerSupportObject->IsConvertFp16ToFp32Supported(input, output, reason);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  }</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">LayerType::ConvertFp32ToFp16</a>:</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  result = layerSupportObject->IsConvertFp32ToFp16Supported(input, output, reason);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  }</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">LayerType::Convolution2d</a>:</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  {</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const Convolution2dLayer*>(&layer);</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> input = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>(),</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  dataType);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> output = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>(), dataType);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  BOOST_ASSERT(cLayer->m_Weight.get() != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a>& descriptor = cLayer->GetParameters();</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="comment">// Construct optional biases object based on the value of m_BiasEnabled</span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<TensorInfo></a> biases;</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  {</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  biases =</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  OverrideDataType(cLayer->m_Bias->GetTensorInfo(), <a class="code" href="namespacearmnn.xhtml#a83c4a275acf59f62b8387f389d0929d5">GetBiasTypeFromWeightsType</a>(dataType));</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  }</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> </div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  result = layerSupportObject->IsConvolution2dSupported(</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  input,</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  output,</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  descriptor,</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  OverrideDataType(cLayer->m_Weight->GetTensorInfo(), dataType),</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  biases,</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  reason);</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  }</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a93a3ba385cad27c4774e5fe64c025d3daa603905470e2a5b8c13e96b579ef0dba">LayerType::Debug</a>:</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  {</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</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>  result = layerSupportObject->IsDebugSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  reason);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  }</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a731729ad1b2c0eb9399b62c770b3482d">LayerType::DepthToSpace</a>:</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  {</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const DepthToSpaceLayer*>(&layer);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> </div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</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>  result = layerSupportObject->IsDepthToSpaceSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  reason);</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  }</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4af97adbfc88b7012a0243215b1076e7e7">LayerType::DepthwiseConvolution2d</a>:</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  {</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const DepthwiseConvolution2dLayer*>(&layer);</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>(),</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  dataType);</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>(), dataType);</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  BOOST_ASSERT(cLayer->m_Weight.get() != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> </div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a>& descriptor = cLayer->GetParameters();</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="comment">// Construct optional biases object based on the value of m_BiasEnabled</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<TensorInfo></a> biases;</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  {</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  biases =</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  OverrideDataType(cLayer->m_Bias->GetTensorInfo(), <a class="code" href="namespacearmnn.xhtml#a83c4a275acf59f62b8387f389d0929d5">GetBiasTypeFromWeightsType</a>(dataType));</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  }</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> </div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  result = layerSupportObject->IsDepthwiseConvolutionSupported(</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  input,</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  output,</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  descriptor,</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  OverrideDataType(cLayer->m_Weight->GetTensorInfo(), dataType),</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  biases,</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  reason);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  }</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a9bc35e069257a508e14ed82965a8661d">LayerType::Dequantize</a>:</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</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>  result = layerSupportObject->IsDequantizeSupported(input,</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  reason);</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  }</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a">LayerType::DetectionPostProcess</a>:</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>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const DetectionPostProcessLayer*>(&layer);</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ada422a73ac4e68bcb1b1b1f0b44028d9">boxEncodings</a> = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a0348e6bb67ace72535bd105219bb6237">scores</a> = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a> = cLayer->m_Anchors->GetTensorInfo();</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& detectionBoxes = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& detectionClasses = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</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_tensor_info.xhtml">TensorInfo</a>& detectionScores = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</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_tensor_info.xhtml">TensorInfo</a>& numDetections = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(3).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> </div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">DetectionPostProcessDescriptor</a>& descriptor = cLayer->GetParameters();</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  result = layerSupportObject->IsDetectionPostProcessSupported(boxEncodings,</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  scores,</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  anchors,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  detectionBoxes,</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  detectionClasses,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  detectionScores,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  numDetections,</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  descriptor,</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  reason);</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  }</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4abcd30d7ea97ad20c2cddc0f47e6b70c7">LayerType::ElementwiseUnary</a>:</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  {</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const ElementwiseUnaryLayer*>(&layer);</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> </div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  result = layerSupportObject->IsElementwiseUnarySupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  reason);</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordflow">break</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"> 301</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a3489c7b05e180496cb2ce8ac73887f48">LayerType::FakeQuantization</a>:</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  {</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const FakeQuantizationLayer*>(&layer);</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  result = layerSupportObject->IsFakeQuantizationSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  reason);</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keywordflow">break</span>;</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">case</span> <a class="code" href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">LayerType::Floor</a>:</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  result = layerSupportObject->IsFloorSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  reason);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="keywordflow">break</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"> 319</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e">LayerType::FullyConnected</a>:</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  {</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const FullyConnectedLayer*>(&layer);</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  BOOST_ASSERT(cLayer->m_Weight.get() != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> </div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> biasInfo;</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> * biasInfoPtr = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keyword">static</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> dummyBFloat16Bias(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({1,1,1,1}), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>);</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keyword">static</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> dummyFloat16Bias(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({1,1,1,1}), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>);</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="keyword">static</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> dummyFloat32Bias(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({1,1,1,1}), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="keyword">static</span> <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> dummyQA8Bias(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({1,1,1,1}), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>);</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> </div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">FullyConnectedDescriptor</a>& descriptor = cLayer->GetParameters();</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</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>  BOOST_ASSERT(cLayer->m_Bias.get() != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  biasInfo = OverrideDataType(cLayer->m_Bias->GetTensorInfo(), <a class="code" href="namespacearmnn.xhtml#a83c4a275acf59f62b8387f389d0929d5">GetBiasTypeFromWeightsType</a>(dataType));</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  biasInfoPtr = &biasInfo;</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">else</span></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>  <span class="comment">// If biases are not enabled pass a dummy tensorinfo for the validation</span></div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordflow">switch</span>(input.GetDataType())</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  {</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>:</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  {</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  biasInfoPtr = &dummyBFloat16Bias;</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  }</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>:</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  {</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  biasInfoPtr = &dummyFloat16Bias;</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keywordflow">break</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"> 355</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>:</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>  biasInfoPtr = &dummyFloat32Bias;</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  }</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>:</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">DataType::QAsymmS8</a>:</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>:</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>:</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  {</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  biasInfoPtr = &dummyQA8Bias;</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  }</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <span class="keywordflow">default</span>:</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>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Unexpected bias type"</span>);</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  }</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  }</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  }</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> </div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  result = layerSupportObject->IsFullyConnectedSupported(</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  OverrideDataType(input, dataType),</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  OverrideDataType(cLayer->m_Weight->GetTensorInfo(), dataType),</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  *biasInfoPtr,</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  descriptor,</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  reason);</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  }</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aad22c799930d644e8468fe44c0312d53">LayerType::Gather</a>:</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  {</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  result = layerSupportObject->IsGatherSupported(OverrideDataType(input0, dataType),</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  input1,</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  reason);</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  }</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">LayerType::Input</a>:</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  {</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  result = layerSupportObject->IsInputSupported(OverrideDataType(input, dataType), reason);</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keywordflow">break</span>;</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a21baa4498161d195f5bb2e3627344ba4">LayerType::InstanceNormalization</a>:</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  {</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const InstanceNormalizationLayer*>(&layer);</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml">InstanceNormalizationDescriptor</a>& descriptor = cLayer->GetParameters();</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span> </div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span> </div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  result = layerSupportObject->IsInstanceNormalizationSupported(</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  OverrideDataType(input, dataType),</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  descriptor,</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  reason);</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  }</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1189467870bc421ae59277e750263eb2">LayerType::L2Normalization</a>:</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  {</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const L2NormalizationLayer*>(&layer);</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_l2_normalization_descriptor.xhtml">L2NormalizationDescriptor</a>& descriptor = cLayer->GetParameters();</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span> </div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span> </div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  result = layerSupportObject->IsL2NormalizationSupported(</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  OverrideDataType(input, dataType),</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  descriptor,</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  reason);</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  }</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ac21dbda57d88c21ec9857f5d1522c488">LayerType::LogSoftmax</a>:</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>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const LogSoftmaxLayer*>(&layer);</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span> </div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span> </div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  result = layerSupportObject->IsLogSoftmaxSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  reason);</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <span class="keywordflow">break</span>;</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a06b091bc9aea697ba473c71f0bb55925">LayerType::Lstm</a>:</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  {</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const LstmLayer*>(&layer);</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml">LstmDescriptor</a>& descriptor = cLayer->GetParameters();</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>  <span class="comment">// All inputs.</span></div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>(),</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  dataType);</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_tensor_info.xhtml">TensorInfo</a>& outputStateIn = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>(),</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  dataType);</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& cellStateIn = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(2).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>(),</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  dataType);</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="comment">// All outputs</span></div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& scratchBuffer = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>(), dataType);</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& outputStateOut = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>(), dataType);</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& cellStateOut = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>(), dataType);</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(3).