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diff --git a/21.02/_shape_inference_tests_8cpp_source.xhtml b/21.02/_shape_inference_tests_8cpp_source.xhtml new file mode 100644 index 0000000000..97cff4b9ba --- /dev/null +++ b/21.02/_shape_inference_tests_8cpp_source.xhtml @@ -0,0 +1,260 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/armnn/test/ShapeInferenceTests.cpp Source File</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">21.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_shape_inference_tests_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">ShapeInferenceTests.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_shape_inference_tests_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 © 2020 Arm Ltd and Contributors. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_tensor_8hpp.xhtml">armnn/Tensor.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_graph_8hpp.xhtml">Graph.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_internal_types_8hpp.xhtml">InternalTypes.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_fully_connected_layer_8hpp.xhtml">layers/FullyConnectedLayer.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_workload_data_8hpp.xhtml">backendsCommon/WorkloadData.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</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="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(ShapeInferenceTests)</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="keyword">namespace</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> </div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> constexpr <span class="keyword">const</span> <span class="keywordtype">bool</span> maskPermutations[6][4] = {{<span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>},</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  {<span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>},</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  {<span class="keyword">false</span>, <span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">false</span>},</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  {<span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">true</span>, <span class="keyword">false</span>},</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  {<span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">true</span>},</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  {<span class="keyword">true</span>, <span class="keyword">true</span>, <span class="keyword">true</span>, <span class="keyword">true</span>}};</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="keyword">template</span><<span class="keyword">typename</span> LayerT, <span class="keyword">typename</span>... Args></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> LayerT* BuildGraph(<a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>* graph, <span class="keyword">const</span> std::vector<TensorShape>& inputShapes, Args &&... args)</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>  <span class="keyword">auto</span> layer = graph-><a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><LayerT>(std::forward<Args>(args)...);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  uint32_t inputCount = 0;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> inputShape : inputShapes)</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputTensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</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>  <span class="keyword">auto</span> input = graph->AddLayer<<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(<span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(inputCount), <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  input->GetOutputSlot().SetTensorInfo(inputTensorInfo);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  input->GetOutputSlot().Connect(layer->GetInputSlot(inputCount));</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  inputCount++;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  }</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">return</span> layer;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> }</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> </div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="keyword">template</span><<span class="keyword">typename</span> LayerT></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="keywordtype">void</span> RunShapeInferenceTest(LayerT* <span class="keyword">const</span> layer,</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="keyword">const</span> std::vector<std::initializer_list<unsigned int>> dimensionSizeLists)</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> {</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  std::vector<unsigned int> numDimensions;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  std::vector<TensorShape> expectedOutputShapes;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> </div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> dimensionSizeList : dimensionSizeLists)</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>  numDimensions.emplace_back(dimensionSizeList.size());</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  expectedOutputShapes.emplace_back(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(dimensionSizeList));</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</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>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = layer->GetNumOutputSlots();</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">const</span> <span class="keyword">auto</span> runTestWithMask = [&](<span class="keyword">const</span> <span class="keywordtype">bool</span> maskPermutations[])</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < outputSize; ++i)</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  {</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  layer->GetOutputSlot(i).SetTensorInfo({{numDimensions[i], dimensionSizeLists[i].begin(), maskPermutations},</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>});</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  }</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  layer->ValidateTensorShapesFromInputs();</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < outputSize; ++i)</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  BOOST_CHECK(layer->GetOutputSlot(i).GetTensorInfo().GetShape() == expectedOutputShapes[i]);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  }</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  };</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="comment">// Test inference with Dimensionality::NotSpecified</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = 0; j < outputSize; ++j)</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  {</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  layer->GetOutputSlot(j).SetTensorInfo({<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">Dimensionality::NotSpecified</a>), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>});</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  }</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  layer->SetShapeInferenceMethod(<a class="code" href="namespacearmnn.xhtml#adf57837d00e8352d9b5cc5ab1fb5fee9af6486a22a9bb11959bfae60a3e5174b1">ShapeInferenceMethod::ValidateOnly</a>);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  BOOST_CHECK_THROW(layer->ValidateTensorShapesFromInputs(), <a class="code" href="classarmnn_1_1_layer_validation_exception.xhtml">LayerValidationException</a>);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  layer->SetShapeInferenceMethod(<a class="code" href="namespacearmnn.xhtml#adf57837d00e8352d9b5cc5ab1fb5fee9a5dd7c525cb1500a2181fd4cc079d7acb">ShapeInferenceMethod::InferAndValidate</a>);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  layer->ValidateTensorShapesFromInputs();</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < outputSize; ++i)</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  {</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  BOOST_CHECK(layer->GetOutputSlot(i).GetTensorInfo().GetShape() == expectedOutputShapes[i]);</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  }</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="comment">// Test inference with Dimensionality::Specified and various combinations of dimensions of unknown size</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numDimensions[0]; ++i)</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>  runTestWithMask(maskPermutations[i]);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  }</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="comment">// maskPermutations[5] equates to all dimensions being known</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  runTestWithMask(maskPermutations[5]);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> }</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="keyword">template</span><<span class="keyword">typename</span> LayerT, <span class="keyword">typename</span>... Args></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="keywordtype">void</span> CreateGraphAndRunTest(<span class="keyword">const</span> std::vector<TensorShape>& inputShapes,</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">const</span> std::vector<std::initializer_list<unsigned int>> dimensionSizeLists,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  Args &&... args)</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> {</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph(<span class="keyword">true</span>);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keyword">auto</span> layer = BuildGraph<LayerT>(&graph, inputShapes, std::forward<Args>(args)...);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> </div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  RunShapeInferenceTest<LayerT>(layer, dimensionSizeLists);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> }</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(NetworkOptionsTest)</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> {</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <a class="code" href="structarmnn_1_1_backend_options.xhtml">BackendOptions</a> ShapeInferenceMethodOption(<span class="stringliteral">"ShapeInferenceMethod"</span>,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  { <span class="stringliteral">"InferAndValidate"</span>, <span class="keyword">true</span> }</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  });</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>({ShapeInferenceMethodOption});</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> tensorInfo({ 5, 7, 6, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</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="keyword">auto</span> inputLayer = network->AddInputLayer(1, <span class="stringliteral">"inputLayer"</span>);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">ActivationDescriptor</a> descriptor;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">ActivationFunction::Abs</a>;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keyword">auto</span> activationLayer = network->AddActivationLayer(descriptor, <span class="stringliteral">"activation"</span>);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  inputLayer->GetOutputSlot(0).Connect(activationLayer->GetInputSlot(0));</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  activationLayer->GetOutputSlot(0).SetTensorInfo({<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">Dimensionality::NotSpecified</a>}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>});</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  BOOST_CHECK_NO_THROW(activationLayer->GetOutputSlot(0).IsTensorInfoSet());</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>  BOOST_CHECK(activationLayer->GetOutputSlot(0).GetTensorInfo() == tensorInfo);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> </div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  ShapeInferenceMethodOption = <a class="code" href="structarmnn_1_1_backend_options.xhtml">BackendOptions</a>(<span class="stringliteral">"ShapeInferenceMethod"</span>,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  { <span class="stringliteral">"InferAndValidate"</span>, <span class="keyword">false</span> }</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  });</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>({ShapeInferenceMethodOption});</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  inputLayer = network->AddInputLayer(1, <span class="stringliteral">"inputLayer"</span>);</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  activationLayer = network->AddActivationLayer(descriptor, <span class="stringliteral">"activation"</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>  inputLayer->GetOutputSlot(0).Connect(activationLayer->GetInputSlot(0));</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  activationLayer->GetOutputSlot(0).SetTensorInfo({<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">Dimensionality::NotSpecified</a>}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>});</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> </div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  BOOST_CHECK_NO_THROW(activationLayer->GetOutputSlot(0).IsTensorInfoSet());</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>();</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  inputLayer = network->AddInputLayer(1, <span class="stringliteral">"inputLayer"</span>);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> </div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  activationLayer = network->AddActivationLayer(descriptor, <span class="stringliteral">"activation"</span>);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  inputLayer->GetOutputSlot(0).Connect(activationLayer->GetInputSlot(0));</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  activationLayer->GetOutputSlot(0).SetTensorInfo({<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">Dimensionality::NotSpecified</a>}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</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>  BOOST_CHECK_NO_THROW(activationLayer->GetOutputSlot(0).IsTensorInfoSet());</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> }</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> </div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(<a class="code" href="_activation_test_impl_8cpp.xhtml#afa1af28f33ae8978b6df0b170561f787">AbsTest</a>)</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>  <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">ActivationDescriptor</a> descriptor;</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">ActivationFunction::Abs</a>;</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  CreateGraphAndRunTest<ActivationLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, descriptor, <span class="stringliteral">"activation"</span>);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> }</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(<a class="code" href="_addition_test_impl_8cpp.xhtml#a5e9b2ce84031d422f4d7c3e8f5b50caa">AdditionTest</a>)</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> {</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  CreateGraphAndRunTest<AdditionLayer>({{ 5, 7, 6, 2 }, { 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> }</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> </div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ArgMinMaxTest)</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> {</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a> descriptor;</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml#ab1ae6f520bb1a4da191a0ae907477f23">m_Function</a> = <a class="code" href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeaea78d811e98514cd165dda532286610fd2">ArgMinMaxFunction::Min</a>;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = 1;</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> </div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  CreateGraphAndRunTest<ArgMinMaxLayer>({{ 1, 3, 2, 4 }}, {{ 1, 2, 4 }}, descriptor, <span class="stringliteral">"argMinMax"</span>);</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> }</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> </div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(BatchNormalizationTest)</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> {</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml">BatchNormalizationDescriptor</a> descriptor;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  CreateGraphAndRunTest<BatchNormalizationLayer>({{ 1, 2, 3, 2 }}, {{ 1, 2, 3, 2 }}, descriptor, <span class="stringliteral">"batchNorm"</span>);</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> }</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(BatchToSpaceNdTest)</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> {</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">BatchToSpaceNdDescriptor</a> descriptor;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  std::vector<unsigned int> blockShape {2, 2};</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> </div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> = blockShape;</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a3941f674c071c9503e00d2b59e92e454">m_Crops</a> = crops;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> </div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  CreateGraphAndRunTest<BatchToSpaceNdLayer>({{ 4, 2, 2, 1 }}, {{ 1, 4, 4, 1 }}, descriptor, <span class="stringliteral">"batchtospacend"</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> </div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ComparisionTest)</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> {</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <a class="code" href="structarmnn_1_1_comparison_descriptor.xhtml">ComparisonDescriptor</a> descriptor;</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  descriptor.<a class="code" href="structarmnn_1_1_comparison_descriptor.xhtml#a865dc4f43cb0ff01a1dcf78036912fd1">m_Operation</a> = <a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">ComparisonOperation::Equal</a>;</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  CreateGraphAndRunTest<ComparisonLayer>({{ 5, 7, 6, 2 }, { 5, 7, 6, 2 }},</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  {{ 5, 7, 6, 2 }},</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  descriptor,</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <span class="stringliteral">"comparision"</span>);</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> }</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> </div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(<a class="code" href="_concat_test_impl_8cpp.xhtml#a2e952c053f3d7a035671a994352e2bc9">ConcatTest</a>)</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>  <a class="code" href="structarmnn_1_1_origins_descriptor.xhtml">ConcatDescriptor</a> descriptor(2, 3);</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>  descriptor.SetViewOriginCoord(0, 0, 0);</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  descriptor.SetViewOriginCoord(1, 0, 1);</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> </div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  CreateGraphAndRunTest<ConcatLayer>({{ 1, 2, 1 }, { 1, 2, 1 }}, {{ 2, 2, 1 }}, descriptor, <span class="stringliteral">"concat"</span>);</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> }</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> </div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ConstantTesst)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape{ 1, 1, 3, 3 };</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keyword">auto</span> layer = BuildGraph<ConstantLayer>(&graph, {}, <span class="stringliteral">"constant"</span>);</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> Datum = 0.0f;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> output0({outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>}, &Datum);</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  layer->m_LayerOutput = std::make_unique<ScopedCpuTensorHandle>(output0);</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>  layer->GetOutputSlot(0).SetTensorInfo({{1, 1, 3, 3}, DataType::Float32});</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> </div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  layer->ValidateTensorShapesFromInputs();</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> </div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  BOOST_CHECK(layer->GetOutputSlot(0).GetTensorInfo().GetShape() == outputShape);</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> }</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> </div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(<a class="code" href="_convert_bf16_to_fp32_test_impl_8cpp.xhtml#a72c71ccbf53cf4db9727ec413f9ff2b3">ConvertBf16ToFp32Test</a>)</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>  CreateGraphAndRunTest<ConvertBf16ToFp32Layer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"floor"</span>);</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> }</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> </div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ConvertFp16ToBf16Test)</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> {</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> tensorShape{5, 7, 6, 2};</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  CreateGraphAndRunTest<ConvertFp32ToBf16Layer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"floor"</span>);</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> }</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> </div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ConvertFp16ToFp32Test)</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> {</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  CreateGraphAndRunTest<ConvertFp16ToFp32Layer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"floor"</span>);</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> }</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> </div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ConvertFp32ToFp16Test)</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> {</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  CreateGraphAndRunTest<ConvertFp32ToFp16Layer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"floor"</span>);</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> }</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> </div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(Convolution2dTest)</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> {</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape{1, 1, 10, 10};</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> </div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> </div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> </div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 0;</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 0;</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 0;</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = 3;</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = 3;</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> layer = BuildGraph<Convolution2dLayer>(&graph,</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  {inputShape},</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  descriptor,</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="stringliteral">"conv2d"</span>);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> Datum = 0.0f;</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> weights({{1, 1, 3, 3}, DataType::Float32}, &Datum);</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  RunShapeInferenceTest<Convolution2dLayer>(layer, {{ 1, 1, 4, 4 }});</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> </div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(DebugLayerTest)</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span> {</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> tensorShape;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  CreateGraphAndRunTest<DebugLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"debug"</span>);</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> }</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> </div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(DepthToSpaceTest)</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>  <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml">DepthToSpaceDescriptor</a> descriptor;</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>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a> = 2;</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> </div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  CreateGraphAndRunTest<DepthToSpaceLayer>({{ 1, 1, 1, 8}}, {{ 1, 2, 2, 2 }}, descriptor, <span class="stringliteral">"depthtospace"</span>);</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> }</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> </div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(DepthwiseConvolutionTest)</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> {</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 0;</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 0;</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 1;</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 1;</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = 0;</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = 0;</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">false</span>;</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> </div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keyword">auto</span> layer = BuildGraph<DepthwiseConvolution2dLayer>(&graph,</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  {{ 8, 16, 2, 1 }},</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  descriptor,</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="stringliteral">"depthwiseconv2d"</span>);</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> </div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> Datum = 0.0f;</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> weights({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum);</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span> </div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  RunShapeInferenceTest<DepthwiseConvolution2dLayer>(layer, {{ 8, 18, 1, 2 }});</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> }</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span> </div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(DequantizeTest)</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span> {</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> tensorShape{5, 7, 6, 2};</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  CreateGraphAndRunTest<DequantizeLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"dequantize"</span>);</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> </div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(DetectionPostProcessTest)</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> detectionBoxesInfo{ 1, 3, 4 };</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> detectionScoresInfo{ 1, 3, 4 };</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> detectionClassesInfo{ 1, 3, 4 };</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> </div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a> descriptor;</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">m_UseRegularNms</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">m_MaxDetections</a> = 3;</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a9ae2c9796692ebeafe19a4d3f09c8ea8">m_MaxClassesPerDetection</a> = 1;</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7e2f87544b8bc7e497e1dec8d3ca4055">m_DetectionsPerClass</a> =1;</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a4392dd6b4862cc9cf95ae8f1001ba592">m_NmsScoreThreshold</a> = 0.0;</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a53c8a7f33a40e1e240256bcfcf41b101">m_NmsIouThreshold</a> = 0.5;</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a3a04b0ccee4bb2f21721ee5045e83df4">m_NumClasses</a> = 2;</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7a2156ec7d9c012ce00bbcc6afcb9028">m_ScaleY</a> = 10.0;</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae64523937ea910030ad66fee6fddd51f">m_ScaleX</a> = 10.0;</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#aa61510cbd529870182e918ac6e8b9d72">m_ScaleH</a> = 5.0;</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ab509802c659de19929f18bad14a35c58">m_ScaleW</a> = 5.0;</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span> </div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> Datum = 0.0f;</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> anchorsTensor({{1, 1, 3, 3}, DataType::Float32}, &Datum);</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> </div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="keyword">auto</span> layer = BuildGraph<DetectionPostProcessLayer>(&graph,</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  {detectionBoxesInfo, detectionScoresInfo},</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  descriptor,</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="stringliteral">"detectionpostprocess"</span>);</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span> </div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  layer->m_Anchors = std::make_unique<ScopedCpuTensorHandle>(anchorsTensor);</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>  RunShapeInferenceTest<DetectionPostProcessLayer>(layer, {{ 1, 3, 4 }, { 1, 3 }, { 1, 3 }, { 1 }});</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> </div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(<a class="code" href="_fake_quantization_test_impl_8cpp.xhtml#a545e66a405496a758053aef7808e81a5">FakeQuantizationTest</a>)</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span> {</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <a class="code" href="structarmnn_1_1_fake_quantization_descriptor.xhtml">FakeQuantizationDescriptor</a> descriptor;</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  descriptor.<a class="code" href="structarmnn_1_1_fake_quantization_descriptor.xhtml#ad3729c591f7bfda7ad9ef9927d8a1bd6">m_Max</a> = 1;</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  descriptor.<a class="code" href="structarmnn_1_1_fake_quantization_descriptor.xhtml#a4c14a8e0d126891dd0c38e7584312bfd">m_Min</a> = 1;</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  CreateGraphAndRunTest<FakeQuantizationLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, descriptor, <span class="stringliteral">"fakequantization"</span>);</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> }</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> </div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(FloorTest)</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_shape.xhtml">TensorShape</a> tensorShape{5, 7, 6, 2};</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  CreateGraphAndRunTest<FloorLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"floor"</span>);</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> }</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span> </div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(<a class="code" href="_fully_connected_test_impl_8cpp.xhtml#a834305b5bfdbee9e753bb7ad299944cf">FullyConnectedTest</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> </div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 3u;</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 2u;</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 1u;</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = 2u;</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> </div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <span class="keyword">auto</span> layer = BuildGraph<FullyConnectedLayer>(&graph,</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  {{1, inputChannels, inputHeight, inputWidth}},</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">FullyConnectedDescriptor</a>(),</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <span class="stringliteral">"fc"</span>);</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> </div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> </div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> Datum = 0.0f;</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> weights({{inputChannels, outputChannels}, DataType::Float32}, &Datum);</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights);</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> </div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  RunShapeInferenceTest<FullyConnectedLayer>(layer, {{ 1, outputChannels }});</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span> }</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span> </div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(GatherTest)</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span> {</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  CreateGraphAndRunTest<GatherLayer>({{ 7, 6, 2}, {2,3}}, {{ 2, 3, 6, 2 }}, <a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">GatherDescriptor</a>(), <span class="stringliteral">"gather"</span>);</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> }</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> </div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(InstanceNormalizationTest)</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span> {</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> tensorShape{5, 7, 6, 2};</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span> </div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  CreateGraphAndRunTest<InstanceNormalizationLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }},</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml">InstanceNormalizationDescriptor</a>(),</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="stringliteral">"instancenorm"</span>);</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span> }</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(L2NormalizationTest)</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> {</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> tensorShape{5, 7, 6, 2};</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span> </div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  CreateGraphAndRunTest<L2NormalizationLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }},</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <a class="code" href="structarmnn_1_1_l2_normalization_descriptor.xhtml">L2NormalizationDescriptor</a>(),</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <span class="stringliteral">"l2norm"</span>);</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span> }</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span> </div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(LogSoftMaxTest)</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span> {</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> tensorShape{5, 7, 6, 2};</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span> </div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  CreateGraphAndRunTest<LogSoftmaxLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <a class="code" href="namespacearmnn.xhtml#ac14705405cbcdd580df613de6766fe65">LogSoftmaxDescriptor</a>(), <span class="stringliteral">"logsoftmax"</span>);</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> }</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span> </div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(LstmTest)</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span> {</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape{2, 5};</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputCellState{2, 20};</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_shape.xhtml">TensorShape</a> expectedOutputShape{2, 20};</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span> </div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml">LstmDescriptor</a> descriptor;</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span> </div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  descriptor.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = 4;</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  descriptor.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  descriptor.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  descriptor.