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| author | Nikhil Raj <nikhil.raj@arm.com> | 2021-11-17 13:16:45 +0000 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2021-11-17 13:16:45 +0000 |
| commit | 9aed8fb43441228343b925b42464a55042c47ca0 (patch) | |
| tree | 4c34534eea1c8e82655ac1f60e3633b9618cc40d /21.11/_conv3d_test_impl_8cpp_source.xhtml | |
| parent | f86be93b7492b381370cae7bf71eca8572a0cbae (diff) | |
| download | armnn-9aed8fb43441228343b925b42464a55042c47ca0.tar.gz | |
IVGCVSW-6040 Update 21.11 Doxygen Documents
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: Ia36ec98c4bebc27a69103911ea3409cd7db587a5
Diffstat (limited to '21.11/_conv3d_test_impl_8cpp_source.xhtml')
| -rw-r--r-- | 21.11/_conv3d_test_impl_8cpp_source.xhtml | 203 |
1 files changed, 203 insertions, 0 deletions
diff --git a/21.11/_conv3d_test_impl_8cpp_source.xhtml b/21.11/_conv3d_test_impl_8cpp_source.xhtml new file mode 100644 index 0000000000..b518a2216b --- /dev/null +++ b/21.11/_conv3d_test_impl_8cpp_source.xhtml @@ -0,0 +1,203 @@ +<!-- 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/Conv3dTestImpl.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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">21.11</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(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('_conv3d_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">Conv3dTestImpl.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_conv3d_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 © 2021 Arm Ltd and Contributors. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_conv3d_test_impl_8hpp.xhtml">Conv3dTestImpl.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> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_data_layout_indexed_8hpp.xhtml">armnnUtils/DataLayoutIndexed.hpp</a>></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="_tensor_handle_8hpp.xhtml">backendsCommon/TensorHandle.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_data_layout_utils_8hpp.xhtml">backendsCommon/test/DataLayoutUtils.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</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="l00016"></a><span class="lineno"> 16</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="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <<a class="code" href="_tensor_helpers_8hpp.xhtml">test/TensorHelpers.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="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.xhtml">armnnUtils</a>;</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="comment">//</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment">// Helper templates</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="comment">//</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="comment">// Helper template that returns a quantized bias depending on the number of output channels.</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00028"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#ac29da01384d6955a5788945352713a21"> 28</a></span> std::vector<T> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#ac29da01384d6955a5788945352713a21">GetBiasData</a>(<span class="keywordtype">bool</span> biasEnabled, <span class="keywordtype">float</span> qScale, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo, <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> {</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keywordflow">if</span>(!biasEnabled)</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="keywordflow">return</span> std::vector<T>();</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>  <span class="keywordflow">else</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  {</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml">armnnUtils::DataLayoutIndexed</a> dataLayoutIndexed(layout);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[dataLayoutIndexed.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</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="keywordflow">switch</span> (outputChannels)</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  {</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  {</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordflow">return</span> QuantizedVector<T>({2}, qScale, 0);</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">case</span> 2:</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordflow">default</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="keywordflow">return</span> QuantizedVector<T>({0, 2}, qScale, 0);</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>  }</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> }</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="comment">// Modifies a std::vector in-place using a specified bias.</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="keyword">template</span><<span class="keyword">typename</span> T, <span class="keyword">typename</span> B></div><div class="line"><a name="l00056"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#a41dde9c18d90c8dea2980e477d22a7fe"> 56</a></span> <span class="keywordtype">void</span> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a41dde9c18d90c8dea2980e477d22a7fe">ApplyBiasToData</a>(std::vector<T>& v, <span class="keyword">const</span> std::vector<B>& bias,</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keywordtype">float</span> vScale, int32_t vOffset,</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keywordtype">float</span> bScale, int32_t bOffset)</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>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>((armnn::IsQuantizedType<T>() && vScale != 0.0f) || (!armnn::IsQuantizedType<T>()),</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="stringliteral">"Invalid type and parameter combination."</span>);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>((armnn::IsQuantizedType<B>() && bScale != 0.0f) || (!armnn::IsQuantizedType<B>()),</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="stringliteral">"Invalid type and parameter combination."</span>);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">for</span> (uint32_t i = 0; i < bias.size(); ++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>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = i; j < v.size(); j+=bias.size())</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="comment">// Note we need to dequantize and re-quantize the image value and the bias.</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordtype">float</span> dBias = <a class="code" href="namespacearmnn_utils.xhtml#a5135dc1ce7a8aeb97623c1a92c5a3543">SelectiveDequantize</a>(bias[i], bScale, bOffset);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  T& outRef = v[j];</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordtype">float</span> dOutput = <a class="code" href="namespacearmnn_utils.xhtml#a5135dc1ce7a8aeb97623c1a92c5a3543">SelectiveDequantize</a>(outRef, vScale, vOffset);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  outRef = SelectiveQuantize<T>(dOutput + dBias, vScale, vOffset);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  }</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  }</div><div class="line"><a name="l00077"></a><span class="lineno"> 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">// Set the quantization scale and offset values for data types.</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="keyword">template</span><armnn::DataType ArmnnType></div><div class="line"><a name="l00081"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#a2f8ee10580b676ec08de159a02ff217e"> 81</a></span> <span class="keywordtype">void</span> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a2f8ee10580b676ec08de159a02ff217e">SetScaleOffset</a>(<span class="keywordtype">float</span>& qScale, int32_t& qOffset)</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordflow">switch</span> (ArmnnType)</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  {</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</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>  qScale = 0.1f;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  qOffset = 128;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordflow">break</span>;</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="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>:</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  {</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  qScale = 0.1f;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  qOffset = 64;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordflow">break</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="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>:</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  {</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  qScale = 0.1f;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  qOffset = 0;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">break</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="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>:</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>:</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>:</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  {</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  qScale = 1.f;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  qOffset = 0;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  }</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  }</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> }</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment">// Create a vector from 0 to size and quantize (if required).</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00117"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#a9ca270ac2dc3cd87e835716606be9e65"> 117</a></span> std::vector<T> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a9ca270ac2dc3cd87e835716606be9e65">CreateQuantizedData</a>(int32_t size, <span class="keywordtype">float</span> qScale, int32_t qOffset)</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>  std::vector<float> data;</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keywordflow">for</span> (int32_t i = 0; i < size; ++i)</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  {</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  data.push_back(static_cast<float>(i));</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  }</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keywordflow">return</span> QuantizedVector<T>(data, qScale, qOffset);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> }</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> <span class="comment">// Create a vector from 0 to size divided and then quantized (if required) to create smaller floating point values.