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>(), dataType);</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span> </div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <span class="comment">// Basic parameters</span></div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputToForgetWeights</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  = OverrideDataType(cLayer->m_BasicParameters.m_InputToForgetWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputToCellWeights</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  = OverrideDataType(cLayer->m_BasicParameters.m_InputToCellWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputToOutputWeights</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  = OverrideDataType(cLayer->m_BasicParameters.m_InputToOutputWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& recurrentToForgetWeights</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  = OverrideDataType(cLayer->m_BasicParameters.m_RecurrentToForgetWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& recurrentToCellWeights</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  = OverrideDataType(cLayer->m_BasicParameters.m_RecurrentToCellWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& recurrentToOutputWeights</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  = OverrideDataType(cLayer->m_BasicParameters.m_RecurrentToOutputWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& forgetGateBias</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  = OverrideDataType(cLayer->m_BasicParameters.m_ForgetGateBias->GetTensorInfo(), dataType);</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& cellBias</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  = OverrideDataType(cLayer->m_BasicParameters.m_CellBias->GetTensorInfo(), dataType);</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& outputGateBias</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  = OverrideDataType(cLayer->m_BasicParameters.m_OutputGateBias->GetTensorInfo(), dataType);</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span> </div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <a class="code" href="structarmnn_1_1_lstm_input_params_info.xhtml">LstmInputParamsInfo</a> paramsInfo;</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span> </div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  paramsInfo.<a class="code" href="structarmnn_1_1_lstm_input_params_info.xhtml#a4b3f6e6f2268416ffd7a34fda95ffd0b">m_InputToForgetWeights</a> = &inputToForgetWeights;</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  paramsInfo.m_InputToCellWeights = &inputToCellWeights;</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  paramsInfo.m_InputToOutputWeights = &inputToOutputWeights;</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  paramsInfo.m_RecurrentToForgetWeights = &recurrentToForgetWeights;</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  paramsInfo.m_RecurrentToCellWeights = &recurrentToCellWeights;</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  paramsInfo.m_RecurrentToOutputWeights = &recurrentToOutputWeights;</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  paramsInfo.m_ForgetGateBias = &forgetGateBias;</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  paramsInfo.m_CellBias = &cellBias;</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  paramsInfo.m_OutputGateBias = &outputGateBias;</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"> 495</span>  <span class="comment">// Optional parameters</span></div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optInputToInputWeights;</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optRecurrentToInputWeights;</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optCellToInputWeights;</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optInputGateBias;</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optProjectionWeights;</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optProjectionBias;</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optCellToForgetWeights;</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optCellToOutputWeights;</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optInputLayerNormWeights;</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optForgetLayerNormWeights;</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optCellLayerNormWeights;</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> optOutputLayerNormWeights;</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>  <span class="keywordflow">if</span>(!descriptor.m_CifgEnabled)</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  {</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  optInputToInputWeights =</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  OverrideDataType(cLayer->m_CifgParameters.m_InputToInputWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  paramsInfo.m_InputToInputWeights = &optInputToInputWeights;</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span> </div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  optRecurrentToInputWeights =</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  OverrideDataType(cLayer->m_CifgParameters.m_RecurrentToInputWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  paramsInfo.m_RecurrentToInputWeights = &optRecurrentToInputWeights;</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="keywordflow">if</span> (cLayer->m_CifgParameters.m_CellToInputWeights != <span class="keyword">nullptr</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>  optCellToInputWeights =</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  OverrideDataType(cLayer->m_CifgParameters.m_CellToInputWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  paramsInfo.m_CellToInputWeights = &optCellToInputWeights;</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  }</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  optInputGateBias =</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  OverrideDataType(cLayer->m_CifgParameters.m_InputGateBias->GetTensorInfo(), dataType);</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  paramsInfo.m_InputGateBias = &optInputGateBias;</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  }</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span> </div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <span class="keywordflow">if</span>(descriptor.m_ProjectionEnabled)</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  {</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  optProjectionWeights =</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  OverrideDataType(cLayer->m_ProjectionParameters.m_ProjectionWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  paramsInfo.m_ProjectionWeights = &optProjectionWeights;</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  <span class="keywordflow">if</span> (cLayer->m_ProjectionParameters.m_ProjectionBias != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  {</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  optProjectionBias =</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  OverrideDataType(cLayer->m_ProjectionParameters.m_ProjectionBias->GetTensorInfo(), dataType);</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  paramsInfo.m_ProjectionBias = &optProjectionBias;</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  }</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  }</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span> </div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  <span class="keywordflow">if</span>(descriptor.m_PeepholeEnabled)</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  {</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  optCellToForgetWeights =</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  OverrideDataType(cLayer->m_PeepholeParameters.m_CellToForgetWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  paramsInfo.m_CellToForgetWeights = &optCellToForgetWeights;</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  optCellToOutputWeights =</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  OverrideDataType(cLayer->m_PeepholeParameters.m_CellToOutputWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  paramsInfo.m_CellToOutputWeights = &optCellToOutputWeights;</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"> 552</span>  <span class="keywordflow">if</span>(descriptor.m_LayerNormEnabled)</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>  <span class="keywordflow">if</span> (!descriptor.m_CifgEnabled)</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  {</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  optInputLayerNormWeights = OverrideDataType(</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  cLayer->m_LayerNormParameters.m_InputLayerNormWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  paramsInfo.m_InputLayerNormWeights = &optInputLayerNormWeights;</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  }</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span> </div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  optForgetLayerNormWeights = OverrideDataType(</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  cLayer->m_LayerNormParameters.m_ForgetLayerNormWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  paramsInfo.m_ForgetLayerNormWeights = &optForgetLayerNormWeights;</div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span> </div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  optCellLayerNormWeights = OverrideDataType(</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  cLayer->m_LayerNormParameters.m_CellLayerNormWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  paramsInfo.m_CellLayerNormWeights = &optCellLayerNormWeights;</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span> </div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  optOutputLayerNormWeights = OverrideDataType(</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  cLayer->m_LayerNormParameters.m_OutputLayerNormWeights->GetTensorInfo(), dataType);</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  paramsInfo.m_OutputLayerNormWeights = &optOutputLayerNormWeights;</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>  result = layerSupportObject->IsLstmSupported(</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  input,</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  outputStateIn,</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  cellStateIn,</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  scratchBuffer,</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  outputStateOut,</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  cellStateOut,</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  output,</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  descriptor,</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  paramsInfo,</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  reason);</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  <span class="keywordflow">break</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"> 587</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a8321e79c278ec510f63675c040594892">LayerType::Maximum</a>:</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  {</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span> </div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  result = layerSupportObject->IsMaximumSupported(OverrideDataType(input0, dataType),</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  OverrideDataType(input1, dataType),</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  reason);</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  }</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>:</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</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>  result = layerSupportObject->IsMemCopySupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  reason);</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  }</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9">LayerType::MemImport</a>:</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  {</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span> </div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  result = layerSupportObject->IsMemImportSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  reason);</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  }</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a68be4837f6c739877233e527a996dd00">LayerType::Merge</a>:</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  {</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span> </div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  result = layerSupportObject->IsMergeSupported(OverrideDataType(input0, dataType),</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  OverrideDataType(input1, dataType),</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  reason);</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  }</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ae20f0f2826a6549809f050b86274567f">LayerType::Concat</a>:</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>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const ConcatLayer*>(&layer);</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span> </div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  <span class="comment">// Get vector of all inputs.</span></div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  <span class="keyword">auto</span> getTensorInfo = [&dataType](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_input_slot.xhtml">InputSlot</a>& slot)</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  {</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  <span class="keywordflow">return</span> OverrideDataType(slot.GetConnectedOutputSlot()->GetTensorInfo(), dataType);</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>  <span class="keyword">auto</span> beginI = boost::make_transform_iterator(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#af5f530544d09a44d726f24702b67b35b">GetInputSlots</a>().begin(), getTensorInfo);</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  <span class="keyword">auto</span> endI = boost::make_transform_iterator(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#af5f530544d09a44d726f24702b67b35b">GetInputSlots</a>().end(), getTensorInfo);</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  std::vector<TensorInfo> inputs(beginI, endI);</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">auto</span> getTensorInfoPtr = [](<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>)</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">return</span> &<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</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>  <span class="keyword">auto</span> beginPtr = boost::make_transform_iterator(inputs.begin(), getTensorInfoPtr);</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  <span class="keyword">auto</span> endPtr = boost::make_transform_iterator(inputs.end(), getTensorInfoPtr);</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  std::vector<const TensorInfo*> inputPtrs(beginPtr, endPtr);</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span> </div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span> </div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  result = layerSupportObject->IsConcatSupported(inputPtrs, output, cLayer->GetParameters(), reason);</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span> </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>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  }</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a27d1a1f7b7c2180e5b20ce9e3d00e2dd">LayerType::Multiplication</a>:</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  {</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  result = layerSupportObject->IsMultiplicationSupported(</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  OverrideDataType(input0, dataType),</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  OverrideDataType(input1, dataType),</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  reason);</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  }</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f">LayerType::Normalization</a>:</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="keyword">auto</span> cLayer = boost::polymorphic_downcast<const NormalizationLayer*>(&layer);</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  result = layerSupportObject->IsNormalizationSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  reason);</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  }</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">LayerType::Output</a>:</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  result = layerSupportObject->IsOutputSupported(OverrideDataType(output, dataType), reason);</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  }</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">LayerType::Permute</a>:</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  {</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const PermuteLayer*>(&layer);</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  result = layerSupportObject->IsPermuteSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  reason);</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  }</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ade43468adaf6acb2c38ebc0c1176f82f">LayerType::Pad</a>:</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  {</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const PadLayer*>(&layer);</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  result = layerSupportObject->IsPadSupported(</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  OverrideDataType(input, dataType),</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  reason);</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  }</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ad662867a41bfb30b9f75dda2b5849001">LayerType::Pooling2d</a>:</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  {</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const Pooling2dLayer*>(&layer);</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  result = layerSupportObject->IsPooling2dSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  reason);</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  <span class="keywordflow">break</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">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1ba143ebe524d46181a4b53470693278">LayerType::PreCompiled</a>:</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="keyword">auto</span> cLayer = boost::polymorphic_downcast<const PreCompiledLayer*>(&layer);</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  result = layerSupportObject->IsPreCompiledSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  reason);</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  }</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aca39930e22f40d10155a57dba32240bb">LayerType::Quantize</a>:</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  {</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  result = layerSupportObject->IsQuantizeSupported(input, output, reason);</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a890a37ff3bfe123414ba7e6f052b49f3">LayerType::QuantizedLstm</a>:</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>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const QuantizedLstmLayer*>(&layer);</div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span> </div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  <span class="comment">// Inputs</span></div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& previousCellStateIn = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& previousOutputIn = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(2).