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diff --git a/20.02/_instance_normalization_test_impl_8cpp_source.xhtml b/20.02/_instance_normalization_test_impl_8cpp_source.xhtml new file mode 100644 index 0000000000..07886c86f0 --- /dev/null +++ b/20.02/_instance_normalization_test_impl_8cpp_source.xhtml @@ -0,0 +1,146 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/backends/backendsCommon/test/layerTests/InstanceNormalizationTestImpl.cpp Source File</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">20.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_instance_normalization_test_impl_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">InstanceNormalizationTestImpl.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_instance_normalization_test_impl_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 © 2019 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_instance_normalization_test_impl_8hpp.xhtml">InstanceNormalizationTestImpl.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_quantize_helper_8hpp.xhtml">QuantizeHelper.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</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="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="include_2armnn_2backends_2_i_backend_internal_8hpp.xhtml">armnn/backends/IBackendInternal.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_workload_factory_8hpp.xhtml">backendsCommon/WorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_data_layout_utils_8hpp.xhtml">backendsCommon/test/DataLayoutUtils.hpp</a>></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <<a class="code" href="_tensor_copy_utils_8hpp.xhtml">backendsCommon/test/TensorCopyUtils.hpp</a>></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <<a class="code" href="_workload_test_utils_8hpp.xhtml">backendsCommon/test/WorkloadTestUtils.hpp</a>></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <<a class="code" href="_tensor_helpers_8hpp.xhtml">test/TensorHelpers.hpp</a>></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> <span class="keyword">namespace</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> {</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> InstanceNormTestImpl(</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& inputTensorInfo,</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& outputTensorInfo,</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keyword">const</span> std::vector<float>& inputValues,</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keyword">const</span> std::vector<float>& expectedOutputValues,</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <a class="code" href="structarmnn_1_1_instance_normalization_queue_descriptor.xhtml">armnn::InstanceNormalizationQueueDescriptor</a> descriptor,</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keywordtype">float</span> qScale = 0.0f,</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  int32_t qOffset = 0)</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="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keyword">auto</span> inputTensor = MakeTensor<T, 4>(inputTensorInfo,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  armnnUtils::QuantizedVector<T>(inputValues, qScale, qOffset));</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> result(outputTensorInfo);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  armnnUtils::QuantizedVector<T>(expectedOutputValues, qScale, qOffset));</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>  std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);</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>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateInstanceNormalization(descriptor, info);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  inputHandle->Allocate();</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  outputHandle->Allocate();</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &inputTensor[0][0][0][0]);</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>  workload->Execute();</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>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&result.output[0][0][0][0], outputHandle.get());</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">return</span> result;</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> </div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> InstanceNormTest(</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="comment">// BatchSize: 2</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="comment">// Height: 2</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="comment">// Channels: 2</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputOutputShape{ 2, 2, 2, 2 };</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo(inputOutputShape, ArmnnType);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo(inputOutputShape, ArmnnType);</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>  std::vector<float> inputValues</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  {</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  0.f, 1.f,</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  0.f, 2.f,</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  0.f, 2.f,</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  0.f, 4.f,</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>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  1.f, -1.f,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  -1.f, 2.f,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="comment">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  -1.f, -2.f,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  1.f, 4.f</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>  std::vector<float> expectedOutputValues</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  {</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  0.f, -1.1470304f,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  0.f, -0.22940612f,</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  0.f, -0.22940612f,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  0.f, 1.6058424f,</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  0.99995005f, -0.7337929f,</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  -0.99995005f, 0.52413774f,</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="comment">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  -0.99995005f, -1.1531031f,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  0.99995005f, 1.3627582f</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  };</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>)</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  {</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(inputTensorInfo, inputValues);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(outputTensorInfo, expectedOutputValues);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  }</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <a class="code" href="structarmnn_1_1_instance_normalization_queue_descriptor.xhtml">armnn::InstanceNormalizationQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a> = 0.0001f;</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = 0.0f;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a5e078fd505aef7bccaa05c8058e096cc">m_Gamma</a> = 1.0f;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keywordflow">return</span> InstanceNormTestImpl<ArmnnType>(</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  