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span> </div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="keyword">auto</span> layer = BuildGraph<LstmLayer>(&graph, {inputShape, inputCellState, inputCellState}, descriptor, <span class="stringliteral">"lstm"</span>);</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span> </div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="keywordtype">float</span> Datum = 0.0f;</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> constTensor({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum);</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span> </div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  layer->m_BasicParameters.m_CellBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  layer->m_CifgParameters.m_InputGateBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  layer->m_BasicParameters.m_OutputGateBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  layer->m_BasicParameters.m_RecurrentToForgetWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  layer->m_BasicParameters.m_RecurrentToCellWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  layer->m_BasicParameters.m_RecurrentToOutputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  layer->m_CifgParameters.m_RecurrentToInputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  layer->m_CifgParameters.m_InputToInputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span> </div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  RunShapeInferenceTest<LstmLayer>(layer, {{2, 80}, {2, 20}, {2, 20}, {2, 20}});</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span> }</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span> </div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(MeanLayerTest)</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> {</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <a class="code" href="structarmnn_1_1_mean_descriptor.xhtml">MeanDescriptor</a> descriptor;</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  descriptor.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a> = {0};</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span> </div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  CreateGraphAndRunTest<MeanLayer>({{ 5, 7, 6, 2 }}, {{ 7, 6, 2 }}, descriptor, <span class="stringliteral">"mean"</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> </div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(MemCopyTest)</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span> {</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  CreateGraphAndRunTest<MemCopyLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"memcopy"</span>);</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span> }</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span> </div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(MemImportTest)</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span> {</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  CreateGraphAndRunTest<MemImportLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"memomport"</span>);</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span> }</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span> </div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(MergeTest)</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span> {</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> tensorShape{ 5, 7, 6, 2 };</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  CreateGraphAndRunTest<MergeLayer>({ { 5, 7, 6, 2 }, { 5, 7, 6, 2 } }, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"merge"</span>);</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> </div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(NormalizationTest)</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span> {</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> tensorShape{5, 7, 6, 2};</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span> </div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  CreateGraphAndRunTest<NormalizationLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <a class="code" href="structarmnn_1_1_normalization_descriptor.xhtml">NormalizationDescriptor</a>(), <span class="stringliteral">"l2norm"</span>);</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span> }</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span> </div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(PermuteTest)</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span> {</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <a class="code" href="structarmnn_1_1_permute_descriptor.xhtml">PermuteDescriptor</a> descriptor;</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  descriptor.<a class="code" href="structarmnn_1_1_permute_descriptor.xhtml#a14433af2b223695b40d8c8f8ba2ebb8f">m_DimMappings</a> = {0U, 2U, 3U, 1U};</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>  CreateGraphAndRunTest<PermuteLayer>({{ 1, 2, 2, 3 }}, {{ 1, 3, 2, 2 }}, descriptor, <span class="stringliteral">"permute"</span>);</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span> }</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span> </div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(Pooling2dTest)</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>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 3;</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 4;</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 3;</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#affb5b68b3eba3ed45a06c7cde7781962">m_OutputShapeRounding</a> = <a class="code" href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a>;</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">m_PaddingMethod</a> = <a class="code" href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a>;</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span> </div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  CreateGraphAndRunTest<Pooling2dLayer>({{ 1, 2, 8, 13 }}, {{ 1, 2, 2, 8 }}, descriptor, <span class="stringliteral">"pooling2d"</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> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(<a class="code" href="_lstm_test_impl_8cpp.xhtml#a3ca648bd28b5f0b835868282409b3458">QLstmTest</a>)</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape{2, 5};</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputCellState{2, 20};</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> expectedOutputShape{2, 20};</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span> </div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml">QLstmDescriptor</a> descriptor;</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span> </div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">false</span>;</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <span class="keyword">auto</span> layer = BuildGraph<QLstmLayer>(&graph, {inputShape, inputCellState, inputCellState}, descriptor, <span class="stringliteral">"qlstm"</span>);</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span> </div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <span class="keywordtype">float</span> Datum = 0.0f;</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> constTensor({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum);</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>  layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  layer->m_BasicParameters.m_CellBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  layer->m_CifgParameters.m_InputGateBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  layer->m_BasicParameters.m_OutputGateBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  layer->m_BasicParameters.m_RecurrentToForgetWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  layer->m_BasicParameters.m_RecurrentToCellWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  layer->m_BasicParameters.m_RecurrentToOutputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  layer->m_CifgParameters.m_RecurrentToInputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  layer->m_CifgParameters.m_InputToInputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</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>  RunShapeInferenceTest<QLstmLayer>(layer, {{2, 20}, {2, 20}, {2, 20}});</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span> }</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span> </div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(<a class="code" href="_lstm_test_impl_8cpp.xhtml#a8d9469ec08347dd451d782f102a6c8fa">QuantizedLstmTest</a>)</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span> {</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape{2, 5};</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputCellState{2, 20};</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> expectedOutputShape{2, 20};</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span> </div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <span class="keyword">auto</span> layer = BuildGraph<QuantizedLstmLayer>(&graph, {inputShape, inputCellState, inputCellState}, <span class="stringliteral">"quatizedlstm"</span>);</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span> </div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  <span class="keywordtype">float</span> Datum = 0.0f;</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> constTensor({{ 2, 5, 3, 2 }, DataType::Float32}, &Datum);</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span> </div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  layer->m_QuantizedLstmParameters.m_InputToCellWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  layer->m_QuantizedLstmParameters.m_InputToForgetWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  layer->m_QuantizedLstmParameters.m_CellBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  layer->m_QuantizedLstmParameters.m_ForgetGateBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  layer->m_QuantizedLstmParameters.m_InputGateBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  layer->m_QuantizedLstmParameters.m_OutputGateBias = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  layer->m_QuantizedLstmParameters.m_InputToOutputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  layer->m_QuantizedLstmParameters.m_InputToInputWeights = std::make_unique<ScopedCpuTensorHandle>(constTensor);</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>  RunShapeInferenceTest<QuantizedLstmLayer>(layer, {{2, 20}, {2, 20}, {2, 20}});</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span> }</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span> </div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(QuantizeTest)</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span> {</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> tensorShape { 5, 4, 7, 6 };</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  CreateGraphAndRunTest<QuantizeLayer>({{ 5, 7, 6, 2 }}, {{ 5, 7, 6, 2 }}, <span class="stringliteral">"mean"</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> </div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(<a class="code" href="_rank_test_impl_8cpp.xhtml#a7856a1669cdb9bdc16e081f2864f0c1b">RankTest</a>)</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span> {</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="comment">// due to rank having a scalar output we need a custom test</span></div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> expectedOutputs(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">Dimensionality::Scalar</a>);</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span> </div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <span class="keyword">auto</span> layer = BuildGraph<RankLayer>(&graph, {{ 1, 1, 1, 1 }}, <span class="stringliteral">"rank"</span>);</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span> </div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  layer->GetOutputSlot(0).SetTensorInfo({<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">Dimensionality::NotSpecified</a>), DataType::Float32});</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span> </div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  BOOST_CHECK_THROW(</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  layer->ValidateTensorShapesFromInputs(), <a class="code" href="classarmnn_1_1_layer_validation_exception.xhtml">LayerValidationException</a>);</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span> </div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  layer->SetShapeInferenceMethod(<a class="code" href="namespacearmnn.xhtml#adf57837d00e8352d9b5cc5ab1fb5fee9a5dd7c525cb1500a2181fd4cc079d7acb">ShapeInferenceMethod::InferAndValidate</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>  layer->ValidateTensorShapesFromInputs();</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span> </div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  BOOST_CHECK(layer->GetOutputSlot(0).GetTensorInfo().GetShape() == expectedOutputs);</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span> </div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  layer->GetOutputSlot(0).SetTensorInfo({<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(<a class="code" href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">Dimensionality::Scalar</a>), DataType::Float32});</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>  layer->ValidateTensorShapesFromInputs();</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>  BOOST_CHECK(layer->GetOutputSlot(0).GetTensorInfo().GetShape() == expectedOutputs);</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span> }</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span> </div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ReshapeTest)</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>  <a class="code" href="structarmnn_1_1_reshape_descriptor.xhtml">ReshapeDescriptor</a> descriptor;</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>  descriptor.