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span> </div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  <span class="comment">// Outputs</span></div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& cellStateOut = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</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>  <span class="comment">// QuantizedLstm parameters</span></div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml">QuantizedLstmInputParamsInfo</a> paramsInfo;</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>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a15f9f65126ad3d4d82d6c19d0662ae01">m_InputToInputWeights</a> =</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  &cLayer->m_QuantizedLstmParameters.m_InputToInputWeights->GetTensorInfo();</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a4b3f6e6f2268416ffd7a34fda95ffd0b">m_InputToForgetWeights</a> =</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  &cLayer->m_QuantizedLstmParameters.m_InputToForgetWeights->GetTensorInfo();</div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#af07c65d3b7886a00f10c69093e76a341">m_InputToCellWeights</a> =</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  &cLayer->m_QuantizedLstmParameters.m_InputToCellWeights->GetTensorInfo();</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a33242cb43250f04f1736161ca8ad2db9">m_InputToOutputWeights</a> =</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  &cLayer->m_QuantizedLstmParameters.m_InputToOutputWeights->GetTensorInfo();</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>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a9ab864961ded72f5ce7ea4eb9921f826">m_RecurrentToInputWeights</a> =</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  &cLayer->m_QuantizedLstmParameters.m_RecurrentToInputWeights->GetTensorInfo();</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a11b90bd2694aa7f4b434aadd75fbb1c2">m_RecurrentToForgetWeights</a> =</div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  &cLayer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights->GetTensorInfo();</div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a6c7873a3320a59a63aa26c006db905c0">m_RecurrentToCellWeights</a> =</div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  &cLayer->m_QuantizedLstmParameters.m_RecurrentToCellWeights->GetTensorInfo();</div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#af434b509cd5232ef762c4b21b2dfaae0">m_RecurrentToOutputWeights</a> =</div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  &cLayer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights->GetTensorInfo();</div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span> </div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a042ea9d6d3842b87f112db126e806a93">m_InputGateBias</a> =</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  &cLayer->m_QuantizedLstmParameters.m_InputGateBias->GetTensorInfo();</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a21626d0b91f8942c3ef8e48e17db9f21">m_ForgetGateBias</a> =</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  &cLayer->m_QuantizedLstmParameters.m_ForgetGateBias->GetTensorInfo();</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#ab173a067eeb7295d84f5327bcc05a6c1">m_CellBias</a> =</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  &cLayer->m_QuantizedLstmParameters.m_CellBias->GetTensorInfo();</div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  paramsInfo.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a48cb83dcb58c786ea36f5d37695e75b1">m_OutputGateBias</a> =</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  &cLayer->m_QuantizedLstmParameters.m_OutputGateBias->GetTensorInfo();;</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>  result = layerSupportObject->IsQuantizedLstmSupported(input,</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  previousCellStateIn,</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  previousOutputIn,</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  cellStateOut,</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  output,</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  paramsInfo,</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  reason);</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  }</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a3025cdaab2deb0bb2cd642449e570833">LayerType::Division</a>:</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  {</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  result = layerSupportObject->IsDivisionSupported(</div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  OverrideDataType(input0, dataType),</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  OverrideDataType(input1, dataType),</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  reason);</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  }</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aa7c59ccedc6a3bd90c17f3b990afefad">LayerType::Reshape</a>:</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  {</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const ReshapeLayer*>(&layer);</div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  result = layerSupportObject->IsReshapeSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  reason);</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  }</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a9d723d04c40bfd81835c0766a698cf63">LayerType::Resize</a>:</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  {</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const ResizeLayer*>(&layer);</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  result = layerSupportObject->IsResizeSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  reason);</div><div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  }</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ad140d37ad98c12ccd8e1c432f548bcdb">LayerType::Slice</a>:</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  {</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const SliceLayer*>(&layer);</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</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>  result = layerSupportObject->IsSliceSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  reason);</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  <span class="keywordflow">break</span>;</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a31d953b9d49a6b4378f45097047976d0">LayerType::Softmax</a>:</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="keyword">auto</span> cLayer = boost::polymorphic_downcast<const SoftmaxLayer*>(&layer);</div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  result = layerSupportObject->IsSoftmaxSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  reason);</div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  }</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a337c392144dca0d18290c6b4711a2279">LayerType::SpaceToBatchNd</a>:</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  {</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const SpaceToBatchNdLayer*>(&layer);</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  result = layerSupportObject->IsSpaceToBatchNdSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  reason);</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  }</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a5e7ff12da912dc79e7e547281823fa4a">LayerType::SpaceToDepth</a>:</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  {</div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const SpaceToDepthLayer*>(&layer);</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span> </div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</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>  result = layerSupportObject->IsSpaceToDepthSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  reason);</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  }</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a41cb9b797ebc6f6f6314e3ded935f4cf">LayerType::Splitter</a>:</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  {</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const SplitterLayer*>(&layer);</div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</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">// Get vector of all outputs.</span></div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  <span class="keyword">auto</span> getTensorInfo = [&dataType](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>& slot)</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> OverrideDataType(slot.GetTensorInfo(), dataType);</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>  <span class="keyword">auto</span> beginI = boost::make_transform_iterator(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a98cdff4e0b45f4c80bfcedaf926e16e0">GetOutputSlots</a>().begin(), getTensorInfo);</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  <span class="keyword">auto</span> endI = boost::make_transform_iterator(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a98cdff4e0b45f4c80bfcedaf926e16e0">GetOutputSlots</a>().end(), getTensorInfo);</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  std::vector<TensorInfo> outputs(beginI, endI);</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span> </div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  <span class="keyword">const</span> std::vector<std::reference_wrapper<TensorInfo>> outputPtrs(outputs.begin(), outputs.end());</div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span> </div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  result = layerSupportObject->IsSplitterSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  outputPtrs,</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  reason);</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  <span class="keywordflow">break</span>;</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a2187e1021a911b3807cc1bea2eb1a9ca">LayerType::Stack</a>:</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  {</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const StackLayer*>(&layer);</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span> </div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  <span class="comment">// Get vector of all inputs.</span></div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span>  <span class="keyword">auto</span> getTensorInfo = [&dataType](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_input_slot.xhtml">InputSlot</a>& slot)</div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  {</div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  <span class="keywordflow">return</span> OverrideDataType(slot.GetConnectedOutputSlot()->GetTensorInfo(), dataType);</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  };</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <span class="keyword">auto</span> beginI = boost::make_transform_iterator(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#af5f530544d09a44d726f24702b67b35b">GetInputSlots</a>().begin(), getTensorInfo);</div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  <span class="keyword">auto</span> endI = boost::make_transform_iterator(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#af5f530544d09a44d726f24702b67b35b">GetInputSlots</a>().end(), getTensorInfo);</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  std::vector<TensorInfo> inputs(beginI, endI);</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span> </div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  <span class="keyword">auto</span> getTensorInfoPtr = [](<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>)</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  {</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  <span class="keywordflow">return</span> &<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  };</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  <span class="keyword">auto</span> beginPtr = boost::make_transform_iterator(inputs.begin(), getTensorInfoPtr);</div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  <span class="keyword">auto</span> endPtr = boost::make_transform_iterator(inputs.end(), getTensorInfoPtr);</div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  std::vector<const TensorInfo*> inputPtrs(beginPtr, endPtr);</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span> </div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span> </div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  result = layerSupportObject->IsStackSupported(inputPtrs, output, cLayer->GetParameters(), reason);</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span> </div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  }</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a93bca63ecbb003649425dd0e4ba79a99">LayerType::StandIn</a>:</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  {</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const StandInLayer*>(&layer);</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span> </div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  <span class="comment">// Get vector of all inputs.</span></div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  <span class="keyword">auto</span> getTensorInfoIn = [&dataType](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_input_slot.xhtml">InputSlot</a>& slot)</div><div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  {</div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  <span class="keywordflow">return</span> OverrideDataType(slot.GetConnectedOutputSlot()->GetTensorInfo(), dataType);</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  };</div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  <span class="keyword">auto</span> getTensorInfoOut = [&dataType](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>& slot)</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  {</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  <span class="keywordflow">return</span> OverrideDataType(slot.GetTensorInfo(), dataType);</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="keyword">auto</span> beginI = boost::make_transform_iterator(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#af5f530544d09a44d726f24702b67b35b">GetInputSlots</a>().begin(), getTensorInfoIn);</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  <span class="keyword">auto</span> endI = boost::make_transform_iterator(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#af5f530544d09a44d726f24702b67b35b">GetInputSlots</a>().end(), getTensorInfoIn);</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  std::vector<TensorInfo> inputs(beginI, endI);</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span> </div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  <span class="keyword">auto</span> beginO = boost::make_transform_iterator(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a98cdff4e0b45f4c80bfcedaf926e16e0">GetOutputSlots</a>().begin(), getTensorInfoOut);</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  <span class="keyword">auto</span> endO = boost::make_transform_iterator(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a98cdff4e0b45f4c80bfcedaf926e16e0">GetOutputSlots</a>().end(), getTensorInfoOut);</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  std::vector<TensorInfo> outputs(beginO, endO);</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span> </div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span> </div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  <span class="keyword">auto</span> getTensorInfoPtr = [](<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>)</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  {</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  <span class="keywordflow">return</span> &<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  };</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  <span class="keyword">auto</span> beginPtrI = boost::make_transform_iterator(inputs.begin(), getTensorInfoPtr);</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  <span class="keyword">auto</span> endPtrI = boost::make_transform_iterator(inputs.end(), getTensorInfoPtr);</div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  std::vector<const TensorInfo*> inputPtrs(beginPtrI, endPtrI);</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span> </div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  <span class="keyword">auto</span> beginPtrO = boost::make_transform_iterator(outputs.begin(), getTensorInfoPtr);</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  <span class="keyword">auto</span> endPtrO = boost::make_transform_iterator(outputs.end(), getTensorInfoPtr);</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  std::vector<const TensorInfo*> outputPtrs(beginPtrO, endPtrO);</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</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>  result = layerSupportObject->IsStandInSupported(inputPtrs,</div><div class="line"><a name="l00957"></a><span class="lineno"> 957</span>  outputPtrs,</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  reason);</div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  <span class="keywordflow">break</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">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aa31904f2b3479b5a00137fd985974b4d">LayerType::StridedSlice</a>:</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>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const StridedSliceLayer*>(&layer);</div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  result = layerSupportObject->IsStridedSliceSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  cLayer->GetParameters(),</div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  reason);</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  }</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a6eb8b8b560161603402c0238b3a7d8b0">LayerType::Subtraction</a>:</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  {</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  result = layerSupportObject->IsSubtractionSupported(</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  OverrideDataType(input0, dataType),</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  OverrideDataType(input1, dataType),</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  reason);</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  }</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4abbc155fb2b111bf61c4f5ff892915e6b">LayerType::Switch</a>:</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  result = layerSupportObject->IsSwitchSupported(OverrideDataType(input0, dataType),</div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  OverrideDataType(input1, dataType),</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span>  OverrideDataType(output0, dataType),</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span>  OverrideDataType(output1, dataType),</div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span>  reason);</div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  }</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a3d6c9ac08ada31c184094bbc67afe00d">LayerType::Mean</a>:</div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span>  {</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const MeanLayer*>(&layer);</div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>  result = layerSupportObject->IsMeanSupported(</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>  OverrideDataType(input, dataType),</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>  cLayer->GetParameters(),</div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  reason);</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  }</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aa1d0ec6d56f8833a078b5a7ac4caf2d4">LayerType::Minimum</a>:</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input0 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input1 = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  result = layerSupportObject->IsMinimumSupported(OverrideDataType(input0, dataType),</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  OverrideDataType(input1, dataType),</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  reason);</div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>  }</div><div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32">LayerType::Prelu</a>:</div><div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>  {</div><div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& alpha = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>  result = layerSupportObject->IsPreluSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  OverrideDataType(alpha, dataType),</div><div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>  reason);</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  }</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aaf70b1ac863830a4e1ce6268c8399f54">LayerType::Transpose</a>:</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>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const TransposeLayer*>(&layer);</div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& input = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output = layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>  result = layerSupportObject->IsTransposeSupported(OverrideDataType(input, dataType),</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  OverrideDataType(output, dataType),</div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  cLayer->GetParameters(),</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>  reason);</div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  }</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a71b23d26c0f5d20416d6c77754f9806a">LayerType::TransposeConvolution2d</a>:</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>  {</div><div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>  <span class="keyword">auto</span> cLayer = boost::polymorphic_downcast<const TransposeConvolution2dLayer*>(&layer);</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> input = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>(),</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  dataType);</div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> output = OverrideDataType(layer.