</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00130"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#a94612dea5289f32c0f065f248b412615"> 130</a></span> std::vector<T> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a94612dea5289f32c0f065f248b412615">CreateSmallQuantizedData</a>(int32_t size, <span class="keywordtype">float</span> divisor, <span class="keywordtype">float</span> qScale, int32_t qOffset)</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>  std::vector<float> data;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordflow">for</span> (int32_t i = 0; i < size; ++i)</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>  <span class="keywordtype">float</span> value = <span class="keyword">static_cast<</span><span class="keywordtype">float</span><span class="keyword">></span>(i);</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  data.push_back(value/divisor);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  }</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>  <span class="keywordflow">return</span> QuantizedVector<T>(data, qScale, qOffset);;</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> </div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment">//</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment">// Convolution3d implementations</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="comment">//</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="keyword">template</span><<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnBType,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="keyword">typename</span> T = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType></a>,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keyword">typename</span> <a class="code" href="_inference_test_image_8hpp.xhtml#a65983f8cb907d873f2328bb8307c296aa9d5ed678fe57bcca610140957afab571">B</a> = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnBType></a>></div><div class="line"><a name="l00150"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#aa8c767319f74f1b79ca1658b0cd0c8e0"> 150</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#aa8c767319f74f1b79ca1658b0cd0c8e0">SimpleConvolution3dTestImpl</a>(</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</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="l00153"></a><span class="lineno"> 153</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keyword">const</span> std::vector<T>& input,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keyword">const</span> std::vector<T>& kernel,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="keyword">const</span> std::vector<B>& bias,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keyword">const</span> std::vector<T>& outputExpected,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& inputShape,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& kernelShape,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& outputExpectedShape,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  int32_t qOffset,</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  uint32_t strideX = 1,</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  uint32_t strideY = 1,</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  uint32_t strideZ = 1,</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  uint32_t dilationX = 1,</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  uint32_t dilationY = 1,</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  uint32_t dilationZ = 1,</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  uint32_t padLeft = 0,</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  uint32_t padTop = 0,</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  uint32_t padRight = 0,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  uint32_t padBottom = 0,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  uint32_t padFront = 0,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  uint32_t padBack = 0)</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> {</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputNum = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(inputShape[0]);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputDepth = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(inputShape[1]);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(inputShape[2]);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(inputShape[3]);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(inputShape[4]);</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>  <span class="comment">// Conv3d weights/kernel layout: [D,H,W,I,O]</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernelDepth = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(kernelShape[0]);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernelHeight = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(kernelShape[1]);</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernelWidth = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(kernelShape[2]);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernelInChannels = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(kernelShape[3]);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernelOutChannels = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(kernelShape[4]);</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputNum = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(outputExpectedShape[0]);</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputDepth = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(outputExpectedShape[1]);</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(outputExpectedShape[2]);</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(outputExpectedShape[3]);</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(outputExpectedShape[4]);</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keywordtype">bool</span> biasEnabled = bias.size() > 0;</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="comment">// If a bias is used, its size must equal the number of output channels.</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(!biasEnabled || bias.size() == outputChannels);</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>  <span class="comment">// Creates the tensors.</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({inputNum, inputDepth, inputHeight, inputWidth, inputChannels}, ArmnnType);</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({outputNum, outputDepth, outputHeight, outputWidth, outputChannels}, ArmnnType);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({kernelDepth, kernelHeight, kernelWidth, kernelInChannels, kernelOutChannels},</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  ArmnnType);</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasDesc({<span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(bias.size())}, ArmnnBType);</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> </div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordflow">if</span>(armnn::IsQuantizedType<T>())</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  {</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  inputTensorInfo.SetQuantizationScale(qScale);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  outputTensorInfo.SetQuantizationScale(qScale);</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  outputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  kernelDesc.SetQuantizationScale(qScale);</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  kernelDesc.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  biasDesc.SetQuantizationScale(qScale*qScale);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  biasDesc.SetQuantizationOffset(0);</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  }</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> </div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="comment">// Construct the input data.</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  std::vector<T> inputData;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  inputData.assign(input.data(), input.data() + inputNum*inputDepth*inputHeight*inputWidth*inputChannels);</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="comment">// Construct the output data and apply bias if needed.</span></div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  std::vector<T> outputData;</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  outputData.assign(outputExpected.data(), outputExpected.data() +</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  outputNum*outputDepth*outputHeight*outputWidth*outputChannels);</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> </div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keywordflow">if</span> (biasEnabled)</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>  <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a41dde9c18d90c8dea2980e477d22a7fe">ApplyBiasToData</a>(outputData, bias,</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  outputTensorInfo.GetQuantizationScale(), outputTensorInfo.GetQuantizationOffset(),</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  biasDesc.GetQuantizationScale(), biasDesc.GetQuantizationOffset());</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  }</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="comment">// Permute input and output if data layout is NCDHW.</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a884e0167ebf9bbe6cfd6ca5ab97ab015">armnn::DataLayout::NCDHW</a>)</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  {</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <a class="code" href="_data_layout_utils_8hpp.xhtml#a024bab832cdcb51248891b1bc3aaf678">PermuteTensorNdhwcToNcdhw</a>(inputTensorInfo, inputData);</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <a class="code" href="_data_layout_utils_8hpp.xhtml#a024bab832cdcb51248891b1bc3aaf678">PermuteTensorNdhwcToNcdhw</a>(outputTensorInfo, outputData);</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  }</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  std::vector<T> actualOutput(outputTensorInfo.GetNumElements());</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> </div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  std::unique_ptr<armnn::ITensorHandle> input0Handle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  std::unique_ptr<armnn::ITensorHandle> input1Handle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(kernelDesc);</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</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>  <a class="code" href="structarmnn_1_1_convolution3d_queue_descriptor.xhtml">armnn::Convolution3dQueueDescriptor</a> data;</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = strideX;</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = strideY;</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#a5164336f6a1b15be0d434a6bbf7289da">m_StrideZ</a> = strideZ;</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = padLeft;</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = padRight;</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = padTop;</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = padBottom;</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#a83ca447892f460dabaa2f87d3dc3db61">m_PadFront</a> = padFront;</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#a11d5c25face9b54e90f79ee8bdc1d0fb">m_PadBack</a> = padBack;</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = dilationX;</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = dilationY;</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#a16543bce17aa2e4d6e81c88f74227192">m_DilationZ</a> = dilationZ;</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution3d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = biasEnabled;</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>  <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="l00267"></a><span class="lineno"> 267</span>  AddInputToWorkload(data, info, inputTensorInfo, input0Handle.get());</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  AddInputToWorkload(data, info, kernelDesc, input1Handle.get());</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> </div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  std::unique_ptr<armnn::ITensorHandle> input2Handle = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  {</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  input2Handle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(biasDesc);</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  AddInputToWorkload(data, info, biasDesc, input2Handle.get());</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> </div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a2120193449bfdb913edb0bf2719c33e4">CreateConvolution3d</a>(data, info);</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  input0Handle->Allocate();</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  input1Handle->Allocate();</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  outputHandle->Allocate();</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> </div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(input0Handle.get(), inputData.data());</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(input1Handle.get(), kernel.data());</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  {</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  input2Handle->Allocate();</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(input2Handle.get(), bias.data());</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> </div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  ExecuteWorkload(*workload, memoryManager);</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> </div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keywordflow">return</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 5></a>(actualOutput,</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  outputData,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  outputHandle->GetShape(),</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  outputTensorInfo.GetShape());</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> }</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> </div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> <span class="keyword">template</span><<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType,</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnBType,</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keyword">typename</span> T = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType></a>></div><div class="line"><a