workloadFactory,</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  memoryManager,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  inputTensorInfo,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  outputTensorInfo,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  inputValues,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  expectedOutputValues,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  descriptor);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> }</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> InstanceNormTest2(</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> {</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="comment">// BatchSize: 2</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="comment">// Height: 2</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">// Width: 2</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="comment">// Channels: 2</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> </div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputOutputShape{ 2, 2, 2, 2 };</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> </div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo(inputOutputShape, ArmnnType);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo(inputOutputShape, ArmnnType);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  std::vector<float> inputValues</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  {</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  0.f, 1.f,</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  0.f, 2.f,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> </div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  0.f, 2.f,</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  0.f, 4.f,</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  1.f, -1.f,</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  -1.f, 2.f,</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> </div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="comment">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  -1.f, -2.f,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  1.f, 4.f</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  };</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> </div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  std::vector<float> expectedOutputValues</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>  <span class="comment">// Batch 0, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  10.f, 7.7059393f,</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="comment">// Batch 0, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  10.f, 9.541187f,</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// Batch 0, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  10.f, 9.541187f,</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="comment">// Batch 0, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  10.f, 13.211685f,</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="comment">// Batch 1, Height 0, Width 0 x Channel (2)</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  11.9999f, 8.532414f,</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="comment">// Batch 1, Height 0, Width 1 x Channel (2)</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  8.0001f, 11.048275f,</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="comment">// Batch 1, Height 1, Width 0 x Channel (2)</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  8.0001f, 7.693794f,</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="comment">// Batch 1, Height 1, Width 1 x Channel (2)</span></div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  11.9999f, 12.725516f</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> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>)</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="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(inputTensorInfo, inputValues);</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <a class="code" href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(outputTensorInfo, expectedOutputValues);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  }</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="code" href="structarmnn_1_1_instance_normalization_queue_descriptor.xhtml">armnn::InstanceNormalizationQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a> = 0.0001f;</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = 10.0f;</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a5e078fd505aef7bccaa05c8058e096cc">m_Gamma</a> = 2.0f;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</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>  <span class="keywordflow">return</span> InstanceNormTestImpl<ArmnnType>(</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  workloadFactory,</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  memoryManager,</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  inputTensorInfo,</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  outputTensorInfo,</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  inputValues,</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  expectedOutputValues,</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  descriptor);</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> } <span class="comment">// anonymous namespace</span></div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div><div class="line"><a name="l00237"></a><span class="lineno"><a class="line" href="_instance_normalization_test_impl_8hpp.xhtml#af6fbb2d172f7285f17c54b60a61d198b"> 237</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_instance_normalization_test_impl_8cpp.xhtml#af6fbb2d172f7285f17c54b60a61d198b">InstanceNormFloat32Test</a>(</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> {</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordflow">return</span> InstanceNormTest<armnn::DataType::Float32>(workloadFactory, memoryManager, dataLayout);</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> }</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> </div><div class="line"><a name="l00245"></a><span class="lineno"><a class="line" href="_instance_normalization_test_impl_8hpp.xhtml#a083992b1851c7681a4b9bd06ba2f5aa6"> 245</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<armnn::Half, 4></a> <a class="code" href="_instance_normalization_test_impl_8cpp.xhtml#a083992b1851c7681a4b9bd06ba2f5aa6">InstanceNormFloat16Test</a>(</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> {</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordflow">return</span> InstanceNormTest<armnn::DataType::Float16>(workloadFactory, memoryManager, dataLayout);</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> </div><div class="line"><a name="l00253"></a><span class="lineno"><a class="line" href="_instance_normalization_test_impl_8hpp.xhtml#a12dcbf5945d7d734b143172ff3129390"> 253</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_instance_normalization_test_impl_8cpp.xhtml#a12dcbf5945d7d734b143172ff3129390">InstanceNormFloat32Test2</a>(</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> {</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keywordflow">return</span> InstanceNormTest2<armnn::DataType::Float32>(workloadFactory, memoryManager, dataLayout);</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> }</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> </div><div class="line"><a name="l00261"></a><span class="lineno"><a class="line" href="_instance_normalization_test_impl_8hpp.xhtml#aa199df9ca7c476e9bf613a3c3f8c7b56"> 261</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<armnn::Half, 4></a> <a class="code" href="_instance_normalization_test_impl_8cpp.xhtml#aa199df9ca7c476e9bf613a3c3f8c7b56">InstanceNormFloat16Test2</a>(</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> {</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keywordflow">return</span> InstanceNormTest2<armnn::DataType::Float16>(workloadFactory, memoryManager, dataLayout);</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> }</div><div class="ttc" id="structarmnn_1_1_instance_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_queue_descriptor.xhtml">armnn::InstanceNormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00311">WorkloadData.hpp:311</a></div></div> +<div class="ttc" id="_tensor_copy_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_copy_utils_8hpp.xhtml">TensorCopyUtils.