<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>(), dataType);</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span> </div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">TransposeConvolution2dDescriptor</a>& descriptor = cLayer->GetParameters();</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>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<TensorInfo></a> biases;</div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>  <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>  {</div><div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>  BOOST_ASSERT(cLayer->m_Bias.get() != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  biases = OverrideDataType(cLayer->m_Bias->GetTensorInfo(),</div><div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>  <a class="code" href="namespacearmnn.xhtml#a83c4a275acf59f62b8387f389d0929d5">GetBiasTypeFromWeightsType</a>(dataType));</div><div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  }</div><div class="line"><a name="l01060"></a><span class="lineno"> 1060</span> </div><div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  BOOST_ASSERT(cLayer->m_Weight.get() != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> weights = OverrideDataType(cLayer->m_Weight->GetTensorInfo(), dataType);</div><div class="line"><a name="l01063"></a><span class="lineno"> 1063</span> </div><div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>  result = layerSupportObject->IsTransposeConvolution2dSupported(input,</div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  output,</div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>  descriptor,</div><div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>  weights,</div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>  biases,</div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>  reason);</div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span> </div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>  }</div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  {</div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"WorkloadFactory did not recognise type of layer."</span>);</div><div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>  reason.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>() = <span class="stringliteral">"Unrecognised layer type"</span>;</div><div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>  result = <span class="keyword">false</span>;</div><div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>  }</div><div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>  }</div><div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l01082"></a><span class="lineno"> 1082</span> }</div><div class="line"><a name="l01083"></a><span class="lineno"> 1083</span> </div><div class="line"><a name="l01084"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a7d94ea841143b76fe08ccb308839bfd7"> 1084</a></span> <span class="keywordtype">bool</span> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a74dc9ec1a223eab8b072368b2dacee87">IWorkloadFactory::IsLayerSupported</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>& connectableLayer,</div><div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<DataType></a> dataType,</div><div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>  std::string& outReasonIfUnsupported)</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>  <span class="keyword">auto</span> layer = boost::polymorphic_downcast<const Layer*>(&connectableLayer);</div><div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a74dc9ec1a223eab8b072368b2dacee87">IsLayerSupported</a>(layer->GetBackendId(), connectableLayer, dataType, outReasonIfUnsupported);</div><div class="line"><a name="l01090"></a><span class="lineno"> 1090</span> }</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span> </div><div class="line"><a name="l01092"></a><span class="lineno"> 1092</span> <span class="comment">// Default Implementations</span></div><div class="line"><a name="l01093"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#ae3ba329a833bbb63961eb64d6477d691"> 1093</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ae3ba329a833bbb63961eb64d6477d691">IWorkloadFactory::CreateAbs</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_abs_queue_descriptor.xhtml">AbsQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span> <span class="keyword"></span>{</div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span> }</div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span> </div><div class="line"><a name="l01099"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5"> 1099</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5">IWorkloadFactory::CreateActivation</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_activation_queue_descriptor.xhtml">ActivationQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</span> <span class="keyword"></span>{</div><div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span> }</div><div class="line"><a name="l01104"></a><span class="lineno"> 1104</span> </div><div class="line"><a name="l01105"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e"> 1105</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">IWorkloadFactory::CreateAddition</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">AdditionQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01107"></a><span class="lineno"> 1107</span> <span class="keyword"></span>{</div><div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01109"></a><span class="lineno"> 1109</span> }</div><div class="line"><a name="l01110"></a><span class="lineno"> 1110</span> </div><div class="line"><a name="l01111"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#ac47803c9faacfb7c10219253b99f61ca"> 1111</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac47803c9faacfb7c10219253b99f61ca">IWorkloadFactory::CreateArgMinMax</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_arg_min_max_queue_descriptor.xhtml">ArgMinMaxQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01113"></a><span class="lineno"> 1113</span> <span class="keyword"></span>{</div><div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01115"></a><span class="lineno"> 1115</span> }</div><div class="line"><a name="l01116"></a><span class="lineno"> 1116</span> </div><div class="line"><a name="l01117"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#abe1e0d40e23195022c0bc10a8aab55ea"> 1117</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#abe1e0d40e23195022c0bc10a8aab55ea">IWorkloadFactory::CreateBatchNormalization</a>(</div><div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">BatchNormalizationQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span> <span class="keyword"></span>{</div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#af00ce13ef7dabd17cc4186d0a4991757"> 1123</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#af00ce13ef7dabd17cc4186d0a4991757">IWorkloadFactory::CreateBatchToSpaceNd</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_to_space_nd_queue_descriptor.xhtml">BatchToSpaceNdQueueDescriptor</a>& <span class="comment">/*desc*/</span>,</div><div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*Info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span> <span class="keyword"></span>{</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span> }</div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span> </div><div class="line"><a name="l01129"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a3fa12033e9be37c529ac54a83ab43b36"> 1129</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a3fa12033e9be37c529ac54a83ab43b36">IWorkloadFactory::CreateComparison</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_comparison_queue_descriptor.xhtml">ComparisonQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span> <span class="keyword"></span>{</div><div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01133"></a><span class="lineno"> 1133</span> }</div><div class="line"><a name="l01134"></a><span class="lineno"> 1134</span> </div><div class="line"><a name="l01135"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a32bb8d6cf5fc028bf501252767c08b21"> 1135</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a32bb8d6cf5fc028bf501252767c08b21">IWorkloadFactory::CreateConcat</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_concat_queue_descriptor.xhtml">ConcatQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01137"></a><span class="lineno"> 1137</span> <span class="keyword"></span>{</div><div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01139"></a><span class="lineno"> 1139</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"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a963bd7acce29a83d96daeb2cea34f2f7"> 1141</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a963bd7acce29a83d96daeb2cea34f2f7">IWorkloadFactory::CreateConstant</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_constant_queue_descriptor.xhtml">ConstantQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span> <span class="keyword"></span>{</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span> }</div><div class="line"><a name="l01146"></a><span class="lineno"> 1146</span> </div><div class="line"><a name="l01147"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a83e0a21747c1ce29b2083c1e3b1d88af"> 1147</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a83e0a21747c1ce29b2083c1e3b1d88af">IWorkloadFactory::CreateConvertFp16ToFp32</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convert_fp16_to_fp32_queue_descriptor.xhtml">ConvertFp16ToFp32QueueDescriptor</a>& <span class="comment">/*desc*/</span>,</div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span> <span class="keyword"></span>{</div><div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01151"></a><span class="lineno"> 1151</span> }</div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span> </div><div class="line"><a name="l01153"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a2b414a001b6b31d00bfe4056fd6740c5"> 1153</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a2b414a001b6b31d00bfe4056fd6740c5">IWorkloadFactory::CreateConvertFp32ToFp16</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convert_fp32_to_fp16_queue_descriptor.xhtml">ConvertFp32ToFp16QueueDescriptor</a>& <span class="comment">/*desc*/</span>,</div><div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01155"></a><span class="lineno"> 1155</span> <span class="keyword"></span>{</div><div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01157"></a><span class="lineno"> 1157</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"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a2184995027cd2c9f9980206de9658855"> 1159</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a2184995027cd2c9f9980206de9658855">IWorkloadFactory::CreateConvolution2d</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">Convolution2dQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span> <span class="keyword"></span>{</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01165"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a00346a3754d9411bba2e29dc1f996ac6"> 1165</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a00346a3754d9411bba2e29dc1f996ac6">IWorkloadFactory::CreateDebug</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_debug_queue_descriptor.xhtml">DebugQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span> <span class="keyword"></span>{</div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span> }</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span> </div><div class="line"><a name="l01171"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a3c3a47828ee252dca111605c9be4b072"> 1171</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a3c3a47828ee252dca111605c9be4b072">IWorkloadFactory::CreateDepthToSpace</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depth_to_space_queue_descriptor.xhtml">DepthToSpaceQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span> <span class="keyword"></span>{</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span> }</div><div class="line"><a name="l01176"></a><span class="lineno"> 1176</span> </div><div class="line"><a name="l01177"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#accb9759dfd2880efe0f8d2705ddee448"> 1177</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#accb9759dfd2880efe0f8d2705ddee448">IWorkloadFactory::CreateDepthwiseConvolution2d</a>(</div><div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">DepthwiseConvolution2dQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span> <span class="keyword"></span>{</div><div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01183"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a3243806bf6c89df8952cc0a3601e538b"> 1183</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a3243806bf6c89df8952cc0a3601e538b">IWorkloadFactory::CreateDequantize</a>(</div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_dequantize_queue_descriptor.xhtml">DequantizeQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span> <span class="keyword"></span>{</div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01187"></a><span class="lineno"> 1187</span> }</div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span> </div><div class="line"><a name="l01189"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#ad0da07faa15302377aa97be89c57677c"> 1189</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ad0da07faa15302377aa97be89c57677c">IWorkloadFactory::CreateDetectionPostProcess</a>(</div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_detection_post_process_queue_descriptor.xhtml">DetectionPostProcessQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</span> <span class="keyword"></span>{</div><div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01193"></a><span class="lineno"> 1193</span> }</div><div class="line"><a name="l01194"></a><span class="lineno"> 1194</span> </div><div class="line"><a name="l01195"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a20bb773c7fd6253418bdedac1312cd19"> 1195</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a20bb773c7fd6253418bdedac1312cd19">IWorkloadFactory::CreateDivision</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_division_queue_descriptor.xhtml">DivisionQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span> <span class="keyword"></span>{</div><div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01201"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a12d2c4e0f0b0d6b36d8a3e14bf69f9e4"> 1201</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a12d2c4e0f0b0d6b36d8a3e14bf69f9e4">IWorkloadFactory::CreateElementwiseUnary</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_elementwise_unary_queue_descriptor.xhtml">ElementwiseUnaryQueueDescriptor</a>& <span class="comment">/*desc*/</span>,</div><div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span> <span class="keyword"></span>{</div><div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01205"></a><span class="lineno"> 1205</span> }</div><div class="line"><a name="l01206"></a><span class="lineno"> 1206</span> </div><div class="line"><a name="l01207"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a096bb62d44fadf079ea4463379d4e6aa"> 1207</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a096bb62d44fadf079ea4463379d4e6aa">IWorkloadFactory::CreateEqual</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_equal_queue_descriptor.xhtml">EqualQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*Info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</span> <span class="keyword"></span>{</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01213"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a42581f3d1c22e64b7f3676ea20acab0e"> 1213</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a42581f3d1c22e64b7f3676ea20acab0e">IWorkloadFactory::CreateFakeQuantization</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fake_quantization_queue_descriptor.xhtml">FakeQuantizationQueueDescriptor</a>& <span class="comment">/*desc*/</span>,</div><div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01215"></a><span class="lineno"> 1215</span> <span class="keyword"></span>{</div><div class="line"><a name="l01216"></a><span class="lineno"> 1216</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01219"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#aa1a45333dc35cb5ba9ab71fca4f359e4"> 1219</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#aa1a45333dc35cb5ba9ab71fca4f359e4">IWorkloadFactory::CreateFloor</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_floor_queue_descriptor.xhtml">FloorQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01221"></a><span class="lineno"> 1221</span> <span class="keyword"></span>{</div><div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a1c193739520e08f686b347ff795ad2fe"> 1225</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a1c193739520e08f686b347ff795ad2fe">IWorkloadFactory::CreateFullyConnected</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml">FullyConnectedQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01227"></a><span class="lineno"> 1227</span> <span class="keyword"></span>{</div><div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01229"></a><span class="lineno"> 1229</span> }</div><div class="line"><a name="l01230"></a><span class="lineno"> 1230</span> </div><div class="line"><a name="l01231"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a91fe56cae7e970d90f6e7f54427e7d44"> 1231</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a91fe56cae7e970d90f6e7f54427e7d44">IWorkloadFactory::CreateGather</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_gather_queue_descriptor.xhtml">GatherQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01233"></a><span class="lineno"> 1233</span> <span class="keyword"></span>{</div><div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01235"></a><span class="lineno"> 1235</span> }</div><div class="line"><a name="l01236"></a><span class="lineno"> 1236</span> </div><div class="line"><a name="l01237"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a4e779d1b00a9e885497364ebd0dc24ef"> 1237</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a4e779d1b00a9e885497364ebd0dc24ef">IWorkloadFactory::CreateGreater</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_greater_queue_descriptor.xhtml">GreaterQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01238"></a><span class="lineno"> 1238</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01239"></a><span class="lineno"> 1239</span> <span class="keyword"></span>{</div><div class="line"><a name="l01240"></a><span class="lineno"> 1240</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span> }</div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span> </div><div class="line"><a name="l01243"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a96a3123d8a8290b01582d955cdcd75d5"> 1243</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a96a3123d8a8290b01582d955cdcd75d5">IWorkloadFactory::CreateInstanceNormalization</a>(</div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_instance_normalization_queue_descriptor.xhtml">InstanceNormalizationQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01246"></a><span