<a class="code" href="structarmnn_1_1_reshape_descriptor.xhtml#a1178f4dafdda81f59c15145ec327f7d9">m_TargetShape</a> = { 1, 1, 1, 8 };</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span> </div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  CreateGraphAndRunTest<ReshapeLayer>({{ 2, 2, 2, 2 }}, {{ 1, 1, 1, 8 }}, descriptor, <span class="stringliteral">"reshape"</span>);</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> </div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ResizeTest)</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span> {</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">ResizeDescriptor</a> descriptor;</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span> </div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a> = 6;</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  descriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a> = 2;</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>  CreateGraphAndRunTest<ResizeLayer>({{ 1, 7, 6, 2 }}, {{ 1, 7, 6, 2 }}, descriptor, <span class="stringliteral">"resize"</span>);</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> </div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(SliceTest)</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>  <a class="code" href="structarmnn_1_1_slice_descriptor.xhtml">SliceDescriptor</a> descriptor;</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.xhtml#a4939f00778f08d6c6fec6f74c0a59b7e">m_Begin</a> = { 1, 0, 1, 2 };</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  descriptor.<a class="code" href="structarmnn_1_1_slice_descriptor.xhtml#ab52cabf19232290fa6b49828ba957ac0">m_Size</a> = { 2, 1, 2, 3 };</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>  CreateGraphAndRunTest<SliceLayer>({{ 3, 2, 3, 5 }}, {{ 2, 1, 2, 3 }}, descriptor, <span class="stringliteral">"mean"</span>);</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span> }</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span> </div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(SpaceToBatchNdTest)</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span> {</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  <a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml">SpaceToBatchNdDescriptor</a> descriptor;</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span> </div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  std::vector<unsigned int> blockShape {2, 2};</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  std::vector<std::pair<unsigned int, unsigned int>> padlist = {{0, 0}, {0, 0}};</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>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> = blockShape;</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a85f98c94e11f65a6b73f831735c040f3">m_PadList</a> = padlist;</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span> </div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  CreateGraphAndRunTest<SpaceToBatchNdLayer>({{ 1, 4, 4, 1 }}, {{ 4, 2, 2, 1 }}, descriptor, <span class="stringliteral">"spacetobatchnd"</span>);</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span> }</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span> </div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(<a class="code" href="namespacearmnn.xhtml#a5e1dc69443b64ad16b669388a6023f7a">SpaceToDepth</a>)</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span> {</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml">SpaceToDepthDescriptor</a> descriptor;</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>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a> = 2;</div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span> </div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  CreateGraphAndRunTest<SpaceToDepthLayer>({{ 1, 2, 2, 2 }}, {{ 1, 1, 1, 8}}, descriptor, <span class="stringliteral">"spacetodepth"</span>);</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span> }</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span> </div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(SplitterTest)</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>  <a class="code" href="structarmnn_1_1_views_descriptor.xhtml">SplitterDescriptor</a> descriptor(2, 3);</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span> </div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  descriptor.SetViewSize(0, 0, 1);</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  descriptor.SetViewSize(0, 1, 2);</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  descriptor.SetViewSize(0, 2, 2);</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span> </div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  descriptor.SetViewSize(1, 0, 1);</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  descriptor.SetViewSize(1, 1, 2);</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  descriptor.SetViewSize(1, 2, 2);</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span> </div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  CreateGraphAndRunTest<SplitterLayer>({{ 2, 2, 2 }}, {{ 1, 2, 2 }, { 1, 2, 2 }}, descriptor, <span class="stringliteral">"splitter"</span>);</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span> }</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span> </div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(StackTest)</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span> {</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">StackDescriptor</a> descriptor;</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span> </div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#ab218de7805899c8412d75d1fd1d846d2">m_Axis</a> = 0;</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">m_NumInputs</a> = 2;</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#a2bea87b470268bb0b73457c3733dbc04">m_InputShape</a> = { 3, 2, 3 };</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>  CreateGraphAndRunTest<StackLayer>({{ 3, 2, 3 }, { 3, 2, 3 }}, {{ 2, 3, 2, 3 }}, descriptor, <span class="stringliteral">"stack"</span>);</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span> }</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span> </div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(StridedSliceTest)</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span> {</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml">StridedSliceDescriptor</a> descriptor;</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span> </div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  descriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#a118fe06b7c2599da60398ee311ede923">m_Begin</a> = {0, 0, 0, 0};</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  descriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#aa68194dd6258ab5b04123005a066ea25">m_End</a> = {3, 2, 3, 1};</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  descriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#a0d53caff836b84204adbd1c28752a201">m_Stride</a> = {2, 2, 2, 1};</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>  CreateGraphAndRunTest<StridedSliceLayer>({{ 3, 2, 3, 1 }}, {{ 2, 1, 2, 1 }}, descriptor, <span class="stringliteral">"stridedslice"</span>);</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> </div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(Switchtest)</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span> {</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  CreateGraphAndRunTest<SwitchLayer>({{ 3, 2, 3, 1 }, { 3, 2, 3, 1 }}, {{ 3, 2, 3, 1 }, { 3, 2, 3, 1 }}, <span class="stringliteral">"switch"</span>);</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span> }</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span> </div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(TransposeConvolution2dTest)</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span> {</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  <a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml">StridedSliceDescriptor</a> descriptor;</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span> </div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  descriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#a118fe06b7c2599da60398ee311ede923">m_Begin</a> = {0, 0, 0, 0};</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  descriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#aa68194dd6258ab5b04123005a066ea25">m_End</a> = {3, 2, 3, 1};</div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  descriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#a0d53caff836b84204adbd1c28752a201">m_Stride</a> = {2, 2, 2, 1};</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>  CreateGraphAndRunTest<StridedSliceLayer>({{ 3, 2, 3, 1 }}, {{ 2, 1, 2, 1 }}, descriptor, <span class="stringliteral">"t"</span>);</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span> }</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span> </div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(TransposeTest)</div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span> {</div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  <a class="code" href="structarmnn_1_1_transpose_descriptor.xhtml">armnn::TransposeDescriptor</a> descriptor;</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_descriptor.xhtml#a14433af2b223695b40d8c8f8ba2ebb8f">m_DimMappings</a> = {0U, 3U, 1U, 2U};</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span> </div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  CreateGraphAndRunTest<TransposeLayer>({{ 1, 2, 2, 3 }}, {{ 1, 3, 2, 2 }}, descriptor, <span class="stringliteral">"stridedslice"</span>);</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span> }</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span> </div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span> <a class="code" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span> }</div><div class="ttc" id="_output_shape_of_squeeze_8cpp_xhtml_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::Convolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00444">Descriptors.hpp:444</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00945">Descriptors.hpp:945</a></div></div> +<div class="ttc" id="_workload_data_8hpp_xhtml"><div class="ttname"><a href="_workload_data_8hpp.xhtml">WorkloadData.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_stack_descriptor_xhtml_ab218de7805899c8412d75d1fd1d846d2"><div class="ttname"><a href="structarmnn_1_1_stack_descriptor.xhtml#ab218de7805899c8412d75d1fd1d846d2">armnn::StackDescriptor::m_Axis</a></div><div class="ttdeci">uint32_t m_Axis</div><div class="ttdoc">0-based axis along which to stack the input tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01046">Descriptors.hpp:1046</a></div></div> +<div class="ttc" id="structarmnn_1_1_views_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_views_descriptor.xhtml">armnn::ViewsDescriptor</a></div><div class="ttdoc">A ViewsDescriptor for the SplitterLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00206">Descriptors.hpp:206</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ab509802c659de19929f18bad14a35c58"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ab509802c659de19929f18bad14a35c58">armnn::DetectionPostProcessDescriptor::m_ScaleW</a></div><div class="ttdeci">float m_ScaleW</div><div class="ttdoc">Center size encoding scale weight. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00561">Descriptors.hpp:561</a></div></div> +<div class="ttc" id="_concat_test_impl_8cpp_xhtml_a2e952c053f3d7a035671a994352e2bc9"><div class="ttname"><a href="_concat_test_impl_8cpp.xhtml#a2e952c053f3d7a035671a994352e2bc9">ConcatTest</a></div><div class="ttdeci">LayerTestResult< float, 3 > ConcatTest(IWorkloadFactory &workloadFactory, const IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_concat_test_impl_8cpp_source.xhtml#l02111">ConcatTestImpl.cpp:2111</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::Pooling2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00371">Descriptors.hpp:371</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00506">Descriptors.hpp:506</a></div></div> +<div class="ttc" id="_fully_connected_test_impl_8cpp_xhtml_a834305b5bfdbee9e753bb7ad299944cf"><div class="ttname"><a href="_fully_connected_test_impl_8cpp.xhtml#a834305b5bfdbee9e753bb7ad299944cf">FullyConnectedTest</a></div><div class="ttdeci">LayerTestResult< T, 2 > FullyConnectedTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled)</div><div class="ttdef"><b>Definition:</b> <a href="_fully_connected_test_impl_8cpp_source.xhtml#l00071">FullyConnectedTestImpl.cpp:71</a></div></div> +<div class="ttc" id="_fake_quantization_test_impl_8cpp_xhtml_a545e66a405496a758053aef7808e81a5"><div class="ttname"><a href="_fake_quantization_test_impl_8cpp.xhtml#a545e66a405496a758053aef7808e81a5">FakeQuantizationTest</a></div><div class="ttdeci">LayerTestResult< float, 2 > FakeQuantizationTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_fake_quantization_test_impl_8cpp_source.xhtml#l00016">FakeQuantizationTestImpl.cpp:16</a></div></div> +<div class="ttc" id="_tensor_8hpp_xhtml"><div class="ttname"><a href="_tensor_8hpp.xhtml">Tensor.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::DepthwiseConvolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00496">Descriptors.hpp:496</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Pooling2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00365">Descriptors.hpp:365</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681a4b7d504abac49ba24b4df86c129d3cbc">armnn::Dimensionality::NotSpecified</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5"><div class="ttname"><a href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58caf5f286e73bda105e538310b3190f75c5">armnn::ComparisonOperation::Equal</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3"><div class="ttname"><a href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a></div></div> +<div class="ttc" id="structarmnn_1_1_reshape_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_reshape_descriptor.xhtml">armnn::ReshapeDescriptor</a></div><div class="ttdoc">A ReshapeDescriptor for the ReshapeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00832">Descriptors.hpp:832</a></div></div> +<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_a118fe06b7c2599da60398ee311ede923"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#a118fe06b7c2599da60398ee311ede923">armnn::StridedSliceDescriptor::m_Begin</a></div><div class="ttdeci">std::vector< int > m_Begin</div><div class="ttdoc">Begin values for the input that will be sliced. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01115">Descriptors.hpp:1115</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00508">Descriptors.hpp:508</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="structarmnn_1_1_comparison_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_comparison_descriptor.xhtml">armnn::ComparisonDescriptor</a></div><div class="ttdoc">A ComparisonDescriptor for the ComparisonLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00078">Descriptors.hpp:78</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae64523937ea910030ad66fee6fddd51f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae64523937ea910030ad66fee6fddd51f">armnn::DetectionPostProcessDescriptor::m_ScaleX</a></div><div class="ttdeci">float m_ScaleX</div><div class="ttdoc">Center size encoding scale x. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00557">Descriptors.hpp:557</a></div></div> +<div class="ttc" id="structarmnn_1_1_stack_descriptor_xhtml_a2bea87b470268bb0b73457c3733dbc04"><div class="ttname"><a href="structarmnn_1_1_stack_descriptor.xhtml#a2bea87b470268bb0b73457c3733dbc04">armnn::StackDescriptor::m_InputShape</a></div><div class="ttdeci">TensorShape m_InputShape</div><div class="ttdoc">Required shape of all input tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01050">Descriptors.hpp:1050</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00402">Graph.hpp:402</a></div></div> +<div class="ttc" id="structarmnn_1_1_fake_quantization_descriptor_xhtml_a4c14a8e0d126891dd0c38e7584312bfd"><div class="ttname"><a href="structarmnn_1_1_fake_quantization_descriptor.xhtml#a4c14a8e0d126891dd0c38e7584312bfd">armnn::FakeQuantizationDescriptor::m_Min</a></div><div class="ttdeci">float m_Min</div><div class="ttdoc">Minimum value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00717">Descriptors.hpp:717</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">armnn::Pooling2dDescriptor::m_PoolWidth</a></div><div class="ttdeci">uint32_t m_PoolWidth</div><div class="ttdoc">Pooling width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00373">Descriptors.hpp:373</a></div></div> +<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::QLstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01193">Descriptors.hpp:1193</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00408">Descriptors.hpp:408</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::DepthwiseConvolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00490">Descriptors.hpp:490</a></div></div> +<div class="ttc" id="_lstm_test_impl_8cpp_xhtml_a3ca648bd28b5f0b835868282409b3458"><div class="ttname"><a href="_lstm_test_impl_8cpp.xhtml#a3ca648bd28b5f0b835868282409b3458">QLstmTest</a></div><div class="ttdeci">LayerTestResult< int8_t, 2 > QLstmTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_test_impl_8cpp_source.xhtml#l02894">LstmTestImpl.cpp:2894</a></div></div> +<div class="ttc" id="structarmnn_1_1_slice_descriptor_xhtml_ab52cabf19232290fa6b49828ba957ac0"><div class="ttname"><a href="structarmnn_1_1_slice_descriptor.xhtml#ab52cabf19232290fa6b49828ba957ac0">armnn::SliceDescriptor::m_Size</a></div><div class="ttdeci">std::vector< unsigned int > m_Size</div><div class="ttdoc">Size of the slice in each dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01020">Descriptors.hpp:1020</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6"><div class="ttname"><a href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a></div><div class="ttdoc">The padding fields don&#39;t count and are ignored. </div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a8c29d6ea9b4186d69aad5961c910939c"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a8c29d6ea9b4186d69aad5961c910939c">armnn::Pooling2dDescriptor::m_PaddingMethod</a></div><div class="ttdeci">PaddingMethod m_PaddingMethod</div><div class="ttdoc">The padding method to be used. (Exclude, IgnoreValue). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00383">Descriptors.hpp:383</a></div></div> +<div class="ttc" id="structarmnn_1_1_arg_min_max_descriptor_xhtml_ab1ae6f520bb1a4da191a0ae907477f23"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml#ab1ae6f520bb1a4da191a0ae907477f23">armnn::ArgMinMaxDescriptor::m_Function</a></div><div class="ttdeci">ArgMinMaxFunction m_Function</div><div class="ttdoc">Specify if the function is to find Min or Max. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00070">Descriptors.hpp:70</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7e2f87544b8bc7e497e1dec8d3ca4055"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7e2f87544b8bc7e497e1dec8d3ca4055">armnn::DetectionPostProcessDescriptor::m_DetectionsPerClass</a></div><div class="ttdeci">uint32_t m_DetectionsPerClass</div><div class="ttdoc">Detections per classes, used in Regular NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00547">Descriptors.hpp:547</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::BatchToSpaceNdDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00700">Descriptors.hpp:700</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">armnn::ActivationFunction::Abs</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::Pooling2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00369">Descriptors.hpp:369</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::Convolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00440">Descriptors.hpp:440</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div> +<div class="ttc" id="_addition_test_impl_8cpp_xhtml_a5e9b2ce84031d422f4d7c3e8f5b50caa"><div class="ttname"><a href="_addition_test_impl_8cpp.xhtml#a5e9b2ce84031d422f4d7c3e8f5b50caa">AdditionTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > AdditionTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_addition_test_impl_8cpp_source.xhtml#l00022">AdditionTestImpl.cpp:22</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="structarmnn_1_1_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::Convolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation along y axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00452">Descriptors.hpp:452</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_depth_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml">armnn::SpaceToDepthDescriptor</a></div><div class="ttdoc">A SpaceToDepthDescriptor for the SpaceToDepthLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00884">Descriptors.hpp:884</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_xhtml_a85f98c94e11f65a6b73f831735c040f3"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a85f98c94e11f65a6b73f831735c040f3">armnn::SpaceToBatchNdDescriptor::m_PadList</a></div><div class="ttdeci">std::vector< std::pair< unsigned int, unsigned int > > m_PadList</div><div class="ttdoc">Specifies the padding values for the input dimension: heightPad{top, bottom} widthPad{left, right}. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00878">Descriptors.hpp:878</a></div></div> +<div class="ttc" id="_internal_types_8hpp_xhtml"><div class="ttname"><a href="_internal_types_8hpp.xhtml">InternalTypes.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::DepthwiseConvolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation factor value for height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00504">Descriptors.hpp:504</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">armnn::BatchToSpaceNdDescriptor</a></div><div class="ttdoc">A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00673">Descriptors.hpp:673</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::Pooling2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00377">Descriptors.hpp:377</a></div></div> +<div class="ttc" id="structarmnn_1_1_permute_descriptor_xhtml_a14433af2b223695b40d8c8f8ba2ebb8f"><div class="ttname"><a href="structarmnn_1_1_permute_descriptor.xhtml#a14433af2b223695b40d8c8f8ba2ebb8f">armnn::PermuteDescriptor::m_DimMappings</a></div><div class="ttdeci">PermutationVector m_DimMappings</div><div class="ttdoc">Indicates how to translate tensor elements from a given source into the target destination, when source and target potentially have different memory layouts e.g. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00135">Descriptors.hpp:135</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml">armnn::ResizeDescriptor</a></div><div class="ttdoc">A ResizeDescriptor for the ResizeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00794">Descriptors.hpp:794</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a9ae2c9796692ebeafe19a4d3f09c8ea8"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a9ae2c9796692ebeafe19a4d3f09c8ea8">armnn::DetectionPostProcessDescriptor::m_MaxClassesPerDetection</a></div><div class="ttdeci">uint32_t m_MaxClassesPerDetection</div><div class="ttdoc">Maximum numbers of classes per detection, used in Fast NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00545">Descriptors.hpp:545</a></div></div> +<div class="ttc" id="structarmnn_1_1_mean_descriptor_xhtml_a1f0d67b087c491248bd1cde3ff995a95"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">armnn::MeanDescriptor::m_Axis</a></div><div class="ttdeci">std::vector< unsigned int > m_Axis</div><div class="ttdoc">Values for the dimensions to reduce. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00969">Descriptors.hpp:969</a></div></div> +<div class="ttc" id="structarmnn_1_1_stack_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a></div><div class="ttdoc">A StackDescriptor for the StackLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01024">Descriptors.hpp:1024</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::SpaceToBatchNdDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00880">Descriptors.hpp:880</a></div></div> +<div class="ttc" id="structarmnn_1_1_reshape_descriptor_xhtml_a1178f4dafdda81f59c15145ec327f7d9"><div class="ttname"><a href="structarmnn_1_1_reshape_descriptor.xhtml#a1178f4dafdda81f59c15145ec327f7d9">armnn::ReshapeDescriptor::m_TargetShape</a></div><div class="ttdeci">TensorShape m_TargetShape</div><div class="ttdoc">Target shape value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00848">Descriptors.hpp:848</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">armnn::Pooling2dDescriptor::m_PoolHeight</a></div><div class="ttdeci">uint32_t m_PoolHeight</div><div class="ttdoc">Pooling height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00375">Descriptors.hpp:375</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::Convolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00442">Descriptors.hpp:442</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae72089bcab60ac175557f4241b16a014"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">armnn::DetectionPostProcessDescriptor::m_MaxDetections</a></div><div class="ttdeci">uint32_t m_MaxDetections</div><div class="ttdoc">Maximum numbers of detections. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00543">Descriptors.hpp:543</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00446">Descriptors.hpp:446</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::DepthwiseConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00498">Descriptors.hpp:498</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a53c8a7f33a40e1e240256bcfcf41b101"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a53c8a7f33a40e1e240256bcfcf41b101">armnn::DetectionPostProcessDescriptor::m_NmsIouThreshold</a></div><div class="ttdeci">float m_NmsIouThreshold</div><div class="ttdoc">Intersection over union threshold. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00551">Descriptors.hpp:551</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml">armnn::LstmDescriptor</a></div><div class="ttdoc">An LstmDescriptor for the LstmLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00911">Descriptors.hpp:911</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::Pooling2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00367">Descriptors.hpp:367</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::DepthwiseConvolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation factor value for width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00502">Descriptors.hpp:502</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::DepthwiseConvolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00494">Descriptors.hpp:494</a></div></div> +<div class="ttc" id="structarmnn_1_1_slice_descriptor_xhtml_a4939f00778f08d6c6fec6f74c0a59b7e"><div class="ttname"><a href="structarmnn_1_1_slice_descriptor.xhtml#a4939f00778f08d6c6fec6f74c0a59b7e">armnn::SliceDescriptor::m_Begin</a></div><div class="ttdeci">std::vector< unsigned int > m_Begin</div><div class="ttdoc">Beginning indices of the slice in each dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01017">Descriptors.hpp:1017</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a02e143524aefddd40b485fcf7dea6696"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">armnn::BatchToSpaceNdDescriptor::m_BlockShape</a></div><div class="ttdeci">std::vector< unsigned int > m_BlockShape</div><div class="ttdoc">Block shape values. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00696">Descriptors.hpp:696</a></div></div> +<div class="ttc" id="structarmnn_1_1_l2_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.xhtml">armnn::L2NormalizationDescriptor</a></div><div class="ttdoc">A L2NormalizationDescriptor for the L2NormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00607">Descriptors.hpp:607</a></div></div> +<div class="ttc" id="_graph_8hpp_xhtml"><div class="ttname"><a href="_graph_8hpp.xhtml">Graph.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_arg_min_max_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a></div><div class="ttdoc">An ArgMinMaxDescriptor for ArgMinMaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00056">Descriptors.hpp:56</a></div></div> +<div class="ttc" id="structarmnn_1_1_origins_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_origins_descriptor.xhtml">armnn::OriginsDescriptor</a></div><div class="ttdoc">An OriginsDescriptor for the ConcatLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00163">Descriptors.hpp:163</a></div></div> +<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml">armnn::FullyConnectedDescriptor</a></div><div class="ttdoc">A FullyConnectedDescriptor for the FullyConnectedLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00389">Descriptors.hpp:389</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_validation_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer_validation_exception.xhtml">armnn::LayerValidationException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00105">Exceptions.hpp:105</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div> +<div class="ttc" id="structarmnn_1_1_fake_quantization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fake_quantization_descriptor.xhtml">armnn::FakeQuantizationDescriptor</a></div><div class="ttdoc">A FakeQuantizationDescriptor for the FakeQuantizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00704">Descriptors.hpp:704</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_adf57837d00e8352d9b5cc5ab1fb5fee9af6486a22a9bb11959bfae60a3e5174b1"><div class="ttname"><a href="namespacearmnn.xhtml#adf57837d00e8352d9b5cc5ab1fb5fee9af6486a22a9bb11959bfae60a3e5174b1">armnn::ShapeInferenceMethod::ValidateOnly</a></div><div class="ttdoc">Validate all output shapes. </div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_adcf5037208faac36c0788239a073f75c"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">armnn::ResizeDescriptor::m_TargetWidth</a></div><div class="ttdeci">uint32_t m_TargetWidth</div><div class="ttdoc">Target width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00816">Descriptors.hpp:816</a></div></div> +<div class="ttc" id="structarmnn_1_1_gather_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_gather_descriptor.xhtml">armnn::GatherDescriptor</a></div><div class="ttdoc">A GatherDescriptor for the GatherLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00742">Descriptors.hpp:742</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00943">Descriptors.hpp:943</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a3a04b0ccee4bb2f21721ee5045e83df4"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a3a04b0ccee4bb2f21721ee5045e83df4">armnn::DetectionPostProcessDescriptor::m_NumClasses</a></div><div class="ttdeci">uint32_t m_NumClasses</div><div class="ttdoc">Number of classes. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00553">Descriptors.hpp:553</a></div></div> +<div class="ttc" id="_lstm_test_impl_8cpp_xhtml_a8d9469ec08347dd451d782f102a6c8fa"><div class="ttname"><a href="_lstm_test_impl_8cpp.xhtml#a8d9469ec08347dd451d782f102a6c8fa">QuantizedLstmTest</a></div><div class="ttdeci">LayerTestResult< uint8_t, 2 > QuantizedLstmTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_test_impl_8cpp_source.xhtml#l02877">LstmTestImpl.cpp:2877</a></div></div> +<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml">armnn::QLstmDescriptor</a></div><div class="ttdoc">A QLstmDescriptor for the QLstmLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01153">Descriptors.hpp:1153</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7ed9bc7c26df67d274d5dd4cd83adf0f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">armnn::DetectionPostProcessDescriptor::m_UseRegularNms</a></div><div class="ttdeci">bool m_UseRegularNms</div><div class="ttdoc">Use Regular NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00555">Descriptors.hpp:555</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a10d15f3df1ab52b3b915a4be1dbf386b"><div class="ttname"><a href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">armnn::BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00268">ConstTensorLayerVisitor.cpp:268</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_xhtml_a02e143524aefddd40b485fcf7dea6696"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">armnn::SpaceToBatchNdDescriptor::m_BlockShape</a></div><div class="ttdeci">std::vector< unsigned int > m_BlockShape</div><div class="ttdoc">Block shape value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00875">Descriptors.hpp:875</a></div></div> +<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_a0d53caff836b84204adbd1c28752a201"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#a0d53caff836b84204adbd1c28752a201">armnn::StridedSliceDescriptor::m_Stride</a></div><div class="ttdeci">std::vector< int > m_Stride</div><div class="ttdoc">Stride values for the input that will be sliced. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01119">Descriptors.hpp:1119</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00025">Descriptors.hpp:25</a></div></div> +<div class="ttc" id="structarmnn_1_1_stack_descriptor_xhtml_aed6086070440ceb94129bef06f70173f"><div class="ttname"><a href="structarmnn_1_1_stack_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">armnn::StackDescriptor::m_NumInputs</a></div><div class="ttdeci">uint32_t m_NumInputs</div><div class="ttdoc">Number of input tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01048">Descriptors.hpp:1048</a></div></div> +<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a46c3fa15c46fb0d1dcdc24d0ea5cb5cd"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">armnn::ResizeDescriptor::m_TargetHeight</a></div><div class="ttdeci">uint32_t m_TargetHeight</div><div class="ttdoc">Target height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00818">Descriptors.hpp:818</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00935">Descriptors.hpp:935</a></div></div> +<div class="ttc" id="structarmnn_1_1_slice_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_slice_descriptor.xhtml">armnn::SliceDescriptor</a></div><div class="ttdoc">A SliceDescriptor for the SliceLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01001">Descriptors.hpp:1001</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00448">Descriptors.hpp:448</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="_convert_bf16_to_fp32_test_impl_8cpp_xhtml_a72c71ccbf53cf4db9727ec413f9ff2b3"><div class="ttname"><a href="_convert_bf16_to_fp32_test_impl_8cpp.xhtml#a72c71ccbf53cf4db9727ec413f9ff2b3">ConvertBf16ToFp32Test</a></div><div class="ttdeci">LayerTestResult< float, 4 > ConvertBf16ToFp32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_convert_bf16_to_fp32_test_impl_8cpp_source.xhtml#l00013">ConvertBf16ToFp32TestImpl.cpp:13</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_depth_descriptor_xhtml_a6c6b8957f1e176867e5fb05b1a1a1486"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">armnn::SpaceToDepthDescriptor::m_BlockSize</a></div><div class="ttdeci">unsigned int m_BlockSize</div><div class="ttdoc">Scalar specifying the input block size. It must be >= 1. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00901">Descriptors.hpp:901</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_aa61510cbd529870182e918ac6e8b9d72"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#aa61510cbd529870182e918ac6e8b9d72">armnn::DetectionPostProcessDescriptor::m_ScaleH</a></div><div class="ttdeci">float m_ScaleH</div><div class="ttdoc">Center size encoding scale height. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00563">Descriptors.hpp:563</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_comparison_descriptor_xhtml_a865dc4f43cb0ff01a1dcf78036912fd1"><div class="ttname"><a href="structarmnn_1_1_comparison_descriptor.xhtml#a865dc4f43cb0ff01a1dcf78036912fd1">armnn::ComparisonDescriptor::m_Operation</a></div><div class="ttdeci">ComparisonOperation m_Operation</div><div class="ttdoc">Specifies the comparison operation to execute. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00094">Descriptors.hpp:94</a></div></div> +<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_aa68194dd6258ab5b04123005a066ea25"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#aa68194dd6258ab5b04123005a066ea25">armnn::StridedSliceDescriptor::m_End</a></div><div class="ttdeci">std::vector< int > m_End</div><div class="ttdoc">End values for the input that will be sliced. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01117">Descriptors.hpp:1117</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml">armnn::SpaceToBatchNdDescriptor</a></div><div class="ttdoc">A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00852">Descriptors.hpp:852</a></div></div> +<div class="ttc" id="structarmnn_1_1_backend_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_backend_options.xhtml">armnn::BackendOptions</a></div><div class="ttdoc">Struct for the users to pass backend specific options. </div><div class="ttdef"><b>Definition:</b> <a href="_backend_options_8hpp_source.xhtml#l00020">BackendOptions.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74"><div class="ttname"><a href="namespacearmnn.xhtml#a8e1f31031ad31cd8cc22d7c9daa32681af60357a8d17e45793298323f1b372a74">armnn::Dimensionality::Scalar</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::Convolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation along x axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00450">Descriptors.hpp:450</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_depth_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::SpaceToDepthDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00904">Descriptors.hpp:904</a></div></div> +<div class="ttc" id="_profiler_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00941">Descriptors.hpp:941</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ac14705405cbcdd580df613de6766fe65"><div class="ttname"><a href="namespacearmnn.xhtml#ac14705405cbcdd580df613de6766fe65">armnn::LogSoftmaxDescriptor</a></div><div class="ttdeci">SoftmaxDescriptor LogSoftmaxDescriptor</div><div class="ttdoc">A LogSoftmaxDescriptor for the LogSoftmaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00158">Descriptors.hpp:158</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a0031997bf43bd2747656c31e4977793a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">armnn::Pooling2dDescriptor::m_PoolType</a></div><div class="ttdeci">PoolingAlgorithm m_PoolType</div><div class="ttdoc">The pooling algorithm to use (Max. Average, L2). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00363">Descriptors.hpp:363</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::DepthwiseConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00500">Descriptors.hpp:500</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a3941f674c071c9503e00d2b59e92e454"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a3941f674c071c9503e00d2b59e92e454">armnn::BatchToSpaceNdDescriptor::m_Crops</a></div><div class="ttdeci">std::vector< std::pair< unsigned int, unsigned int > > m_Crops</div><div class="ttdoc">The values to crop from the input dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00698">Descriptors.hpp:698</a></div></div> +<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::QLstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01195">Descriptors.hpp:1195</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_affb5b68b3eba3ed45a06c7cde7781962"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#affb5b68b3eba3ed45a06c7cde7781962">armnn::Pooling2dDescriptor::m_OutputShapeRounding</a></div><div class="ttdeci">OutputShapeRounding m_OutputShapeRounding</div><div class="ttdoc">The rounding method for the output shape. (Floor, Ceiling). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00381">Descriptors.hpp:381</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.xhtml#l00013">InputLayer.hpp:13</a></div></div> +<div class="ttc" id="_fully_connected_layer_8hpp_xhtml"><div class="ttname"><a href="_fully_connected_layer_8hpp.xhtml">FullyConnectedLayer.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_mean_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml">armnn::MeanDescriptor</a></div><div class="ttdoc">A MeanDescriptor for the MeanLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00951">Descriptors.hpp:951</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_adf57837d00e8352d9b5cc5ab1fb5fee9a5dd7c525cb1500a2181fd4cc079d7acb"><div class="ttname"><a href="namespacearmnn.xhtml#adf57837d00e8352d9b5cc5ab1fb5fee9a5dd7c525cb1500a2181fd4cc079d7acb">armnn::ShapeInferenceMethod::InferAndValidate</a></div><div class="ttdoc">Infer missing output shapes and validate all output shapes. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_descriptor.xhtml">armnn::TransposeDescriptor</a></div><div class="ttdoc">A TransposeDescriptor for the TransposeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01263">Descriptors.hpp:1263</a></div></div> +<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml">armnn::StridedSliceDescriptor</a></div><div class="ttdoc">A StridedSliceDescriptor for the StridedSliceLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01076">Descriptors.hpp:1076</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="structarmnn_1_1_arg_min_max_descriptor_xhtml_a214c3636fdf0ea5bac8edb42d0e6c7f0"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml#a214c3636fdf0ea5bac8edb42d0e6c7f0">armnn::ArgMinMaxDescriptor::m_Axis</a></div><div class="ttdeci">int m_Axis</div><div class="ttdoc">Axis to reduce across the input tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00072">Descriptors.hpp:72</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a5e1dc69443b64ad16b669388a6023f7a"><div class="ttname"><a href="namespacearmnn.xhtml#a5e1dc69443b64ad16b669388a6023f7a">armnn::SpaceToDepth</a></div><div class="ttdeci">void SpaceToDepth(const TensorInfo &inputInfo, const TensorInfo &outputInfo, const SpaceToDepthDescriptor &params, Decoder< float > &inputData, Encoder< float > &outputData)</div><div class="ttdef"><b>Definition:</b> <a href="_space_to_depth_8cpp_source.xhtml#l00036">SpaceToDepth.cpp:36</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7a2156ec7d9c012ce00bbcc6afcb9028"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7a2156ec7d9c012ce00bbcc6afcb9028">armnn::DetectionPostProcessDescriptor::m_ScaleY</a></div><div class="ttdeci">float m_ScaleY</div><div class="ttdoc">Center size encoding scale y. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00559">Descriptors.hpp:559</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a4392dd6b4862cc9cf95ae8f1001ba592"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a4392dd6b4862cc9cf95ae8f1001ba592">armnn::DetectionPostProcessDescriptor::m_NmsScoreThreshold</a></div><div class="ttdeci">float m_NmsScoreThreshold</div><div class="ttdoc">NMS score threshold. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00549">Descriptors.hpp:549</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00329">Descriptors.hpp:329</a></div></div> +<div class="ttc" id="_activation_test_impl_8cpp_xhtml_afa1af28f33ae8978b6df0b170561f787"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#afa1af28f33ae8978b6df0b170561f787">AbsTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > AbsTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00817">ActivationTestImpl.cpp:817</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml">armnn::NormalizationDescriptor</a></div><div class="ttdoc">A NormalizationDescriptor for the NormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00567">Descriptors.hpp:567</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00511">Descriptors.hpp:511</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml">armnn::InstanceNormalizationDescriptor</a></div><div class="ttdoc">An InstanceNormalizationDescriptor for InstanceNormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00645">Descriptors.hpp:645</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00510">Network.cpp:510</a></div></div> +<div class="ttc" id="_rank_test_impl_8cpp_xhtml_a7856a1669cdb9bdc16e081f2864f0c1b"><div class="ttname"><a href="_rank_test_impl_8cpp.xhtml#a7856a1669cdb9bdc16e081f2864f0c1b">RankTest</a></div><div class="ttdeci">LayerTestResult< int32_t, 1 > RankTest(armnn::TensorInfo inputTensorInfo, boost::multi_array< T, n > input, armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_rank_test_impl_8cpp_source.xhtml#l00015">RankTestImpl.cpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_fake_quantization_descriptor_xhtml_ad3729c591f7bfda7ad9ef9927d8a1bd6"><div class="ttname"><a href="structarmnn_1_1_fake_quantization_descriptor.xhtml#ad3729c591f7bfda7ad9ef9927d8a1bd6">armnn::FakeQuantizationDescriptor::m_Max</a></div><div class="ttdeci">float m_Max</div><div class="ttdoc">Maximum value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00719">Descriptors.hpp:719</a></div></div> +<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::QLstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable CIFG (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01191">Descriptors.hpp:1191</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_descriptor_xhtml_a14433af2b223695b40d8c8f8ba2ebb8f"><div class="ttname"><a href="structarmnn_1_1_transpose_descriptor.xhtml#a14433af2b223695b40d8c8f8ba2ebb8f">armnn::TransposeDescriptor::m_DimMappings</a></div><div class="ttdeci">PermutationVector m_DimMappings</div><div class="ttdoc">Indicates how to translate tensor elements from a given source into the target destination, when source and target potentially have different memory layouts e.g. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01280">Descriptors.hpp:1280</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_af10fa7883e3579950f477bee92a64844"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">armnn::ActivationDescriptor::m_Function</a></div><div class="ttdeci">ActivationFunction m_Function</div><div class="ttdoc">The activation function to use (Sigmoid, TanH, Linear, ReLu, BoundedReLu, SoftReLu, LeakyReLu, Abs, Sqrt, Square, Elu). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00048">Descriptors.hpp:48</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Pooling2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00379">Descriptors.hpp:379</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00460">Descriptors.hpp:460</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml">armnn::BatchNormalizationDescriptor</a></div><div class="ttdoc">A BatchNormalizationDescriptor for the BatchNormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00626">Descriptors.hpp:626</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Convolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00438">Descriptors.hpp:438</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae7e8cbf71db6a490789ca6dcaa8deeaea78d811e98514cd165dda532286610fd2"><div class="ttname"><a href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeaea78d811e98514cd165dda532286610fd2">armnn::ArgMinMaxFunction::Min</a></div></div> +<div class="ttc" id="structarmnn_1_1_permute_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_permute_descriptor.xhtml">armnn::PermuteDescriptor</a></div><div class="ttdoc">A PermuteDescriptor for the PermuteLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00118">Descriptors.hpp:118</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::DepthwiseConvolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00492">Descriptors.hpp:492</a></div></div> +</div><!-- fragment --></div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_e0a84d05c80a2ef4231141dcbbeac5c8.xhtml">armnn</a></li><li class="navelem"><a class="el" href="dir_9d86fd1fbecbedf5bdb69c7e7235fe5f.xhtml">test</a></li><li class="navelem"><a class="el" href="_shape_inference_tests_8cpp.xhtml">ShapeInferenceTests.cpp</a></li> + <li class="footer">Generated on Thu Feb 25 2021 17:27:29 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + </ul> +</div> +</body> +</html> |