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00049">Types.hpp:49</a></div></div> +<div class="ttc" id="_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_workload_factory_8hpp.xhtml">WorkloadFactory.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="_quantize_helper_8hpp_xhtml"><div class="ttname"><a href="_quantize_helper_8hpp.xhtml">QuantizeHelper.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.xhtml#l00021">WorkloadFactory.hpp:21</a></div></div> +<div class="ttc" id="_workload_test_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_test_utils_8hpp.xhtml">WorkloadTestUtils.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml_a5e078fd505aef7bccaa05c8058e096cc"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a5e078fd505aef7bccaa05c8058e096cc">armnn::InstanceNormalizationDescriptor::m_Gamma</a></div><div class="ttdeci">float m_Gamma</div><div class="ttdoc">Gamma, the scale scalar value applied for the normalized tensor. Defaults to 1.0. ...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00647">Descriptors.hpp:647</a></div></div> +<div class="ttc" id="_instance_normalization_test_impl_8cpp_xhtml_af6fbb2d172f7285f17c54b60a61d198b"><div class="ttname"><a href="_instance_normalization_test_impl_8cpp.xhtml#af6fbb2d172f7285f17c54b60a61d198b">InstanceNormFloat32Test</a></div><div class="ttdeci">LayerTestResult< float, 4 > InstanceNormFloat32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_instance_normalization_test_impl_8cpp_source.xhtml#l00237">InstanceNormalizationTestImpl.cpp:237</a></div></div> +<div class="ttc" id="_instance_normalization_test_impl_8hpp_xhtml"><div class="ttname"><a href="_instance_normalization_test_impl_8hpp.xhtml">InstanceNormalizationTestImpl.hpp</a></div></div> +<div class="ttc" id="_instance_normalization_test_impl_8cpp_xhtml_a083992b1851c7681a4b9bd06ba2f5aa6"><div class="ttname"><a href="_instance_normalization_test_impl_8cpp.xhtml#a083992b1851c7681a4b9bd06ba2f5aa6">InstanceNormFloat16Test</a></div><div class="ttdeci">LayerTestResult< armnn::Half, 4 > InstanceNormFloat16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_instance_normalization_test_impl_8cpp_source.xhtml#l00245">InstanceNormalizationTestImpl.cpp:245</a></div></div> +<div class="ttc" id="_resolve_type_8hpp_xhtml"><div class="ttname"><a href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="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_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00049">WorkloadData.hpp:49</a></div></div> +<div class="ttc" id="_tensor_helpers_8hpp_xhtml"><div class="ttname"><a href="_tensor_helpers_8hpp.xhtml">TensorHelpers.hpp</a></div></div> +<div class="ttc" id="include_2armnn_2backends_2_i_backend_internal_8hpp_xhtml"><div class="ttname"><a href="include_2armnn_2backends_2_i_backend_internal_8hpp.xhtml">IBackendInternal.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">armnn::InstanceNormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Epsilon, small scalar value added to variance to avoid dividing by zero. Defaults to 1e-12f...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00651">Descriptors.hpp:651</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_backend_internal_xhtml_a693b40e6b94e958836aeb0410ca186bd"><div class="ttname"><a href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a></div><div class="ttdeci">std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.xhtml#l00090">IBackendInternal.hpp:90</a></div></div> +<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::InstanceNormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00653">Descriptors.hpp:653</a></div></div> +<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml_a8275d51ef9a584feb95726ea0522f6e5"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">armnn::InstanceNormalizationDescriptor::m_Beta</a></div><div class="ttdeci">float m_Beta</div><div class="ttdoc">Beta, the offset scalar value applied for the normalized tensor. Defaults to 1.0. ...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00649">Descriptors.hpp:649</a></div></div> +<div class="ttc" id="_cpu_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.xhtml">CpuTensorHandle.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div> +<div class="ttc" id="_instance_normalization_test_impl_8cpp_xhtml_aa199df9ca7c476e9bf613a3c3f8c7b56"><div class="ttname"><a href="_instance_normalization_test_impl_8cpp.xhtml#aa199df9ca7c476e9bf613a3c3f8c7b56">InstanceNormFloat16Test2</a></div><div class="ttdeci">LayerTestResult< armnn::Half, 4 > InstanceNormFloat16Test2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_instance_normalization_test_impl_8cpp_source.xhtml#l00261">InstanceNormalizationTestImpl.cpp:261</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +<div class="ttc" id="_data_layout_utils_8hpp_xhtml"><div class="ttname"><a href="_data_layout_utils_8hpp.xhtml">DataLayoutUtils.hpp</a></div></div> +<div class="ttc" id="_instance_normalization_test_impl_8cpp_xhtml_a12dcbf5945d7d734b143172ff3129390"><div class="ttname"><a href="_instance_normalization_test_impl_8cpp.xhtml#a12dcbf5945d7d734b143172ff3129390">InstanceNormFloat32Test2</a></div><div class="ttdeci">LayerTestResult< float, 4 > InstanceNormFloat32Test2(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_instance_normalization_test_impl_8cpp_source.xhtml#l00253">InstanceNormalizationTestImpl.cpp:253</a></div></div> +<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="_data_layout_utils_8hpp_xhtml_a1452f049aef30409b3b649af2be7ff82"><div class="ttname"><a href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a></div><div class="ttdeci">void PermuteTensorNhwcToNchw(armnn::TensorInfo &tensorInfo, std::vector< T > &tensorData)</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_utils_8hpp_source.xhtml#l00026">DataLayoutUtils.hpp:26</a></div></div> +</div><!-- fragment --></div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.xhtml">backendsCommon</a></li><li class="navelem"><a class="el" href="dir_28bfe507f7e135bdae07c2a6b7f66696.xhtml">test</a></li><li class="navelem"><a class="el" href="dir_99a30439342d160875b21dac3498ad7f.xhtml">layerTests</a></li><li class="navelem"><a class="el" href="_instance_normalization_test_impl_8cpp.xhtml">InstanceNormalizationTestImpl.cpp</a></li> + <li class="footer">Generated on Fri Mar 13 2020 16:09:11 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + </ul> +</div> +</body> +</html> |