class="lineno"> 1246</span> <span class="keyword"></span>{</div><div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01250"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a3c86f886e36ce943f1ebc241a37f0413"> 1250</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a3c86f886e36ce943f1ebc241a37f0413">IWorkloadFactory::CreateL2Normalization</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_l2_normalization_queue_descriptor.xhtml">L2NormalizationQueueDescriptor</a>& <span class="comment">/*desc*/</span>,</div><div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01252"></a><span class="lineno"> 1252</span> <span class="keyword"></span>{</div><div class="line"><a name="l01253"></a><span class="lineno"> 1253</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01254"></a><span class="lineno"> 1254</span> }</div><div class="line"><a name="l01255"></a><span class="lineno"> 1255</span> </div><div class="line"><a name="l01256"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#adbdc0563cc7d8b6c1e3c2fb6f13871bf"> 1256</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#adbdc0563cc7d8b6c1e3c2fb6f13871bf">IWorkloadFactory::CreateLogSoftmax</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_log_softmax_queue_descriptor.xhtml">LogSoftmaxQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01258"></a><span class="lineno"> 1258</span> <span class="keyword"></span>{</div><div class="line"><a name="l01259"></a><span class="lineno"> 1259</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01260"></a><span class="lineno"> 1260</span> }</div><div class="line"><a name="l01261"></a><span class="lineno"> 1261</span> </div><div class="line"><a name="l01262"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#ab6bd7aaf685d4e956d780f8655a6f174"> 1262</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ab6bd7aaf685d4e956d780f8655a6f174">IWorkloadFactory::CreateLstm</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_lstm_queue_descriptor.xhtml">LstmQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01264"></a><span class="lineno"> 1264</span> <span class="keyword"></span>{</div><div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01266"></a><span class="lineno"> 1266</span> }</div><div class="line"><a name="l01267"></a><span class="lineno"> 1267</span> </div><div class="line"><a name="l01268"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a3fe27b35296a25984ab97319fd9a13d6"> 1268</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a3fe27b35296a25984ab97319fd9a13d6">IWorkloadFactory::CreateMaximum</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_maximum_queue_descriptor.xhtml">MaximumQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01269"></a><span class="lineno"> 1269</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01270"></a><span class="lineno"> 1270</span> <span class="keyword"></span>{</div><div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01272"></a><span class="lineno"> 1272</span> }</div><div class="line"><a name="l01273"></a><span class="lineno"> 1273</span> </div><div class="line"><a name="l01274"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#ac63f8f12f80efbe37b789d1540649470"> 1274</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac63f8f12f80efbe37b789d1540649470">IWorkloadFactory::CreateMean</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_mean_queue_descriptor.xhtml">MeanQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01275"></a><span class="lineno"> 1275</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*Info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01276"></a><span class="lineno"> 1276</span> <span class="keyword"></span>{</div><div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a87bf54bcdc865fd5d4f86194b3899d09"> 1280</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a87bf54bcdc865fd5d4f86194b3899d09">IWorkloadFactory::CreateMemCopy</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_mem_copy_queue_descriptor.xhtml">MemCopyQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01282"></a><span class="lineno"> 1282</span> <span class="keyword"></span>{</div><div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01284"></a><span class="lineno"> 1284</span> }</div><div class="line"><a name="l01285"></a><span class="lineno"> 1285</span> </div><div class="line"><a name="l01286"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#af0c99a5e2a6e4a67fec8b8c5906a3552"> 1286</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#af0c99a5e2a6e4a67fec8b8c5906a3552">IWorkloadFactory::CreateMemImport</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_mem_import_queue_descriptor.xhtml">MemImportQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01287"></a><span class="lineno"> 1287</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01288"></a><span class="lineno"> 1288</span> <span class="keyword"></span>{</div><div class="line"><a name="l01289"></a><span class="lineno"> 1289</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01292"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#acc3239cb7dd9434551a70d8534387069"> 1292</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#acc3239cb7dd9434551a70d8534387069">IWorkloadFactory::CreateMerge</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_merge_queue_descriptor.xhtml">MergeQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01293"></a><span class="lineno"> 1293</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01294"></a><span class="lineno"> 1294</span> <span class="keyword"></span>{</div><div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01296"></a><span class="lineno"> 1296</span> }</div><div class="line"><a name="l01297"></a><span class="lineno"> 1297</span> </div><div class="line"><a name="l01298"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#addb710d76098d55ad2f56117b73a9f48"> 1298</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#addb710d76098d55ad2f56117b73a9f48">IWorkloadFactory::CreateMerger</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_concat_queue_descriptor.xhtml">MergerQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01299"></a><span class="lineno"> 1299</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01300"></a><span class="lineno"> 1300</span> <span class="keyword"></span>{</div><div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a8851ca32bea910cf9376d05527e3dbef"> 1304</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a8851ca32bea910cf9376d05527e3dbef">IWorkloadFactory::CreateMinimum</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_minimum_queue_descriptor.xhtml">MinimumQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01306"></a><span class="lineno"> 1306</span> <span class="keyword"></span>{</div><div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01308"></a><span class="lineno"> 1308</span> }</div><div class="line"><a name="l01309"></a><span class="lineno"> 1309</span> </div><div class="line"><a name="l01310"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a756955d7436dd8f6e63cdf6367eb1694"> 1310</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a756955d7436dd8f6e63cdf6367eb1694">IWorkloadFactory::CreateMultiplication</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">MultiplicationQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01311"></a><span class="lineno"> 1311</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01312"></a><span class="lineno"> 1312</span> <span class="keyword"></span>{</div><div class="line"><a name="l01313"></a><span class="lineno"> 1313</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a185c215631e1b01a6d41232410de4c46"> 1316</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a185c215631e1b01a6d41232410de4c46">IWorkloadFactory::CreateNormalization</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_normalization_queue_descriptor.xhtml">NormalizationQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01318"></a><span class="lineno"> 1318</span> <span class="keyword"></span>{</div><div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01320"></a><span class="lineno"> 1320</span> }</div><div class="line"><a name="l01321"></a><span class="lineno"> 1321</span> </div><div class="line"><a name="l01322"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#adb279112eb265e5531c4ac2194b6c898"> 1322</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#adb279112eb265e5531c4ac2194b6c898">IWorkloadFactory::CreateOutput</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_mem_copy_queue_descriptor.xhtml">OutputQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01323"></a><span class="lineno"> 1323</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01324"></a><span class="lineno"> 1324</span> <span class="keyword"></span>{</div><div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01328"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#ab0c956e4a638d0a2777ecb71953f7e27"> 1328</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ab0c956e4a638d0a2777ecb71953f7e27">IWorkloadFactory::CreatePad</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_pad_queue_descriptor.xhtml">PadQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*Info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01330"></a><span class="lineno"> 1330</span> <span class="keyword"></span>{</div><div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01334"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a2dcee0bc4bbae1f745324aed0f841a0a"> 1334</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a2dcee0bc4bbae1f745324aed0f841a0a">IWorkloadFactory::CreatePermute</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_permute_queue_descriptor.xhtml">PermuteQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01336"></a><span class="lineno"> 1336</span> <span class="keyword"></span>{</div><div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01338"></a><span class="lineno"> 1338</span> }</div><div class="line"><a name="l01339"></a><span class="lineno"> 1339</span> </div><div class="line"><a name="l01340"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a6e95afd9a55700cbf6f9e8db8089f2f2"> 1340</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a6e95afd9a55700cbf6f9e8db8089f2f2">IWorkloadFactory::CreatePooling2d</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_pooling2d_queue_descriptor.xhtml">Pooling2dQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01342"></a><span class="lineno"> 1342</span> <span class="keyword"></span>{</div><div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01346"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a012306477c38a533edd29c422227cd8c"> 1346</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a012306477c38a533edd29c422227cd8c">IWorkloadFactory::CreatePreCompiled</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_pre_compiled_queue_descriptor.xhtml">PreCompiledQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01348"></a><span class="lineno"> 1348</span> <span class="keyword"></span>{</div><div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01350"></a><span class="lineno"> 1350</span> }</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span> </div><div class="line"><a name="l01352"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#adf4a93f605e4e7dad6aee0b4d2159171"> 1352</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#adf4a93f605e4e7dad6aee0b4d2159171">IWorkloadFactory::CreatePrelu</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_prelu_queue_descriptor.xhtml">PreluQueueDescriptor</a> &<span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a> &<span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01354"></a><span class="lineno"> 1354</span> <span class="keyword"></span>{</div><div class="line"><a name="l01355"></a><span class="lineno"> 1355</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01356"></a><span class="lineno"> 1356</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"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a1942c254ba89d17803e5a636aa927d90"> 1358</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a1942c254ba89d17803e5a636aa927d90">IWorkloadFactory::CreateQuantize</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_quantize_queue_descriptor.xhtml">QuantizeQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*Info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01360"></a><span class="lineno"> 1360</span> <span class="keyword"></span>{</div><div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01364"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#ab5ceda49651dcd53fb7eb05658b5a0cb"> 1364</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ab5ceda49651dcd53fb7eb05658b5a0cb">IWorkloadFactory::CreateQuantizedLstm</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml">QuantizedLstmQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01366"></a><span class="lineno"> 1366</span> <span class="keyword"></span>{</div><div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01370"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a4f9d9c79a100a0d057027d8524373962"> 1370</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a4f9d9c79a100a0d057027d8524373962">IWorkloadFactory::CreateReshape</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_reshape_queue_descriptor.xhtml">ReshapeQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01372"></a><span class="lineno"> 1372</span> <span class="keyword"></span>{</div><div class="line"><a name="l01373"></a><span class="lineno"> 1373</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01374"></a><span class="lineno"> 1374</span> }</div><div class="line"><a name="l01375"></a><span class="lineno"> 1375</span> </div><div class="line"><a name="l01376"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a7eb321c47cd90d2cc3823e74596f1239"> 1376</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a7eb321c47cd90d2cc3823e74596f1239">IWorkloadFactory::CreateResizeBilinear</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_resize_bilinear_queue_descriptor.xhtml">ResizeBilinearQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01378"></a><span class="lineno"> 1378</span> <span class="keyword"></span>{</div><div class="line"><a name="l01379"></a><span class="lineno"> 1379</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01380"></a><span class="lineno"> 1380</span> }</div><div class="line"><a name="l01381"></a><span class="lineno"> 1381</span> </div><div class="line"><a name="l01382"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a84377c94a59c589dbf419f838c4b9119"> 1382</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a84377c94a59c589dbf419f838c4b9119">IWorkloadFactory::CreateResize</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_resize_queue_descriptor.xhtml">ResizeQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01384"></a><span class="lineno"> 1384</span> <span class="keyword"></span>{</div><div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a2459b9d4f72d78eab86f9ec09384c491"> 1388</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a2459b9d4f72d78eab86f9ec09384c491">IWorkloadFactory::CreateRsqrt</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_rsqrt_queue_descriptor.xhtml">RsqrtQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01389"></a><span class="lineno"> 1389</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</span> <span class="keyword"></span>{</div><div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01394"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a86658e2fc02a32acd4de20ef92242347"> 1394</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a86658e2fc02a32acd4de20ef92242347">IWorkloadFactory::CreateSlice</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_slice_queue_descriptor.xhtml">SliceQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01396"></a><span class="lineno"> 1396</span> <span class="keyword"></span>{</div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01398"></a><span class="lineno"> 1398</span> }</div><div class="line"><a name="l01399"></a><span class="lineno"> 1399</span> </div><div class="line"><a name="l01400"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a8a843d44d2e81df87e414df3b3e688de"> 1400</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a8a843d44d2e81df87e414df3b3e688de">IWorkloadFactory::CreateSoftmax</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_softmax_queue_descriptor.xhtml">SoftmaxQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01402"></a><span class="lineno"> 1402</span> <span class="keyword"></span>{</div><div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01404"></a><span class="lineno"> 1404</span> }</div><div class="line"><a name="l01405"></a><span class="lineno"> 1405</span> </div><div class="line"><a name="l01406"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#ac306abe0073a04300f2d96d0b5eb6218"> 1406</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac306abe0073a04300f2d96d0b5eb6218">IWorkloadFactory::CreateSplitter</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_splitter_queue_descriptor.xhtml">SplitterQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01408"></a><span class="lineno"> 1408</span> <span class="keyword"></span>{</div><div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01412"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a44e7aebc021646becc3f32722e22553e"> 1412</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a44e7aebc021646becc3f32722e22553e">IWorkloadFactory::CreateSpaceToBatchNd</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_space_to_batch_nd_queue_descriptor.xhtml">SpaceToBatchNdQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span> <span class="keyword"></span>{</div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01418"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a9bdc3801e1e964046730d49c0e11d1ce"> 1418</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a9bdc3801e1e964046730d49c0e11d1ce">IWorkloadFactory::CreateSpaceToDepth</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_space_to_depth_queue_descriptor.xhtml">SpaceToDepthQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01420"></a><span class="lineno"> 1420</span> <span class="keyword"></span>{</div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</span> }</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span> </div><div class="line"><a name="l01424"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#aa06423ce3f34e4ec2d336889f8c0d79a"> 1424</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#aa06423ce3f34e4ec2d336889f8c0d79a">IWorkloadFactory::CreateStack</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_stack_queue_descriptor.xhtml">StackQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span> <span class="keyword"></span>{</div><div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a21344e9f338e1d4c3d26825002a02754"> 1430</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a21344e9f338e1d4c3d26825002a02754">IWorkloadFactory::CreateStridedSlice</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_strided_slice_queue_descriptor.xhtml">StridedSliceQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01432"></a><span class="lineno"> 1432</span> <span class="keyword"></span>{</div><div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01434"></a><span class="lineno"> 1434</span> }</div><div class="line"><a name="l01435"></a><span class="lineno"> 1435</span> </div><div class="line"><a name="l01436"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a439305cf0a71fc85a0b93cc063100f91"> 1436</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a439305cf0a71fc85a0b93cc063100f91">IWorkloadFactory::CreateSubtraction</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">SubtractionQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01438"></a><span class="lineno"> 1438</span> <span class="keyword"></span>{</div><div class="line"><a name="l01439"></a><span class="lineno"> 1439</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01440"></a><span class="lineno"> 1440</span> }</div><div class="line"><a name="l01441"></a><span