name="l00304"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#a7d255a9d48c3070697023d78e624524a"> 304</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a7d255a9d48c3070697023d78e624524a">SimpleConvolution3d3x3x3TestCommon</a>(</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</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="l00307"></a><span class="lineno"> 307</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> {</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordtype">float</span> qScale;</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  int32_t qOffset;</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  SetScaleOffset<ArmnnType>(qScale, qOffset);</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputDesc({ 1, 5, 5, 5, 1 }, ArmnnType);</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  std::vector<T> input = CreateQuantizedData<T>(125, qScale, qOffset);</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="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({ 3, 3, 3, 1, 1 }, ArmnnType);</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  std::vector<T> kernel = QuantizedVector<T>(</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  {</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  1, 1, 1,</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  1, 1, 1,</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  1, 1, 1,</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> </div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  0, 0, 0,</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  0, 1, 0,</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  0, 0, 0,</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> </div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  1, 1, 1,</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  1, 1, 1,</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  1, 1, 1,</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>  qScale, qOffset);</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputDesc({ 1, 3, 3, 3, 1 }, ArmnnType);</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  std::vector<T> outputData = QuantizedVector<T>(</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  {</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  589, 608, 627,</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  684, 703, 722,</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  779, 798, 817,</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> </div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  1064, 1083, 1102,</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  1159, 1178, 1197,</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  1254, 1273, 1292,</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>  1539, 1558, 1577,</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  1634, 1653, 1672,</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  1729, 1748, 1767</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  },</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  qScale, qOffset);</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> </div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keywordflow">return</span> SimpleConvolution3dTestImpl<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  workloadFactory,</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  memoryManager,</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  tensorHandleFactory,</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  input,</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  kernel,</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  GetBiasData<ArmnnBType>(biasEnabled, qScale * qScale, outputDesc, dataLayout),</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  outputData,</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  inputDesc.GetShape(),</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  kernelDesc.GetShape(),</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  outputDesc.GetShape(),</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  dataLayout,</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  qScale,</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  qOffset</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  );</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span> }</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> </div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span> <span class="keyword">template</span><<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType,</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnBType,</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keyword">typename</span> T = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType></a>></div><div class="line"><a name="l00372"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#afbace158a4ab4aacb4def9b30f4e4d65"> 372</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#afbace158a4ab4aacb4def9b30f4e4d65">Convolution3d2x2x2Strides3x5x5TestCommon</a>(</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</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="l00375"></a><span class="lineno"> 375</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> {</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="keywordtype">float</span> qScale;</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  int32_t qOffset;</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  SetScaleOffset<ArmnnType>(qScale, qOffset);</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> </div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputDesc({ 1, 3, 10, 10, 1 }, ArmnnType);</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  std::vector<T> input = CreateQuantizedData<T>(300, qScale, qOffset);</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({ 3, 5, 5, 1, 1 }, ArmnnType);</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  std::vector<T> kernel = QuantizedVector<T>(</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>  1, 1, 1, 1, 1,</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  1, 1, 1, 1, 1,</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  1, 1, 1, 1, 1,</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  1, 1, 1, 1, 1,</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  1, 1, 1, 1, 1,</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>  0, 0, 0, 0, 0,</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  0, 0, 0, 0, 0,</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  0, 0, 0, 0, 0,</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  0, 0, 0, 0, 0,</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  0, 0, 0, 0, 0,</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>  2, 2, 2, 2, 2,</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  2, 2, 2, 2, 2,</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  2, 2, 2, 2, 2,</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  2, 2, 2, 2, 2,</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  2, 2, 2, 2, 2,</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  },</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  qScale, qOffset);</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span> </div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputDesc({ 1, 1, 3, 3, 1 }, ArmnnType);</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  std::vector<T> outputData = QuantizedVector<T>(</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  {</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  11650, 11800, 11950,</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span> </div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  13150, 13300, 13450,</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>  14650, 14800, 14950</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  },</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  qScale, qOffset);</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> </div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keywordflow">return</span> SimpleConvolution3dTestImpl<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  workloadFactory,</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  memoryManager,</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  tensorHandleFactory,</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  input,</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  kernel,</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  GetBiasData<ArmnnBType>(biasEnabled, qScale * qScale, outputDesc, dataLayout),</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  outputData,</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  inputDesc.GetShape(),</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  kernelDesc.GetShape(),</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  outputDesc.GetShape(),</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  dataLayout,</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  qScale,</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  qOffset,</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  2, <span class="comment">// strideX</span></div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  2, <span class="comment">// strideY</span></div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  2 <span class="comment">// strideZ</span></div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  );</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> }</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span> </div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span> <span class="keyword">template</span><<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType,</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnBType,</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <span class="keyword">typename</span> T = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType></a>></div><div class="line"><a name="l00443"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#a0878ba921d9497706bc243ba202f7016"> 443</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a0878ba921d9497706bc243ba202f7016">Convolution3d2x2x2Dilation2x2x2TestCommon</a>(</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</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="l00446"></a><span class="lineno"> 446</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</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>  <span class="keywordtype">float</span> qScale;</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  int32_t qOffset;</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  SetScaleOffset<ArmnnType>(qScale, qOffset);</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span> </div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputDesc({ 1, 5, 5, 5, 2 }, ArmnnType);</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  std::vector<T> input = CreateQuantizedData<T>(250, qScale, qOffset);</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({ 2, 2, 2, 2, 2 }, ArmnnType);</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  std::vector<T> kernel = QuantizedVector<T>(</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  {</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1,</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  1, 1, -1, 1, -1, 1, -1, 1, -1, -1, -1, 1, -1, 1, -1, 1,</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  },</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  qScale, qOffset);</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span> </div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="comment">// Since the dilation rate is 3 this will dilate the kernel to be 4x4,</span></div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <span class="comment">// therefore the output will be 2x2</span></div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputDesc({ 1, 2, 2, 2, 2 }, ArmnnType);</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  std::vector<T> outputData = QuantizedVector<T>(</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  {</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  -1124, 974,</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  -1148, 978,</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span> </div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  -1244, 994,</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  -1268, 998,</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span> </div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  -1724, 1074,</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  -1748, 1078,</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span> </div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  -1844, 1094,</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  -1868, 1098</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  },</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  qScale, qOffset);</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span> </div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="keywordflow">return</span> SimpleConvolution3dTestImpl<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  workloadFactory,</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  memoryManager,</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  tensorHandleFactory,</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  input,</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  kernel,</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  GetBiasData<ArmnnBType>(biasEnabled, qScale * qScale, outputDesc, dataLayout),</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  outputData,</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  inputDesc.GetShape(),</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  kernelDesc.GetShape(),</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  outputDesc.GetShape(),</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  dataLayout,</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  qScale,</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  qOffset,</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  1, <span class="comment">// strideX</span></div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  1, <span class="comment">// strideY</span></div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  1, <span class="comment">// strideZ</span></div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  3, <span class="comment">// dilationX</span></div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  3, <span class="comment">// dilationY</span></div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  3 <span class="comment">// dilationZ</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> </div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span> <span class="keyword">template</span><<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType,</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnBType,</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <span class="keyword">typename</span> T = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType></a>></div><div class="line"><a name="l00510"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#a1736a9bf1b2b7f77069e129ff67e03d1"> 510</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a1736a9bf1b2b7f77069e129ff67e03d1">Convolution3dPaddingSame3x3x3TestCommon</a>(</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</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="l00513"></a><span class="lineno"> 513</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span> {</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <span class="keywordtype">float</span> qScale;</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  int32_t qOffset;</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  SetScaleOffset<ArmnnType>(qScale, qOffset);</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="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputDesc({ 1, 5, 5, 5, 1 }, ArmnnType);</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  std::vector<T> input = CreateQuantizedData<T>(125, qScale, qOffset);</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({ 3, 3, 3, 1, 1 }, ArmnnType);</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  std::vector<T> kernel = QuantizedVector<T>(</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>  1, 1, 1,</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  1, 1, 1,</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  1, 1, 1,</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span> </div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  0, 0, 0,</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  0, 0, 0,</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  0, 0, 0,</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span> </div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  1, 1, 1,</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  1, 1, 1,</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  1, 1, 1,</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>  qScale, qOffset);</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputDesc({ 1, 5, 5, 5, 1 }, ArmnnType);</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  std::vector<T> outputData = QuantizedVector<T>(</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>  112, 171, 177, 183, 124,</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  183, 279, 288, 297, 201,</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  213, 324, 333, 342, 231,</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  243, 369, 378, 387, 261,</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  172, 261, 267, 273, 184,</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>  224, 342, 354, 366, 248,</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  366, 558, 576, 594, 402,</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  426, 648, 666, 684, 462,</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  486, 738, 756, 774, 522,</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  344, 522, 534, 546, 368,</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span> </div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  424, 642, 654, 666, 448,</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  666, 1008, 1026, 1044, 702,</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  726, 1098, 1116, 1134, 762,</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  786, 1188, 1206, 1224, 822,</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  544, 822, 834, 846, 568,</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  624, 942, 954, 966, 648,</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span> </div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  966, 1458, 1476, 1494, 1002,</div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  1026, 1548, 1566, 1584, 1062,</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  1086, 1638, 1656, 1674, 1122,</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  744, 1122, 1134, 1146, 768,</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  312, 471, 477, 483, 324,</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  483, 729, 738, 747, 501,</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  513, 774, 783, 792, 531,</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  543, 819, 828, 837, 561,</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  372, 561, 567, 573, 384</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>  qScale, qOffset);</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>  <span class="keywordflow">return</span> SimpleConvolution3dTestImpl<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  workloadFactory,</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  memoryManager,</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  tensorHandleFactory,</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  input,</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  kernel,</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  GetBiasData<ArmnnBType>(biasEnabled, qScale * qScale, outputDesc, dataLayout),</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  outputData,</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  inputDesc.GetShape(),</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  kernelDesc.GetShape(),</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  outputDesc.GetShape(),</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  dataLayout,</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  qScale,</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  qOffset,</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  1, <span class="comment">// strideX</span></div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  1, <span class="comment">// strideY</span></div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  1, <span class="comment">// strideZ</span></div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  1, <span class="comment">// dilationX</span></div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  1, <span class="comment">// dilationY</span></div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  1, <span class="comment">// dilationZ</span></div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  1, <span class="comment">// padLeft</span></div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  1, <span class="comment">// padTop</span></div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  1, <span class="comment">// padRight</span></div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  1, <span class="comment">// padBottom</span></div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  1, <span class="comment">// padFront</span></div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  1 <span class="comment">// padBack</span></div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  );</div><div class="line"><a name="l00602"></a><span class="lineno"> 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"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#acbbf738deb20cb22c554d0d1f12f0ab6"> 604</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#acbbf738deb20cb22c554d0d1f12f0ab6">Convolution3dStrideDilationPadding3x3x3TestCommonFloat32</a>(</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</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_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span> {</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keywordtype">float</span> qScale = 0.f;</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  int32_t qOffset = 0;</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span> </div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputDesc({ 1, 3, 10, 10, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  std::vector<float> input = CreateSmallQuantizedData<float>(600, 100.0f, qScale, qOffset);</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span> </div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({ 3, 3, 3, 2, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  std::vector<float> kernel = CreateSmallQuantizedData<float>(108, 100.0f, qScale, qOffset);</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>  <span class="comment">// Since the dilation rate is 2 this will dilate the kernel to be 5x5: d(K-1)+1 --> 2 x (3-1) + 1 = 5,</span></div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  <span class="comment">// therefore the output will be 1x4x4: (I − K + 2P)/S +1 => trunc((10 - 3 + 2x2 )/3 + 1))</span></div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  <span class="comment">// where, dilation size = d = 2; kernel size = K = 3; input size = I = 10; padding size = P = 2; stride = S = 3</span></div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputDesc({ 1, 1, 4, 4, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  std::vector<float> outputData =</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  {</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  12.0312f, 12.2268f, 17.7512f, 18.0494f,</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  18.176f, 18.4814f, 5.6912f, 5.7938f,</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  19.1664f, 19.5078f, 28.119f, 28.6383f,</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  28.6914f, 29.2215f, 8.9094f, 9.0873f,</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>  23.1264f, 23.5398f, 33.843f, 34.4703f,</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  34.4154f, 35.0535f, 10.6734f, 10.8873f,</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  6.2712f, 6.417f, 9.0718f, 9.2929f,</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  9.2194f, 9.4441f, 2.7862f, 2.8615f</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  };</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span> </div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <span class="keywordflow">return</span> SimpleConvolution3dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  workloadFactory,</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  memoryManager,</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  tensorHandleFactory,</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  input,</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  kernel,</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  GetBiasData<armnn::DataType::Float32>(biasEnabled, qScale * qScale, outputDesc, dataLayout),</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  