class="lineno"> 1441</span> </div><div class="line"><a name="l01442"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#ab37f39b9e3e224ccde6b36adc876bb19"> 1442</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ab37f39b9e3e224ccde6b36adc876bb19">IWorkloadFactory::CreateSwitch</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_switch_queue_descriptor.xhtml">SwitchQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01444"></a><span class="lineno"> 1444</span> <span class="keyword"></span>{</div><div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</div><div class="line"><a name="l01446"></a><span class="lineno"> 1446</span> }</div><div class="line"><a name="l01447"></a><span class="lineno"> 1447</span> </div><div class="line"><a name="l01448"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a96217a8bbb66811608ce729fd49a3dd2"> 1448</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a96217a8bbb66811608ce729fd49a3dd2">IWorkloadFactory::CreateTranspose</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_transpose_queue_descriptor.xhtml">TransposeQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01450"></a><span class="lineno"> 1450</span> <span class="keyword"></span>{</div><div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01454"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_workload_factory.xhtml#a12cccba82124cc4993868a3173a65167"> 1454</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a12cccba82124cc4993868a3173a65167">IWorkloadFactory::CreateTransposeConvolution2d</a>(</div><div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_transpose_convolution2d_queue_descriptor.xhtml">TransposeConvolution2dQueueDescriptor</a>& <span class="comment">/*descriptor*/</span>,</div><div class="line"><a name="l01456"></a><span class="lineno"> 1456</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& <span class="comment">/*info*/</span>)<span class="keyword"> const</span></div><div class="line"><a name="l01457"></a><span class="lineno"> 1457</span> <span class="keyword"></span>{</div><div class="line"><a name="l01458"></a><span class="lineno"> 1458</span>  <span class="keywordflow">return</span> std::unique_ptr<IWorkload>();</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> </div><div class="line"><a name="l01461"></a><span class="lineno"> 1461</span> } <span class="comment">// namepsace armnn</span></div><div class="ttc" id="structarmnn_1_1_multiplication_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">armnn::MultiplicationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00222">WorkloadData.hpp:222</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a71b23d26c0f5d20416d6c77754f9806a"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a71b23d26c0f5d20416d6c77754f9806a">armnn::LayerType::TransposeConvolution2d</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4abcd30d7ea97ad20c2cddc0f47e6b70c7"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4abcd30d7ea97ad20c2cddc0f47e6b70c7">armnn::LayerType::ElementwiseUnary</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ac306abe0073a04300f2d96d0b5eb6218"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ac306abe0073a04300f2d96d0b5eb6218">armnn::IWorkloadFactory::CreateSplitter</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateSplitter(const SplitterQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01406">WorkloadFactory.cpp:1406</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_queue_descriptor.xhtml">armnn::InstanceNormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00311">WorkloadData.hpp:311</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_abe1e0d40e23195022c0bc10a8aab55ea"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#abe1e0d40e23195022c0bc10a8aab55ea">armnn::IWorkloadFactory::CreateBatchNormalization</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateBatchNormalization(const BatchNormalizationQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01117">WorkloadFactory.cpp:1117</a></div></div> +<div class="ttc" id="structarmnn_1_1_permute_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_permute_queue_descriptor.xhtml">armnn::PermuteQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00156">WorkloadData.hpp:156</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a00346a3754d9411bba2e29dc1f996ac6"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a00346a3754d9411bba2e29dc1f996ac6">armnn::IWorkloadFactory::CreateDebug</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateDebug(const DebugQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01165">WorkloadFactory.cpp:1165</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a87bf54bcdc865fd5d4f86194b3899d09"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a87bf54bcdc865fd5d4f86194b3899d09">armnn::IWorkloadFactory::CreateMemCopy</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateMemCopy(const MemCopyQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01280">WorkloadFactory.cpp:1280</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a3c86f886e36ce943f1ebc241a37f0413"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a3c86f886e36ce943f1ebc241a37f0413">armnn::IWorkloadFactory::CreateL2Normalization</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateL2Normalization(const L2NormalizationQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01250">WorkloadFactory.cpp:1250</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4ae20f0f2826a6549809f050b86274567f"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ae20f0f2826a6549809f050b86274567f">armnn::LayerType::Concat</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantize_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_quantize_queue_descriptor.xhtml">armnn::QuantizeQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00257">WorkloadData.hpp:257</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00061">INetwork.hpp:61</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_af00ce13ef7dabd17cc4186d0a4991757"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#af00ce13ef7dabd17cc4186d0a4991757">armnn::IWorkloadFactory::CreateBatchToSpaceNd</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateBatchToSpaceNd(const BatchToSpaceNdQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01123">WorkloadFactory.cpp:1123</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a756955d7436dd8f6e63cdf6367eb1694"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a756955d7436dd8f6e63cdf6367eb1694">armnn::IWorkloadFactory::CreateMultiplication</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateMultiplication(const MultiplicationQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01310">WorkloadFactory.cpp:1310</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4af6c0e3a1c3cfabd32ae8d3ae741fcf0a"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4af6c0e3a1c3cfabd32ae8d3ae741fcf0a">armnn::LayerType::Comparison</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01079">Descriptors.hpp:1079</a></div></div> +<div class="ttc" id="structarmnn_1_1_maximum_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_maximum_queue_descriptor.xhtml">armnn::MaximumQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00240">WorkloadData.hpp:240</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_queue_descriptor.xhtml">armnn::DetectionPostProcessQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00197">WorkloadData.hpp:197</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a96a3123d8a8290b01582d955cdcd75d5"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a96a3123d8a8290b01582d955cdcd75d5">armnn::IWorkloadFactory::CreateInstanceNormalization</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateInstanceNormalization(const InstanceNormalizationQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01243">WorkloadFactory.cpp:1243</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a4e779d1b00a9e885497364ebd0dc24ef"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a4e779d1b00a9e885497364ebd0dc24ef">armnn::IWorkloadFactory::CreateGreater</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateGreater(const GreaterQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01237">WorkloadFactory.cpp:1237</a></div></div> +<div class="ttc" id="structarmnn_1_1_gather_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_gather_queue_descriptor.xhtml">armnn::GatherQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00457">WorkloadData.hpp:457</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_workload_factory_xhtml_ac47803c9faacfb7c10219253b99f61ca"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ac47803c9faacfb7c10219253b99f61ca">armnn::IWorkloadFactory::CreateArgMinMax</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateArgMinMax(const ArgMinMaxQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01111">WorkloadFactory.cpp:1111</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_addb710d76098d55ad2f56117b73a9f48"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#addb710d76098d55ad2f56117b73a9f48">armnn::IWorkloadFactory::CreateMerger</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateMerger(const MergerQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01298">WorkloadFactory.cpp:1298</a></div></div> +<div class="ttc" id="structarmnn_1_1_splitter_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_splitter_queue_descriptor.xhtml">armnn::SplitterQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00083">WorkloadData.hpp:83</a></div></div> +<div class="ttc" id="structarmnn_1_1_constant_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_constant_queue_descriptor.xhtml">armnn::ConstantQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00326">WorkloadData.hpp:326</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3"><div class="ttname"><a href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml">armnn::QuantizedLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00512">WorkloadData.hpp:512</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_adbdc0563cc7d8b6c1e3c2fb6f13871bf"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#adbdc0563cc7d8b6c1e3c2fb6f13871bf">armnn::IWorkloadFactory::CreateLogSoftmax</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateLogSoftmax(const LogSoftmaxQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01256">WorkloadFactory.cpp:1256</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a7eb321c47cd90d2cc3823e74596f1239"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a7eb321c47cd90d2cc3823e74596f1239">armnn::IWorkloadFactory::CreateResizeBilinear</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateResizeBilinear(const ResizeBilinearQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01376">WorkloadFactory.cpp:1376</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a6ee06c6045d0c5b6565a247955ef0fc2"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a6ee06c6045d0c5b6565a247955ef0fc2">armnn::LayerType::BatchToSpaceNd</a></div></div> +<div class="ttc" id="_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_workload_factory_8hpp.xhtml">WorkloadFactory.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="_workload_test_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_test_utils_8hpp.xhtml">WorkloadTestUtils.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a21344e9f338e1d4c3d26825002a02754"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a21344e9f338e1d4c3d26825002a02754">armnn::IWorkloadFactory::CreateStridedSlice</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateStridedSlice(const StridedSliceQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01430">WorkloadFactory.cpp:1430</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00392">Descriptors.hpp:392</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a2187e1021a911b3807cc1bea2eb1a9ca"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a2187e1021a911b3807cc1bea2eb1a9ca">armnn::LayerType::Stack</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_aa06423ce3f34e4ec2d336889f8c0d79a"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#aa06423ce3f34e4ec2d336889f8c0d79a">armnn::IWorkloadFactory::CreateStack</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateStack(const StackQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01424">WorkloadFactory.cpp:1424</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4aa31904f2b3479b5a00137fd985974b4d"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aa31904f2b3479b5a00137fd985974b4d">armnn::LayerType::StridedSlice</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ab6bd7aaf685d4e956d780f8655a6f174"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ab6bd7aaf685d4e956d780f8655a6f174">armnn::IWorkloadFactory::CreateLstm</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateLstm(const LstmQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01262">WorkloadFactory.cpp:1262</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4aa9a62e70841c4d06dd16306a85700d36"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aa9a62e70841c4d06dd16306a85700d36">armnn::LayerType::Activation</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_quantized_lstm_input_params_info_xhtml_a21626d0b91f8942c3ef8e48e17db9f21"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a21626d0b91f8942c3ef8e48e17db9f21">armnn::QuantizedLstmInputParamsInfo::m_ForgetGateBias</a></div><div class="ttdeci">const TensorInfo * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00150">QuantizedLstmParams.hpp:150</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a42581f3d1c22e64b7f3676ea20acab0e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a42581f3d1c22e64b7f3676ea20acab0e">armnn::IWorkloadFactory::CreateFakeQuantization</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateFakeQuantization(const FakeQuantizationQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01213">WorkloadFactory.cpp:1213</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ab5ceda49651dcd53fb7eb05658b5a0cb"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ab5ceda49651dcd53fb7eb05658b5a0cb">armnn::IWorkloadFactory::CreateQuantizedLstm</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateQuantizedLstm(const QuantizedLstmQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01364">WorkloadFactory.cpp:1364</a></div></div> +<div class="ttc" id="structarmnn_1_1_stack_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stack_queue_descriptor.xhtml">armnn::StackQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00124">WorkloadData.hpp:124</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a963bd7acce29a83d96daeb2cea34f2f7"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a963bd7acce29a83d96daeb2cea34f2f7">armnn::IWorkloadFactory::CreateConstant</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateConstant(const ConstantQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01141">WorkloadFactory.cpp:1141</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4addf4f83b056acd5549949fc0350e9aad">armnn::LayerType::ConvertFp32ToFp16</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_af434b509cd5232ef762c4b21b2dfaae0"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#af434b509cd5232ef762c4b21b2dfaae0">armnn::QuantizedLstmInputParamsInfo::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const TensorInfo * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00147">QuantizedLstmParams.hpp:147</a></div></div> +<div class="ttc" id="structarmnn_1_1_rsqrt_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_rsqrt_queue_descriptor.xhtml">armnn::RsqrtQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00452">WorkloadData.hpp:452</a></div></div> +<div class="ttc" id="structarmnn_1_1_merge_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_merge_queue_descriptor.xhtml">armnn::MergeQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00479">WorkloadData.hpp:479</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f">armnn::LayerType::Normalization</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a337c392144dca0d18290c6b4711a2279"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a337c392144dca0d18290c6b4711a2279">armnn::LayerType::SpaceToBatchNd</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e">armnn::LayerType::FullyConnected</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_a042ea9d6d3842b87f112db126e806a93"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a042ea9d6d3842b87f112db126e806a93">armnn::QuantizedLstmInputParamsInfo::m_InputGateBias</a></div><div class="ttdeci">const TensorInfo * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00149">QuantizedLstmParams.hpp:149</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a12d2c4e0f0b0d6b36d8a3e14bf69f9e4"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a12d2c4e0f0b0d6b36d8a3e14bf69f9e4">armnn::IWorkloadFactory::CreateElementwiseUnary</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateElementwiseUnary(const ElementwiseUnaryQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01201">WorkloadFactory.cpp:1201</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div> +<div class="ttc" id="structarmnn_1_1_addition_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00216">WorkloadData.hpp:216</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_slot_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_slot.xhtml">armnn::InputSlot</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00041">Layer.hpp:41</a></div></div> +<div class="ttc" id="structarmnn_1_1_minimum_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_minimum_queue_descriptor.xhtml">armnn::MinimumQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00431">WorkloadData.hpp:431</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_a11b90bd2694aa7f4b434aadd75fbb1c2"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a11b90bd2694aa7f4b434aadd75fbb1c2">armnn::QuantizedLstmInputParamsInfo::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const TensorInfo * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00145">QuantizedLstmParams.hpp:145</a></div></div> +<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_ada422a73ac4e68bcb1b1b1f0b44028d9"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#ada422a73ac4e68bcb1b1b1f0b44028d9">boxEncodings</a></div><div class="ttdeci">std::vector< float > boxEncodings({ 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, -1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f })</div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ae3ba329a833bbb63961eb64d6477d691"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ae3ba329a833bbb63961eb64d6477d691">armnn::IWorkloadFactory::CreateAbs</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateAbs(const AbsQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01093">WorkloadFactory.cpp:1093</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div> +<div class="ttc" id="structarmnn_1_1_fully_connected_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml">armnn::FullyConnectedQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00141">WorkloadData.hpp:141</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_af5f530544d09a44d726f24702b67b35b"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#af5f530544d09a44d726f24702b67b35b">armnn::Layer::GetInputSlots</a></div><div class="ttdeci">const std::vector< InputSlot > & GetInputSlots() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00231">Layer.hpp:231</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a4458d75c0db21c6abc941cd93a6a24c5"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5">armnn::IWorkloadFactory::CreateActivation</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateActivation(const ActivationQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01099">WorkloadFactory.cpp:1099</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a2459b9d4f72d78eab86f9ec09384c491"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a2459b9d4f72d78eab86f9ec09384c491">armnn::IWorkloadFactory::CreateRsqrt</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateRsqrt(const RsqrtQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01388">WorkloadFactory.cpp:1388</a></div></div> +<div class="ttc" id="structarmnn_1_1_prelu_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_prelu_queue_descriptor.xhtml">armnn::PreluQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00489">WorkloadData.hpp:489</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a27d1a1f7b7c2180e5b20ce9e3d00e2dd"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a27d1a1f7b7c2180e5b20ce9e3d00e2dd">armnn::LayerType::Multiplication</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a21baa4498161d195f5bb2e3627344ba4"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a21baa4498161d195f5bb2e3627344ba4">armnn::LayerType::InstanceNormalization</a></div></div> +<div class="ttc" id="structarmnn_1_1_equal_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_equal_queue_descriptor.xhtml">armnn::EqualQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00263">WorkloadData.hpp:263</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a96217a8bbb66811608ce729fd49a3dd2"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a96217a8bbb66811608ce729fd49a3dd2">armnn::IWorkloadFactory::CreateTranspose</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateTranspose(const TransposeQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01448">WorkloadFactory.cpp:1448</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_slot_xhtml_a3153abb7c0c0a84629079b2fac7db54f"><div class="ttname"><a href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">armnn::InputSlot::GetConnection</a></div><div class="ttdeci">const IOutputSlot * GetConnection() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00199">Layer.hpp:199</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_queue_descriptor.xhtml">armnn::BatchToSpaceNdQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00420">WorkloadData.hpp:420</a></div></div> +<div class="ttc" id="structarmnn_1_1_softmax_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_softmax_queue_descriptor.xhtml">armnn::SoftmaxQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00077">WorkloadData.hpp:77</a></div></div> +<div class="ttc" id="structarmnn_1_1_division_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_division_queue_descriptor.xhtml">armnn::DivisionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00228">WorkloadData.hpp:228</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a68be4837f6c739877233e527a996dd00"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a68be4837f6c739877233e527a996dd00">armnn::LayerType::Merge</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_a48cb83dcb58c786ea36f5d37695e75b1"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a48cb83dcb58c786ea36f5d37695e75b1">armnn::QuantizedLstmInputParamsInfo::m_OutputGateBias</a></div><div class="ttdeci">const TensorInfo * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00152">QuantizedLstmParams.hpp:152</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a20bb773c7fd6253418bdedac1312cd19"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a20bb773c7fd6253418bdedac1312cd19">armnn::IWorkloadFactory::CreateDivision</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateDivision(const DivisionQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01195">WorkloadFactory.cpp:1195</a></div></div> +<div class="ttc" id="structarmnn_1_1_subtraction_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">armnn::SubtractionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00234">WorkloadData.hpp:234</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a1189467870bc421ae59277e750263eb2"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1189467870bc421ae59277e750263eb2">armnn::LayerType::L2Normalization</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="structarmnn_1_1_pad_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pad_queue_descriptor.xhtml">armnn::PadQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00252">WorkloadData.hpp:252</a></div></div> +<div class="ttc" id="structarmnn_1_1_concat_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_concat_queue_descriptor.xhtml">armnn::ConcatQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00102">WorkloadData.hpp:102</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32">armnn::LayerType::Prelu</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a3fe27b35296a25984ab97319fd9a13d6"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a3fe27b35296a25984ab97319fd9a13d6">armnn::IWorkloadFactory::CreateMaximum</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateMaximum(const MaximumQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01268">WorkloadFactory.cpp:1268</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a32bb8d6cf5fc028bf501252767c08b21"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a32bb8d6cf5fc028bf501252767c08b21">armnn::IWorkloadFactory::CreateConcat</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateConcat(const ConcatQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01135">WorkloadFactory.cpp:1135</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_depth_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_queue_descriptor.xhtml">armnn::SpaceToDepthQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00348">WorkloadData.hpp:348</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4aca39930e22f40d10155a57dba32240bb"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aca39930e22f40d10155a57dba32240bb">armnn::LayerType::Quantize</a></div></div> +<div class="ttc" id="structarmnn_1_1_abs_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_abs_queue_descriptor.xhtml">armnn::AbsQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00549">WorkloadData.hpp:549</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_resize_queue_descriptor.xhtml">armnn::ResizeQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00292">WorkloadData.hpp:292</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_acc3239cb7dd9434551a70d8534387069"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#acc3239cb7dd9434551a70d8534387069">armnn::IWorkloadFactory::CreateMerge</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateMerge(const MergeQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01292">WorkloadFactory.cpp:1292</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_queue_descriptor.xhtml">armnn::SpaceToBatchNdQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00343">WorkloadData.hpp:343</a></div></div> +<div class="ttc" id="structarmnn_1_1_floor_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_floor_queue_descriptor.xhtml">armnn::FloorQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00353">WorkloadData.hpp:353</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a83c4a275acf59f62b8387f389d0929d5"><div class="ttname"><a href="namespacearmnn.xhtml#a83c4a275acf59f62b8387f389d0929d5">armnn::GetBiasTypeFromWeightsType</a></div><div class="ttdeci">armnn::Optional< armnn::DataType > GetBiasTypeFromWeightsType(armnn::Optional< armnn::DataType > weightsType)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_support_rules_8hpp_source.xhtml#l00014">LayerSupportRules.hpp:14</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="structarmnn_1_1_lstm_input_params_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params_info.xhtml">armnn::LstmInputParamsInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00063">LstmParams.hpp:63</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_a33242cb43250f04f1736161ca8ad2db9"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a33242cb43250f04f1736161ca8ad2db9">armnn::QuantizedLstmInputParamsInfo::m_InputToOutputWeights</a></div><div class="ttdeci">const TensorInfo * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00142">QuantizedLstmParams.hpp:142</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a6eb8b8b560161603402c0238b3a7d8b0"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a6eb8b8b560161603402c0238b3a7d8b0">armnn::LayerType::Subtraction</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a096bb62d44fadf079ea4463379d4e6aa"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a096bb62d44fadf079ea4463379d4e6aa">armnn::IWorkloadFactory::CreateEqual</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateEqual(const EqualQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01207">WorkloadFactory.cpp:1207</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ad0da07faa15302377aa97be89c57677c"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ad0da07faa15302377aa97be89c57677c">armnn::IWorkloadFactory::CreateDetectionPostProcess</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateDetectionPostProcess(const DetectionPostProcessQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01189">WorkloadFactory.cpp:1189</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1db19222ac424bd7162142ddf929fd2a">armnn::LayerType::DetectionPostProcess</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_bilinear_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_resize_bilinear_queue_descriptor.xhtml">armnn::ResizeBilinearQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00287">WorkloadData.hpp:287</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="classarmnn_1_1_i_workload_factory_xhtml_a44e7aebc021646becc3f32722e22553e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a44e7aebc021646becc3f32722e22553e">armnn::IWorkloadFactory::CreateSpaceToBatchNd</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateSpaceToBatchNd(const SpaceToBatchNdQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01412">WorkloadFactory.cpp:1412</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml">armnn::LstmDescriptor</a></div><div class="ttdoc">An LstmDescriptor for the LstmLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00837">Descriptors.hpp:837</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a84377c94a59c589dbf419f838c4b9119"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a84377c94a59c589dbf419f838c4b9119">armnn::IWorkloadFactory::CreateResize</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateResize(const ResizeQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01382">WorkloadFactory.cpp:1382</a></div></div> +<div class="ttc" id="structarmnn_1_1_fake_quantization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fake_quantization_queue_descriptor.xhtml">armnn::FakeQuantizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00297">WorkloadData.hpp:297</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml">armnn::QuantizedLstmInputParamsInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00119">QuantizedLstmParams.hpp:119</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_queue_descriptor.xhtml">armnn::LstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00358">WorkloadData.hpp:358</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a3d6c9ac08ada31c184094bbc67afe00d"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a3d6c9ac08ada31c184094bbc67afe00d">armnn::LayerType::Mean</a></div></div> +<div class="ttc" id="structarmnn_1_1_greater_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_greater_queue_descriptor.xhtml">armnn::GreaterQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00436">WorkloadData.hpp:436</a></div></div> +<div class="ttc" id="structarmnn_1_1_l2_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.xhtml">armnn::L2NormalizationDescriptor</a></div><div class="ttdoc">A L2NormalizationDescriptor for the L2NormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00591">Descriptors.hpp:591</a></div></div> +<div class="ttc" id="structarmnn_1_1_arg_min_max_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a></div><div class="ttdoc">An ArgMinMaxDescriptor for ArgMinMaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00043">Descriptors.hpp:43</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a1942c254ba89d17803e5a636aa927d90"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a1942c254ba89d17803e5a636aa927d90">armnn::IWorkloadFactory::CreateQuantize</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateQuantize(const QuantizeQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01358">WorkloadFactory.cpp:1358</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="_types_8hpp_xhtml"><div class="ttname"><a href="_types_8hpp.xhtml">Types.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml">armnn::FullyConnectedDescriptor</a></div><div class="ttdoc">A FullyConnectedDescriptor for the FullyConnectedLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00373">Descriptors.hpp:373</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4aad22c799930d644e8468fe44c0312d53"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aad22c799930d644e8468fe44c0312d53">armnn::LayerType::Gather</a></div></div> +<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::FullyConnectedDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00386">Descriptors.hpp:386</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_input_params_info_xhtml_a4b3f6e6f2268416ffd7a34fda95ffd0b"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params_info.xhtml#a4b3f6e6f2268416ffd7a34fda95ffd0b">armnn::LstmInputParamsInfo::m_InputToForgetWeights</a></div><div class="ttdeci">const TensorInfo * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00090">LstmParams.hpp:90</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a9d723d04c40bfd81835c0766a698cf63"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a9d723d04c40bfd81835c0766a698cf63">armnn::LayerType::Resize</a></div></div> +<div class="ttc" id="structarmnn_1_1_comparison_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_comparison_queue_descriptor.xhtml">armnn::ComparisonQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00564">WorkloadData.hpp:564</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a93a3ba385cad27c4774e5fe64c025d3daa603905470e2a5b8c13e96b579ef0dba"><div class="ttname"><a href="namespacearmnn.xhtml#a93a3ba385cad27c4774e5fe64c025d3daa603905470e2a5b8c13e96b579ef0dba">armnn::LogSeverity::Debug</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="classarmnn_1_1_i_workload_factory_xhtml_ab37f39b9e3e224ccde6b36adc876bb19"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ab37f39b9e3e224ccde6b36adc876bb19">armnn::IWorkloadFactory::CreateSwitch</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateSwitch(const SwitchQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01442">WorkloadFactory.cpp:1442</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_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ab0c956e4a638d0a2777ecb71953f7e27"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ab0c956e4a638d0a2777ecb71953f7e27">armnn::IWorkloadFactory::CreatePad</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreatePad(const PadQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01328">WorkloadFactory.cpp:1328</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4ade43468adaf6acb2c38ebc0c1176f82f"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ade43468adaf6acb2c38ebc0c1176f82f">armnn::LayerType::Pad</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a8321e79c278ec510f63675c040594892"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a8321e79c278ec510f63675c040594892">armnn::LayerType::Maximum</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_a9ab864961ded72f5ce7ea4eb9921f826"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a9ab864961ded72f5ce7ea4eb9921f826">armnn::QuantizedLstmInputParamsInfo::m_RecurrentToInputWeights</a></div><div class="ttdeci">const TensorInfo * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00144">QuantizedLstmParams.hpp:144</a></div></div> +<div class="ttc" id="structarmnn_1_1_convert_fp16_to_fp32_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convert_fp16_to_fp32_queue_descriptor.xhtml">armnn::ConvertFp16ToFp32QueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00410">WorkloadData.hpp:410</a></div></div> +<div class="ttc" id="_i_layer_support_8hpp_xhtml"><div class="ttname"><a href="_i_layer_support_8hpp.xhtml">ILayerSupport.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a1ba143ebe524d46181a4b53470693278"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a1ba143ebe524d46181a4b53470693278">armnn::LayerType::PreCompiled</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4aa7c59ccedc6a3bd90c17f3b990afefad"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aa7c59ccedc6a3bd90c17f3b990afefad">armnn::LayerType::Reshape</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4ad662867a41bfb30b9f75dda2b5849001"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ad662867a41bfb30b9f75dda2b5849001">armnn::LayerType::Pooling2d</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a74dc9ec1a223eab8b072368b2dacee87"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a74dc9ec1a223eab8b072368b2dacee87">armnn::IWorkloadFactory::IsLayerSupported</a></div><div class="ttdeci">static bool IsLayerSupported(const BackendId &backendId, const IConnectableLayer &layer, Optional< DataType > dataType, std::string &outReasonIfUnsupported)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l00045">WorkloadFactory.cpp:45</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a185c215631e1b01a6d41232410de4c46"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a185c215631e1b01a6d41232410de4c46">armnn::IWorkloadFactory::CreateNormalization</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateNormalization(const NormalizationQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01316">WorkloadFactory.cpp:1316</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a9bc35e069257a508e14ed82965a8661d"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a9bc35e069257a508e14ed82965a8661d">armnn::LayerType::Dequantize</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">armnn::LayerType::Addition</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="classarmnn_1_1_i_workload_factory_xhtml_a4f9d9c79a100a0d057027d8524373962"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a4f9d9c79a100a0d057027d8524373962">armnn::IWorkloadFactory::CreateReshape</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateReshape(const ReshapeQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01370">WorkloadFactory.cpp:1370</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a2dcee0bc4bbae1f745324aed0f841a0a"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a2dcee0bc4bbae1f745324aed0f841a0a">armnn::IWorkloadFactory::CreatePermute</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreatePermute(const PermuteQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01334">WorkloadFactory.cpp:1334</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a3fa12033e9be37c529ac54a83ab43b36"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a3fa12033e9be37c529ac54a83ab43b36">armnn::IWorkloadFactory::CreateComparison</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateComparison(const ComparisonQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01129">WorkloadFactory.cpp:1129</a></div></div> +<div class="ttc" id="structarmnn_1_1_convert_fp32_to_fp16_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convert_fp32_to_fp16_queue_descriptor.xhtml">armnn::ConvertFp32ToFp16QueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00415">WorkloadData.hpp:415</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a98cdff4e0b45f4c80bfcedaf926e16e0"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a98cdff4e0b45f4c80bfcedaf926e16e0">armnn::Layer::GetOutputSlots</a></div><div class="ttdeci">const std::vector< OutputSlot > & GetOutputSlots() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00232">Layer.hpp:232</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a5e7ff12da912dc79e7e547281823fa4a"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a5e7ff12da912dc79e7e547281823fa4a">armnn::LayerType::SpaceToDepth</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4af97adbfc88b7012a0243215b1076e7e7"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4af97adbfc88b7012a0243215b1076e7e7">armnn::LayerType::DepthwiseConvolution2d</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a6e95afd9a55700cbf6f9e8db8089f2f2"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a6e95afd9a55700cbf6f9e8db8089f2f2">armnn::IWorkloadFactory::CreatePooling2d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreatePooling2d(const Pooling2dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01340">WorkloadFactory.cpp:1340</a></div></div> +<div class="ttc" id="_cpu_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.xhtml">CpuTensorHandle.