outputData,</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  inputDesc.GetShape(),</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  kernelDesc.GetShape(),</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  outputDesc.GetShape(),</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  dataLayout,</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  qScale,</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  qOffset,</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  3, <span class="comment">// strideX</span></div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  3, <span class="comment">// strideY</span></div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  3, <span class="comment">// strideZ</span></div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  2, <span class="comment">// dilationX</span></div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  2, <span class="comment">// dilationY</span></div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  2, <span class="comment">// dilationZ</span></div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  1, <span class="comment">// padLeft</span></div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  1, <span class="comment">// padTop</span></div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  1, <span class="comment">// padRight</span></div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  1, <span class="comment">// padBottom</span></div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  1, <span class="comment">// padFront</span></div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  1 <span class="comment">// padBack</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> }</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span> </div><div class="line"><a name="l00666"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#a4668f0282ba880fed2768558243ccf00"> 666</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a4668f0282ba880fed2768558243ccf00">Convolution3d2x2x2Stride3x3x3SmallTestCommonFloat32</a>(</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</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="l00669"></a><span class="lineno"> 669</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span> {</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  <span class="keywordtype">float</span> qScale = 0.f;</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  int32_t qOffset = 0;</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span> </div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputDesc({ 1, 3, 10, 10, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  std::vector<float> input = CreateSmallQuantizedData<float>(300, 100.0f, qScale, qOffset);</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span> </div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({ 3, 3, 3, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  std::vector<float> kernel =</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>  0.125977f, 0.150391f, 0.101562f,</div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  0.0585938f, 0.0864258f, 0.043457f,</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  0.034668f, 0.0322266f, 0.0385742f,</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span> </div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  0.125977f, 0.150391f, -0.101562f,</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  -0.0585938f,-0.0864258f,-0.043457f,</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  -0.0104630f, 0.0154114f, 0.0013768f,</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>  0.0344238f, 0.035644f, 0.0495605f,</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  0.0683594f, 0.099121f, -0.0461426f,</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  -0.0996094f,-0.126953f, -0.043457f,</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  };</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span> </div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputDesc({ 1, 1, 4, 4, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  std::vector<float> outputData =</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  {</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  -0.08156067f, -0.06891209f, -0.05589598f, -0.04310101f,</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  0.04584253f, 0.05855697f, 0.07129729f, 0.08325434f,</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  0.17304349f, 0.18521416f, 0.19818866f, 0.21096253f,</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  0.29965734f, 0.312698f, 0.32547557f, 0.33818722f</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> </div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  <span class="keywordflow">return</span> SimpleConvolution3dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  workloadFactory,</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  memoryManager,</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  tensorHandleFactory,</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  input,</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  kernel,</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  GetBiasData<armnn::DataType::Float32>(biasEnabled, qScale * qScale, outputDesc, dataLayout),</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  outputData,</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  inputDesc.GetShape(),</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  kernelDesc.GetShape(),</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  outputDesc.GetShape(),</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  dataLayout,</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  qScale,</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  qOffset,</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  2, <span class="comment">// strideX</span></div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  2, <span class="comment">// strideY</span></div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  2 <span class="comment">// strideZ</span></div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  );</div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span> }</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span> </div><div class="line"><a name="l00724"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#abd444942e3547d0dce1c48f8455f071f"> 724</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<armnn::Half, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#abd444942e3547d0dce1c48f8455f071f">Convolution3d2x3x3TestCommonFloat16</a>(</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</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="l00727"></a><span class="lineno"> 727</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span> {</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  <span class="keyword">using namespace </span>half_float::literal;</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span> </div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  <span class="keywordtype">float</span> qScale = 0.f;</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  int32_t qOffset = 0;</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span> </div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputDesc({ 1, 2, 3, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  <span class="keyword">const</span> std::vector<armnn::Half> input =</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  {</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  1._h, 2._h, 3._h,</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  4._h, 5._h, 6._h,</div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span> </div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  7._h, 8._h, 9._h,</div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  10._h, 11._h, 12._h,</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span> </div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  13._h, 14._h, 15._h,</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  16._h, 17._h, 18._h,</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>  19._h, 20._h, 21._h,</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  22._h, 23._h, 24._h,</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span> </div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  25._h, 26._h, 27._h,</div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  28._h, 29._h, 30._h,</div><div class="line"><a name="l00753"></a><span class="lineno"> 753</span> </div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  31._h, 32._h, 33._h,</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  34._h, 35._h, 36._h</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  };</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span> </div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({ 2, 2, 2, 2, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  std::vector<armnn::Half> kernel =</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  {</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  -1._h, -1._h, -1._h, -1._h, -1._h, -1._h, -1._h, -1._h,</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  -1._h, -1._h, -1._h, 1._h, 1._h, 1._h, -1._h, -1._h,</div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  1._h, 1._h, -1._h, 1._h, -1._h, 1._h, -1._h, 1._h,</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  -1._h, -1._h, -1._h, 1._h, -1._h, 1._h, -1._h, 1._h,</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  };</div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span> </div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputDesc({ 1, 1, 2, 2, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  std::vector<armnn::Half> outputData =</div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  {</div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  -176._h, 128._h,</div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  -200._h, 132._h,</div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span> </div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  -248._h, 140._h,</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  -272._h, 144._h</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  };</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span> </div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <span class="keywordflow">return</span> SimpleConvolution3dTestImpl<armnn::DataType::Float16, armnn::DataType::Float16>(</div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  workloadFactory,</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  memoryManager,</div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  tensorHandleFactory,</div><div class="line"><a name="l00781"></a><span class="lineno"> 781</span>  input,</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  kernel,</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  GetBiasData<armnn::DataType::Float16>(biasEnabled, qScale * qScale, outputDesc, dataLayout),</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  outputData,</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  inputDesc.GetShape(),</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  kernelDesc.GetShape(),</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  outputDesc.GetShape(),</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  dataLayout,</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  qScale,</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  qOffset</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  );</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span> }</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span> </div><div class="line"><a name="l00794"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8cpp.xhtml#a6a5b0b2846112d6280e58a36f826635c"> 794</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<armnn::Half, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a6a5b0b2846112d6280e58a36f826635c">Convolution3d2x2x2SmallTestCommonFloat16</a>(</div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00796"></a><span class="lineno"> 796</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="l00797"></a><span class="lineno"> 797</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span> {</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  <span class="keyword">using namespace </span>half_float::literal;</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span> </div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <span class="keywordtype">float</span> qScale = 0.f;</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  int32_t qOffset = 0;</div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span> </div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputDesc({ 1, 2, 4, 4, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  <span class="keyword">const</span> std::vector<armnn::Half> input =</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  {</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  0.0367984_h, 0.0380895_h, 0.0420157_h, 0.0675631_h,</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  0.0938920_h, 0.0476106_h, 0.1035490_h, 0.1260370_h,</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  0.0461647_h, 0.0883828_h, 0.1159540_h, 0.0498519_h,</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  0.0104630_h, 0.0154114_h, 0.00137681_h, 0.0344238_h,</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span> </div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  0.0356445_h, 0.0495605_h, 0.0683594_h, 0.0991211_h,</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  0.0461426_h, 0.0996094_h, 0.1269530_h, 0.0393066_h,</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  0.103516_h, 0.032544_h, 0.124334_h, 0.0564566_h,</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  0.0123544_h, 0.0461647_h, 0.0883828_h, 0.1159540_h,</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  };</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span> </div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({ 2, 2, 2, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  std::vector<armnn::Half> kernel =</div><div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  {</div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  -0.126184_h, -0.150468_h,</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  -0.101412_h, -0.0586369_h,</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span> </div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  -0.0435089_h, 0.0347555_h,</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  0.0323111_h, 0.0385381_h</div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  };</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span> </div><div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputDesc({ 1, 1, 3, 3, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00831"></a><span class="lineno"> 831</span>  std::vector<armnn::Half> outputData =</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span>  {</div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span>  -0.01718917_h, -0.01370182_h, -0.02727737_h,</div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span> </div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  -0.02282543_h, -0.03144084_h, -0.04468598_h,</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span> </div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  -0.02228982_h, -0.02244923_h, -0.02042268_h</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  };</div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span> </div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  <span class="keywordflow">return</span> SimpleConvolution3dTestImpl<armnn::DataType::Float16, armnn::DataType::Float16>(</div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  workloadFactory,</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  memoryManager,</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  tensorHandleFactory,</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  input,</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  kernel,</div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  GetBiasData<armnn::DataType::Float16>(biasEnabled, qScale * qScale, outputDesc, dataLayout),</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  outputData,</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  inputDesc.GetShape(),</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  kernelDesc.GetShape(),</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  outputDesc.GetShape(),</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  dataLayout,</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  qScale,</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  qOffset</div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  );</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span> }</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span> </div><div class="line"><a name="l00857"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a97f335101f2aeb09994ab41d32c09904"> 857</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a97f335101f2aeb09994ab41d32c09904">SimpleConvolution3d3x3x3Float32Test</a>(</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</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="l00860"></a><span class="lineno"> 860</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span> {</div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  <span class="keywordflow">return</span> SimpleConvolution3d3x3x3TestCommon<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span> }</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span> </div><div class="line"><a name="l00868"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a3cb502406461e6ae0293e5352558eb30"> 868</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int8_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a547970283584b6cec80bf753eca14cd8">SimpleConvolution3d3x3x3Int8Test</a>(</div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</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="l00871"></a><span class="lineno"> 871</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span> {</div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  <span class="keywordflow">return</span> SimpleConvolution3d3x3x3TestCommon<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>(</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span> }</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span> </div><div class="line"><a name="l00879"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a4c578ed3b0e74f84354fad1cc40a1d9d"> 879</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a4c578ed3b0e74f84354fad1cc40a1d9d">SimpleConvolution3d3x3x3Uint8Test</a>(</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00881"></a><span class="lineno"> 881</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="l00882"></a><span class="lineno"> 882</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span> {</div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  <span class="keywordflow">return</span> SimpleConvolution3d3x3x3TestCommon<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>(</div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span> }</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span> </div><div class="line"><a name="l00890"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a383e402b8f57b092bd6fc6fda8387f11"> 890</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a383e402b8f57b092bd6fc6fda8387f11">SimpleConvolution3d3x3x3Int16Test</a>(</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span> {</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  <span class="keywordflow">return</span> SimpleConvolution3d3x3x3TestCommon<armnn::DataType::QSymmS16, armnn::DataType::Signed32>(</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span> }</div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span> </div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span> </div><div class="line"><a name="l00902"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a7e32be2b43d18a12bfd8e47ad4cd0b46"> 902</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a7e32be2b43d18a12bfd8e47ad4cd0b46">Convolution3d2x2x2Strides3x5x5Float32Test</a>(</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00904"></a><span class="lineno"> 904</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="l00905"></a><span class="lineno"> 905</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span> {</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  <span class="keywordflow">return</span> Convolution3d2x2x2Strides3x5x5TestCommon<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span> }</div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span> </div><div class="line"><a name="l00913"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#abfbb70c8542ff7f986b4cd7284369913"> 913</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int8_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a3be73c19cbb7ea724b7e5e777d3acf62">Convolution3d2x2x2Strides3x5x5Int8Test</a>(</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span> {</div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  <span class="keywordflow">return</span> Convolution3d2x2x2Strides3x5x5TestCommon<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>(</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span> }</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span> </div><div class="line"><a name="l00924"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#aeb54439f726cc853209509e730e876e6"> 924</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#aeb54439f726cc853209509e730e876e6">Convolution3d2x2x2Strides3x5x5Uint8Test</a>(</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00926"></a><span class="lineno"> 926</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="l00927"></a><span class="lineno"> 927</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span> {</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  <span class="keywordflow">return</span> Convolution3d2x2x2Strides3x5x5TestCommon<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>(</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span> }</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span> </div><div class="line"><a name="l00935"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a58289ea01aec699a91f8184db7bbda20"> 935</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a58289ea01aec699a91f8184db7bbda20">Convolution3d2x2x2Strides3x5x5Int16Test</a>(</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</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="l00938"></a><span class="lineno"> 938</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span> {</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  <span class="keywordflow">return</span> Convolution3d2x2x2Strides3x5x5TestCommon<armnn::DataType::QSymmS16, armnn::DataType::Signed32>(</div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span> }</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span> </div><div class="line"><a name="l00946"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#aff7f671b6c142a9a27f6de42163c31bc"> 946</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#aff7f671b6c142a9a27f6de42163c31bc">Convolution3d2x2x2Dilation2x2x2Float32Test</a>(</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</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="l00949"></a><span class="lineno"> 949</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span> {</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  <span class="keywordflow">return</span> Convolution3d2x2x2Dilation2x2x2TestCommon<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span> }</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span> </div><div class="line"><a name="l00957"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a78fb20c968605ebeb0d64a8aa4773d11"> 957</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int8_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#ac951dbcec6aa92bad6ca12bca60303cb">Convolution3d2x2x2Dilation2x2x2Int8Test</a>(</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</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="l00960"></a><span class="lineno"> 960</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span> {</div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  <span class="keywordflow">return</span> Convolution3d2x2x2Dilation2x2x2TestCommon<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>(</div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span> }</div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span> </div><div class="line"><a name="l00968"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a753f5422f1714c31b62f0b8af0ade5fc"> 968</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a753f5422f1714c31b62f0b8af0ade5fc">Convolution3d2x2x2Dilation2x2x2Uint8Test</a>(</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00970"></a><span class="lineno"> 970</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="l00971"></a><span class="lineno"> 971</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span> {</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  <span class="keywordflow">return</span> Convolution3d2x2x2Dilation2x2x2TestCommon<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>(</div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span> }</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span> </div><div class="line"><a