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_queue_descriptor.xhtml">armnn::TransposeConvolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00494">WorkloadData.hpp:494</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">armnn::Convolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00168">WorkloadData.hpp:168</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a9bdc3801e1e964046730d49c0e11d1ce"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a9bdc3801e1e964046730d49c0e11d1ce">armnn::IWorkloadFactory::CreateSpaceToDepth</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateSpaceToDepth(const SpaceToDepthQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01418">WorkloadFactory.cpp:1418</a></div></div> +<div class="ttc" id="structarmnn_1_1_mem_copy_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mem_copy_queue_descriptor.xhtml">armnn::MemCopyQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00058">WorkloadData.hpp:58</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="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_a4b3f6e6f2268416ffd7a34fda95ffd0b"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a4b3f6e6f2268416ffd7a34fda95ffd0b">armnn::QuantizedLstmInputParamsInfo::m_InputToForgetWeights</a></div><div class="ttdeci">const TensorInfo * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00140">QuantizedLstmParams.hpp:140</a></div></div> +<div class="ttc" id="structarmnn_1_1_slice_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_slice_queue_descriptor.xhtml">armnn::SliceQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00554">WorkloadData.hpp:554</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a93bca63ecbb003649425dd0e4ba79a99"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a93bca63ecbb003649425dd0e4ba79a99">armnn::LayerType::StandIn</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a115bfc5d633eae55c67f9588acdd2bf9">armnn::LayerType::MemImport</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_a6c7873a3320a59a63aa26c006db905c0"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a6c7873a3320a59a63aa26c006db905c0">armnn::QuantizedLstmInputParamsInfo::m_RecurrentToCellWeights</a></div><div class="ttdeci">const TensorInfo * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00146">QuantizedLstmParams.hpp:146</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a41cb9b797ebc6f6f6314e3ded935f4cf"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a41cb9b797ebc6f6f6314e3ded935f4cf">armnn::LayerType::Splitter</a></div></div> +<div class="ttc" id="_layer_support_8hpp_xhtml"><div class="ttname"><a href="_layer_support_8hpp.xhtml">LayerSupport.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_depth_to_space_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depth_to_space_queue_descriptor.xhtml">armnn::DepthToSpaceQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00559">WorkloadData.hpp:559</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a91fe56cae7e970d90f6e7f54427e7d44"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a91fe56cae7e970d90f6e7f54427e7d44">armnn::IWorkloadFactory::CreateGather</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateGather(const GatherQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01231">WorkloadFactory.cpp:1231</a></div></div> +<div class="ttc" id="structarmnn_1_1_l2_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_queue_descriptor.xhtml">armnn::L2NormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00316">WorkloadData.hpp:316</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a2b414a001b6b31d00bfe4056fd6740c5"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a2b414a001b6b31d00bfe4056fd6740c5">armnn::IWorkloadFactory::CreateConvertFp32ToFp16</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateConvertFp32ToFp16(const ConvertFp32ToFp16QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01153">WorkloadFactory.cpp:1153</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4abbc155fb2b111bf61c4f5ff892915e6b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4abbc155fb2b111bf61c4f5ff892915e6b">armnn::LayerType::Switch</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a8851ca32bea910cf9376d05527e3dbef"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a8851ca32bea910cf9376d05527e3dbef">armnn::IWorkloadFactory::CreateMinimum</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateMinimum(const MinimumQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01304">WorkloadFactory.cpp:1304</a></div></div> +<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_a0348e6bb67ace72535bd105219bb6237"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#a0348e6bb67ace72535bd105219bb6237">scores</a></div><div class="ttdeci">std::vector< float > scores({ 0.0f, 0.9f, 0.8f, 0.0f, 0.75f, 0.72f, 0.0f, 0.6f, 0.5f, 0.0f, 0.93f, 0.95f, 0.0f, 0.5f, 0.4f, 0.0f, 0.3f, 0.2f })</div></div> +<div class="ttc" id="structarmnn_1_1_transpose_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_queue_descriptor.xhtml">armnn::TransposeQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00507">WorkloadData.hpp:507</a></div></div> +<div class="ttc" id="structarmnn_1_1_strided_slice_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_strided_slice_queue_descriptor.xhtml">armnn::StridedSliceQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00425">WorkloadData.hpp:425</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="structarmnn_1_1_arg_min_max_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_queue_descriptor.xhtml">armnn::ArgMinMaxQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00135">WorkloadData.hpp:135</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_a15f9f65126ad3d4d82d6c19d0662ae01"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#a15f9f65126ad3d4d82d6c19d0662ae01">armnn::QuantizedLstmInputParamsInfo::m_InputToInputWeights</a></div><div class="ttdeci">const TensorInfo * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00139">QuantizedLstmParams.hpp:139</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a3c3a47828ee252dca111605c9be4b072"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a3c3a47828ee252dca111605c9be4b072">armnn::IWorkloadFactory::CreateDepthToSpace</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateDepthToSpace(const DepthToSpaceQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01171">WorkloadFactory.cpp:1171</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a86658e2fc02a32acd4de20ef92242347"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a86658e2fc02a32acd4de20ef92242347">armnn::IWorkloadFactory::CreateSlice</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateSlice(const SliceQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01394">WorkloadFactory.cpp:1394</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateAddition(const AdditionQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01105">WorkloadFactory.cpp:1105</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">armnn::BatchNormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00269">WorkloadData.hpp:269</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a12cccba82124cc4993868a3173a65167"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a12cccba82124cc4993868a3173a65167">armnn::IWorkloadFactory::CreateTransposeConvolution2d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateTransposeConvolution2d(const TransposeConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01454">WorkloadFactory.cpp:1454</a></div></div> +<div class="ttc" id="structarmnn_1_1_mem_import_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mem_import_queue_descriptor.xhtml">armnn::MemImportQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00066">WorkloadData.hpp:66</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a890a37ff3bfe123414ba7e6f052b49f3"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a890a37ff3bfe123414ba7e6f052b49f3">armnn::LayerType::QuantizedLstm</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_af07c65d3b7886a00f10c69093e76a341"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#af07c65d3b7886a00f10c69093e76a341">armnn::QuantizedLstmInputParamsInfo::m_InputToCellWeights</a></div><div class="ttdeci">const TensorInfo * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00141">QuantizedLstmParams.hpp:141</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a2139684546b147c106b329f41547640c"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a2139684546b147c106b329f41547640c">armnn::LayerType::ArgMinMax</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ac63f8f12f80efbe37b789d1540649470"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ac63f8f12f80efbe37b789d1540649470">armnn::IWorkloadFactory::CreateMean</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateMean(const MeanQueueDescriptor &descriptor, const WorkloadInfo &Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01274">WorkloadFactory.cpp:1274</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a06b091bc9aea697ba473c71f0bb55925"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a06b091bc9aea697ba473c71f0bb55925">armnn::LayerType::Lstm</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ae4743c3ec15d1d84169b17264634692e">armnn::LayerType::BatchNormalization</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_adb279112eb265e5531c4ac2194b6c898"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#adb279112eb265e5531c4ac2194b6c898">armnn::IWorkloadFactory::CreateOutput</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateOutput(const OutputQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01322">WorkloadFactory.cpp:1322</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_aaef29472862381822654ab6cbf7cba2a"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00259">Layer.hpp:259</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a9943775a364fc4ab53b85ac88f311886"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">armnn::IOutputSlot::GetTensorInfo</a></div><div class="ttdeci">virtual const TensorInfo & GetTensorInfo() const =0</div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a8a843d44d2e81df87e414df3b3e688de"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a8a843d44d2e81df87e414df3b3e688de">armnn::IWorkloadFactory::CreateSoftmax</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateSoftmax(const SoftmaxQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01400">WorkloadFactory.cpp:1400</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4ac21dbda57d88c21ec9857f5d1522c488"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ac21dbda57d88c21ec9857f5d1522c488">armnn::LayerType::LogSoftmax</a></div></div> +<div class="ttc" id="_layers_fwd_8hpp_xhtml"><div class="ttname"><a href="_layers_fwd_8hpp.xhtml">LayersFwd.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_switch_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_switch_queue_descriptor.xhtml">armnn::SwitchQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00484">WorkloadData.hpp:484</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_afcc1c3a20bd2860e0ddd21674389246f"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#afcc1c3a20bd2860e0ddd21674389246f">armnn::IConnectableLayer::GetName</a></div><div class="ttdeci">virtual const char * GetName() const =0</div><div class="ttdoc">Returns the name of the layer. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a3489c7b05e180496cb2ce8ac73887f48"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a3489c7b05e180496cb2ce8ac73887f48">armnn::LayerType::FakeQuantization</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a731729ad1b2c0eb9399b62c770b3482d"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a731729ad1b2c0eb9399b62c770b3482d">armnn::LayerType::DepthToSpace</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a1c193739520e08f686b347ff795ad2fe"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a1c193739520e08f686b347ff795ad2fe">armnn::IWorkloadFactory::CreateFullyConnected</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateFullyConnected(const FullyConnectedQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01225">WorkloadFactory.cpp:1225</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4aa1d0ec6d56f8833a078b5a7ac4caf2d4"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aa1d0ec6d56f8833a078b5a7ac4caf2d4">armnn::LayerType::Minimum</a></div></div> +<div class="ttc" id="structarmnn_1_1_pre_compiled_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pre_compiled_queue_descriptor.xhtml">armnn::PreCompiledQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00462">WorkloadData.hpp:462</a></div></div> +<div class="ttc" id="structarmnn_1_1_dequantize_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_dequantize_queue_descriptor.xhtml">armnn::DequantizeQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00474">WorkloadData.hpp:474</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_queue_descriptor.xhtml">armnn::Pooling2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00162">WorkloadData.hpp:162</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_accb9759dfd2880efe0f8d2705ddee448"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#accb9759dfd2880efe0f8d2705ddee448">armnn::IWorkloadFactory::CreateDepthwiseConvolution2d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateDepthwiseConvolution2d(const DepthwiseConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01177">WorkloadFactory.cpp:1177</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4aaf70b1ac863830a4e1ce6268c8399f54"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aaf70b1ac863830a4e1ce6268c8399f54">armnn::LayerType::Transpose</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_aa1a45333dc35cb5ba9ab71fca4f359e4"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#aa1a45333dc35cb5ba9ab71fca4f359e4">armnn::IWorkloadFactory::CreateFloor</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateFloor(const FloorQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01219">WorkloadFactory.cpp:1219</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_af0c99a5e2a6e4a67fec8b8c5906a3552"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#af0c99a5e2a6e4a67fec8b8c5906a3552">armnn::IWorkloadFactory::CreateMemImport</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateMemImport(const MemImportQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01286">WorkloadFactory.cpp:1286</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00495">Descriptors.hpp:495</a></div></div> +<div class="ttc" id="structarmnn_1_1_mean_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mean_queue_descriptor.xhtml">armnn::MeanQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00246">WorkloadData.hpp:246</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml">armnn::InstanceNormalizationDescriptor</a></div><div class="ttdoc">An InstanceNormalizationDescriptor for InstanceNormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00629">Descriptors.hpp:629</a></div></div> +<div class="ttc" id="structarmnn_1_1_log_softmax_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_log_softmax_queue_descriptor.xhtml">armnn::LogSoftmaxQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00321">WorkloadData.hpp:321</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a439305cf0a71fc85a0b93cc063100f91"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a439305cf0a71fc85a0b93cc063100f91">armnn::IWorkloadFactory::CreateSubtraction</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateSubtraction(const SubtractionQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01436">WorkloadFactory.cpp:1436</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4ad140d37ad98c12ccd8e1c432f548bcdb"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ad140d37ad98c12ccd8e1c432f548bcdb">armnn::LayerType::Slice</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a3025cdaab2deb0bb2cd642449e570833"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a3025cdaab2deb0bb2cd642449e570833">armnn::LayerType::Division</a></div></div> +<div class="ttc" id="structarmnn_1_1_reshape_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_reshape_queue_descriptor.xhtml">armnn::ReshapeQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00338">WorkloadData.hpp:338</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a012306477c38a533edd29c422227cd8c"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a012306477c38a533edd29c422227cd8c">armnn::IWorkloadFactory::CreatePreCompiled</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreatePreCompiled(const PreCompiledQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01346">WorkloadFactory.cpp:1346</a></div></div> +<div class="ttc" id="structarmnn_1_1_debug_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_debug_queue_descriptor.xhtml">armnn::DebugQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00441">WorkloadData.hpp:441</a></div></div> +<div class="ttc" id="structarmnn_1_1_elementwise_unary_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_elementwise_unary_queue_descriptor.xhtml">armnn::ElementwiseUnaryQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00569">WorkloadData.hpp:569</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a83e0a21747c1ce29b2083c1e3b1d88af"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a83e0a21747c1ce29b2083c1e3b1d88af">armnn::IWorkloadFactory::CreateConvertFp16ToFp32</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateConvertFp16ToFp32(const ConvertFp16ToFp32QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01147">WorkloadFactory.cpp:1147</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00444">Descriptors.hpp:444</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">armnn::DepthwiseConvolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00183">WorkloadData.hpp:183</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_queue_descriptor.xhtml">armnn::ActivationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00130">WorkloadData.hpp:130</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a2184995027cd2c9f9980206de9658855"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a2184995027cd2c9f9980206de9658855">armnn::IWorkloadFactory::CreateConvolution2d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateConvolution2d(const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01159">WorkloadFactory.cpp:1159</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_info_xhtml_ab173a067eeb7295d84f5327bcc05a6c1"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params_info.xhtml#ab173a067eeb7295d84f5327bcc05a6c1">armnn::QuantizedLstmInputParamsInfo::m_CellBias</a></div><div class="ttdeci">const TensorInfo * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00151">QuantizedLstmParams.hpp:151</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_i_workload_factory_xhtml_adf4a93f605e4e7dad6aee0b4d2159171"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#adf4a93f605e4e7dad6aee0b4d2159171">armnn::IWorkloadFactory::CreatePrelu</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreatePrelu(const PreluQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01352">WorkloadFactory.cpp:1352</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_normalization_queue_descriptor.xhtml">armnn::NormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00210">WorkloadData.hpp:210</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 class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a3243806bf6c89df8952cc0a3601e538b"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a3243806bf6c89df8952cc0a3601e538b">armnn::IWorkloadFactory::CreateDequantize</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateDequantize(const DequantizeQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01183">WorkloadFactory.cpp:1183</a></div></div> +</div><!-- fragment --></div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.xhtml">backendsCommon</a></li><li class="navelem"><a class="el" href="_workload_factory_8cpp.xhtml">WorkloadFactory.cpp</a></li> + <li class="footer">Generated on Fri Mar 13 2020 16:09:11 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> |