name="l00979"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#ac176698dda319e6958ec8fdc658f3771"> 979</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#ac176698dda319e6958ec8fdc658f3771">Convolution3d2x2x2Dilation2x2x2Int16Test</a>(</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</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="l00982"></a><span class="lineno"> 982</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span> {</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  <span class="keywordflow">return</span> Convolution3d2x2x2Dilation2x2x2TestCommon<armnn::DataType::QSymmS16, armnn::DataType::Signed32>(</div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span> }</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span> </div><div class="line"><a name="l00990"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a7306e3c4bbf3369f431d02c511549cb4"> 990</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a7306e3c4bbf3369f431d02c511549cb4">Convolution3dPaddingSame3x3x3Float32Test</a>(</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00992"></a><span class="lineno"> 992</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="l00993"></a><span class="lineno"> 993</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span> {</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  <span class="keywordflow">return</span> Convolution3dPaddingSame3x3x3TestCommon<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span> }</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span> </div><div class="line"><a name="l01001"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a30b7eae4729de06534bfbe24c59af176"> 1001</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int8_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a494edc54ecf36a98b35437e8c2fe1a9e">Convolution3dPaddingSame3x3x3Int8Test</a>(</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</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="l01004"></a><span class="lineno"> 1004</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span> {</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  <span class="keywordflow">return</span> Convolution3dPaddingSame3x3x3TestCommon<armnn::DataType::QAsymmS8, armnn::DataType::Signed32>(</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span> }</div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span> </div><div class="line"><a name="l01012"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a7e91c39f11c5399ad8aaf8d61250aa75"> 1012</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a7e91c39f11c5399ad8aaf8d61250aa75">Convolution3dPaddingSame3x3x3Uint8Test</a>(</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span> {</div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  <span class="keywordflow">return</span> Convolution3dPaddingSame3x3x3TestCommon<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>(</div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l01021"></a><span class="lineno"> 1021</span> }</div><div class="line"><a name="l01022"></a><span class="lineno"> 1022</span> </div><div class="line"><a name="l01023"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a7decbecf820e4ffcd48246ce9411f13e"> 1023</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a7decbecf820e4ffcd48246ce9411f13e">Convolution3dPaddingSame3x3x3Int16Test</a>(</div><div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span> {</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>  <span class="keywordflow">return</span> Convolution3dPaddingSame3x3x3TestCommon<armnn::DataType::QSymmS16, armnn::DataType::Signed32>(</div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span> }</div><div class="line"><a name="l01033"></a><span class="lineno"> 1033</span> </div><div class="line"><a name="l01034"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#ab92354f039394a1f144d266a2d919c63"> 1034</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#ab92354f039394a1f144d266a2d919c63">Convolution3dStrideDilationPadding3x3x3Float32Test</a>(</div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span> {</div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>  <span class="keywordflow">return</span> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#acbbf738deb20cb22c554d0d1f12f0ab6">Convolution3dStrideDilationPadding3x3x3TestCommonFloat32</a>(</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span> }</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span> </div><div class="line"><a name="l01045"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a10b4c0d6aa10d1077210f105bc56a242"> 1045</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a10b4c0d6aa10d1077210f105bc56a242">Convolution3d2x2x2Stride3x3x3SmallFloat32Test</a>(</div><div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</span> {</div><div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>  <span class="keywordflow">return</span> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a4668f0282ba880fed2768558243ccf00">Convolution3d2x2x2Stride3x3x3SmallTestCommonFloat32</a>(</div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span> }</div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span> </div><div class="line"><a name="l01056"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a3cdd0ad48e8cd5bd948d659b9a56a0b4"> 1056</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<armnn::Half, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a3cdd0ad48e8cd5bd948d659b9a56a0b4">Convolution3d2x3x3Float16Test</a>(</div><div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01058"></a><span class="lineno"> 1058</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="l01059"></a><span class="lineno"> 1059</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01062"></a><span class="lineno"> 1062</span> {</div><div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>  <span class="keywordflow">return</span> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#abd444942e3547d0dce1c48f8455f071f">Convolution3d2x3x3TestCommonFloat16</a>(</div><div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span> }</div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span> </div><div class="line"><a name="l01067"></a><span class="lineno"><a class="line" href="_conv3d_test_impl_8hpp.xhtml#a8e7d066dae8be968b1b1e649f9019bbc"> 1067</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<armnn::Half, 5></a> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a8e7d066dae8be968b1b1e649f9019bbc">Convolution3d2x2x2SmallFloat16Test</a>(</div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</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="l01070"></a><span class="lineno"> 1070</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  <span class="keywordtype">bool</span> biasEnabled,</div><div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</span> {</div><div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  <span class="keywordflow">return</span> <a class="code" href="_conv3d_test_impl_8cpp.xhtml#a6a5b0b2846112d6280e58a36f826635c">Convolution3d2x2x2SmallTestCommonFloat16</a>(</div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>  workloadFactory, memoryManager, tensorHandleFactory, biasEnabled, dataLayout);</div><div class="line"><a name="l01076"></a><span class="lineno"> 1076</span> }</div><div class="ttc" id="_conv3d_test_impl_8hpp_xhtml"><div class="ttname"><a href="_conv3d_test_impl_8hpp.xhtml">Conv3dTestImpl.hpp</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a7e32be2b43d18a12bfd8e47ad4cd0b46"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a7e32be2b43d18a12bfd8e47ad4cd0b46">Convolution3d2x2x2Strides3x5x5Float32Test</a></div><div class="ttdeci">LayerTestResult< float, 5 > Convolution3d2x2x2Strides3x5x5Float32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00902">Conv3dTestImpl.cpp:902</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="_conv3d_test_impl_8cpp_xhtml_a383e402b8f57b092bd6fc6fda8387f11"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a383e402b8f57b092bd6fc6fda8387f11">SimpleConvolution3d3x3x3Int16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 5 > SimpleConvolution3d3x3x3Int16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00890">Conv3dTestImpl.cpp:890</a></div></div> +<div class="ttc" id="_data_layout_indexed_8hpp_xhtml"><div class="ttname"><a href="_data_layout_indexed_8hpp.xhtml">DataLayoutIndexed.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="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00191">Tensor.hpp:191</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_acbbf738deb20cb22c554d0d1f12f0ab6"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#acbbf738deb20cb22c554d0d1f12f0ab6">Convolution3dStrideDilationPadding3x3x3TestCommonFloat32</a></div><div class="ttdeci">LayerTestResult< float, 5 > Convolution3dStrideDilationPadding3x3x3TestCommonFloat32(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00604">Conv3dTestImpl.cpp:604</a></div></div> +<div class="ttc" id="_data_layout_utils_8hpp_xhtml_a024bab832cdcb51248891b1bc3aaf678"><div class="ttname"><a href="_data_layout_utils_8hpp.xhtml#a024bab832cdcb51248891b1bc3aaf678">PermuteTensorNdhwcToNcdhw</a></div><div class="ttdeci">void PermuteTensorNdhwcToNcdhw(armnn::TensorInfo &tensorInfo, std::vector< T > &tensorData)</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_utils_8hpp_source.xhtml#l00039">DataLayoutUtils.hpp:39</a></div></div> +<div class="ttc" id="_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_tensor_handle_8hpp.xhtml">TensorHandle.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_a11d5c25face9b54e90f79ee8bdc1d0fb"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#a11d5c25face9b54e90f79ee8bdc1d0fb">armnn::Convolution3dDescriptor::m_PadBack</a></div><div class="ttdeci">uint32_t m_PadBack</div><div class="ttdoc">Padding back value in the depth dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00515">Descriptors.hpp:515</a></div></div> +<div class="ttc" id="_inference_test_image_8hpp_xhtml_a65983f8cb907d873f2328bb8307c296aa9d5ed678fe57bcca610140957afab571"><div class="ttname"><a href="_inference_test_image_8hpp.xhtml#a65983f8cb907d873f2328bb8307c296aa9d5ed678fe57bcca610140957afab571">ImageChannel::B</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="_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#l00022">WorkloadFactory.hpp:22</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_convolution3d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::Convolution3dDescriptor::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#l00517">Descriptors.hpp:517</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_ac29da01384d6955a5788945352713a21"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#ac29da01384d6955a5788945352713a21">GetBiasData</a></div><div class="ttdeci">std::vector< T > GetBiasData(bool biasEnabled, float qScale, armnn::TensorInfo outputInfo, armnn::DataLayout layout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00028">Conv3dTestImpl.cpp:28</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution3d_queue_descriptor.xhtml">armnn::Convolution3dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00212">WorkloadData.hpp:212</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a547970283584b6cec80bf753eca14cd8"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a547970283584b6cec80bf753eca14cd8">SimpleConvolution3d3x3x3Int8Test</a></div><div class="ttdeci">LayerTestResult< int8_t, 5 > SimpleConvolution3d3x3x3Int8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00868">Conv3dTestImpl.cpp:868</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a7306e3c4bbf3369f431d02c511549cb4"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a7306e3c4bbf3369f431d02c511549cb4">Convolution3dPaddingSame3x3x3Float32Test</a></div><div class="ttdeci">LayerTestResult< float, 5 > Convolution3dPaddingSame3x3x3Float32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00990">Conv3dTestImpl.cpp:990</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a0743ed5e860c316a20b68ca96301b411"><div class="ttname"><a href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a></div><div class="ttdeci">typename ResolveTypeImpl< DT >::Type ResolveType</div><div class="ttdef"><b>Definition:</b> <a href="_resolve_type_8hpp_source.xhtml#l00079">ResolveType.hpp:79</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::Convolution3dDescriptor::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#l00511">Descriptors.hpp:511</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution3dDescriptor::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#l00529">Descriptors.hpp:529</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a8e7d066dae8be968b1b1e649f9019bbc"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a8e7d066dae8be968b1b1e649f9019bbc">Convolution3d2x2x2SmallFloat16Test</a></div><div class="ttdeci">LayerTestResult< armnn::Half, 5 > Convolution3d2x2x2SmallFloat16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l01067">Conv3dTestImpl.cpp:1067</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_afbace158a4ab4aacb4def9b30f4e4d65"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#afbace158a4ab4aacb4def9b30f4e4d65">Convolution3d2x2x2Strides3x5x5TestCommon</a></div><div class="ttdeci">LayerTestResult< T, 5 > Convolution3d2x2x2Strides3x5x5TestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00372">Conv3dTestImpl.cpp:372</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#l00057">WorkloadData.hpp:57</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::Convolution3dDescriptor::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#l00523">Descriptors.hpp:523</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a7decbecf820e4ffcd48246ce9411f13e"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a7decbecf820e4ffcd48246ce9411f13e">Convolution3dPaddingSame3x3x3Int16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 5 > Convolution3dPaddingSame3x3x3Int16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l01023">Conv3dTestImpl.cpp:1023</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution3dDescriptor::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#l00519">Descriptors.hpp:519</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a7d255a9d48c3070697023d78e624524a"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a7d255a9d48c3070697023d78e624524a">SimpleConvolution3d3x3x3TestCommon</a></div><div class="ttdeci">LayerTestResult< T, 5 > SimpleConvolution3d3x3x3TestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00304">Conv3dTestImpl.cpp:304</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_ab92354f039394a1f144d266a2d919c63"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#ab92354f039394a1f144d266a2d919c63">Convolution3dStrideDilationPadding3x3x3Float32Test</a></div><div class="ttdeci">LayerTestResult< float, 5 > Convolution3dStrideDilationPadding3x3x3Float32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l01034">Conv3dTestImpl.cpp:1034</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_aa8c767319f74f1b79ca1658b0cd0c8e0"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#aa8c767319f74f1b79ca1658b0cd0c8e0">SimpleConvolution3dTestImpl</a></div><div class="ttdeci">LayerTestResult< T, 5 > SimpleConvolution3dTestImpl(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, const std::vector< T > &input, const std::vector< T > &kernel, const std::vector< B > &bias, const std::vector< T > &outputExpected, const armnn::TensorShape &inputShape, const armnn::TensorShape &kernelShape, const armnn::TensorShape &outputExpectedShape, const armnn::DataLayout dataLayout, float qScale, int32_t qOffset, uint32_t strideX=1, uint32_t strideY=1, uint32_t strideZ=1, uint32_t dilationX=1, uint32_t dilationY=1, uint32_t dilationZ=1, uint32_t padLeft=0, uint32_t padTop=0, uint32_t padRight=0, uint32_t padBottom=0, uint32_t padFront=0, uint32_t padBack=0)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00150">Conv3dTestImpl.cpp:150</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a753f5422f1714c31b62f0b8af0ade5fc"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a753f5422f1714c31b62f0b8af0ade5fc">Convolution3d2x2x2Dilation2x2x2Uint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 5 > Convolution3d2x2x2Dilation2x2x2Uint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00968">Conv3dTestImpl.cpp:968</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="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a884e0167ebf9bbe6cfd6ca5ab97ab015"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a884e0167ebf9bbe6cfd6ca5ab97ab015">armnn::DataLayout::NCDHW</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a10b4c0d6aa10d1077210f105bc56a242"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a10b4c0d6aa10d1077210f105bc56a242">Convolution3d2x2x2Stride3x3x3SmallFloat32Test</a></div><div class="ttdeci">LayerTestResult< float, 5 > Convolution3d2x2x2Stride3x3x3SmallFloat32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l01045">Conv3dTestImpl.cpp:1045</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00035">Types.hpp:35</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a3cdd0ad48e8cd5bd948d659b9a56a0b4"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a3cdd0ad48e8cd5bd948d659b9a56a0b4">Convolution3d2x3x3Float16Test</a></div><div class="ttdeci">LayerTestResult< armnn::Half, 5 > Convolution3d2x3x3Float16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l01056">Conv3dTestImpl.cpp:1056</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00015">Assert.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_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="_i_backend_internal_8hpp_source.xhtml#l00099">IBackendInternal.hpp:99</a></div></div> +<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml">armnnUtils::DataLayoutIndexed</a></div><div class="ttdoc">Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00017">DataLayoutIndexed.hpp:17</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a7e91c39f11c5399ad8aaf8d61250aa75"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a7e91c39f11c5399ad8aaf8d61250aa75">Convolution3dPaddingSame3x3x3Uint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 5 > Convolution3dPaddingSame3x3x3Uint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l01012">Conv3dTestImpl.cpp:1012</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a3be73c19cbb7ea724b7e5e777d3acf62"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a3be73c19cbb7ea724b7e5e777d3acf62">Convolution3d2x2x2Strides3x5x5Int8Test</a></div><div class="ttdeci">LayerTestResult< int8_t, 5 > Convolution3d2x2x2Strides3x5x5Int8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00913">Conv3dTestImpl.cpp:913</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a41dde9c18d90c8dea2980e477d22a7fe"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a41dde9c18d90c8dea2980e477d22a7fe">ApplyBiasToData</a></div><div class="ttdeci">void ApplyBiasToData(std::vector< T > &v, const std::vector< B > &bias, float vScale, int32_t vOffset, float bScale, int32_t bOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00056">Conv3dTestImpl.cpp:56</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_a83ca447892f460dabaa2f87d3dc3db61"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#a83ca447892f460dabaa2f87d3dc3db61">armnn::Convolution3dDescriptor::m_PadFront</a></div><div class="ttdeci">uint32_t m_PadFront</div><div class="ttdoc">Padding front value in the depth dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00513">Descriptors.hpp:513</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="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Convolution3dDescriptor::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#l00505">Descriptors.hpp:505</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::Convolution3dDescriptor::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#l00507">Descriptors.hpp:507</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a2120193449bfdb913edb0bf2719c33e4"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a2120193449bfdb913edb0bf2719c33e4">armnn::IWorkloadFactory::CreateConvolution3d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateConvolution3d(const Convolution3dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01597">WorkloadFactory.cpp:1597</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a97f335101f2aeb09994ab41d32c09904"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a97f335101f2aeb09994ab41d32c09904">SimpleConvolution3d3x3x3Float32Test</a></div><div class="ttdeci">LayerTestResult< float, 5 > SimpleConvolution3d3x3x3Float32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00857">Conv3dTestImpl.cpp:857</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a4c578ed3b0e74f84354fad1cc40a1d9d"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a4c578ed3b0e74f84354fad1cc40a1d9d">SimpleConvolution3d3x3x3Uint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 5 > SimpleConvolution3d3x3x3Uint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00879">Conv3dTestImpl.cpp:879</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::Convolution3dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NDHWC, NCDHW). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00531">Descriptors.hpp:531</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a94612dea5289f32c0f065f248b412615"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a94612dea5289f32c0f065f248b412615">CreateSmallQuantizedData</a></div><div class="ttdeci">std::vector< T > CreateSmallQuantizedData(int32_t size, float divisor, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00130">Conv3dTestImpl.cpp:130</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a2f8ee10580b676ec08de159a02ff217e"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a2f8ee10580b676ec08de159a02ff217e">SetScaleOffset</a></div><div class="ttdeci">void SetScaleOffset(float &qScale, int32_t &qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00081">Conv3dTestImpl.cpp:81</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a4668f0282ba880fed2768558243ccf00"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a4668f0282ba880fed2768558243ccf00">Convolution3d2x2x2Stride3x3x3SmallTestCommonFloat32</a></div><div class="ttdeci">LayerTestResult< float, 5 > Convolution3d2x2x2Stride3x3x3SmallTestCommonFloat32(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00666">Conv3dTestImpl.cpp:666</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_abd444942e3547d0dce1c48f8455f071f"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#abd444942e3547d0dce1c48f8455f071f">Convolution3d2x3x3TestCommonFloat16</a></div><div class="ttdeci">LayerTestResult< armnn::Half, 5 > Convolution3d2x3x3TestCommonFloat16(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00724">Conv3dTestImpl.cpp:724</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_convolution3d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::Convolution3dDescriptor::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#l00509">Descriptors.hpp:509</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a494edc54ecf36a98b35437e8c2fe1a9e"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a494edc54ecf36a98b35437e8c2fe1a9e">Convolution3dPaddingSame3x3x3Int8Test</a></div><div class="ttdeci">LayerTestResult< int8_t, 5 > Convolution3dPaddingSame3x3x3Int8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l01001">Conv3dTestImpl.cpp:1001</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a6a5b0b2846112d6280e58a36f826635c"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a6a5b0b2846112d6280e58a36f826635c">Convolution3d2x2x2SmallTestCommonFloat16</a></div><div class="ttdeci">LayerTestResult< armnn::Half, 5 > Convolution3d2x2x2SmallTestCommonFloat16(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00794">Conv3dTestImpl.cpp:794</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00042">ITensorHandleFactory.hpp:42</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a58289ea01aec699a91f8184db7bbda20"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a58289ea01aec699a91f8184db7bbda20">Convolution3d2x2x2Strides3x5x5Int16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 5 > Convolution3d2x2x2Strides3x5x5Int16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00935">Conv3dTestImpl.cpp:935</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_aeb54439f726cc853209509e730e876e6"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#aeb54439f726cc853209509e730e876e6">Convolution3d2x2x2Strides3x5x5Uint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 5 > Convolution3d2x2x2Strides3x5x5Uint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00924">Conv3dTestImpl.cpp:924</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a375ca3cff9f1b005d1412dc5f3cf5b6e"><div class="ttname"><a href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00035">NumericCast.hpp:35</a></div></div> +<div class="ttc" id="namespacearmnn_utils_xhtml"><div class="ttname"><a href="namespacearmnn_utils.xhtml">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00013">DataLayoutIndexed.hpp:13</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_ac951dbcec6aa92bad6ca12bca60303cb"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#ac951dbcec6aa92bad6ca12bca60303cb">Convolution3d2x2x2Dilation2x2x2Int8Test</a></div><div class="ttdeci">LayerTestResult< int8_t, 5 > Convolution3d2x2x2Dilation2x2x2Int8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00957">Conv3dTestImpl.cpp:957</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="_conv3d_test_impl_8cpp_xhtml_a0878ba921d9497706bc243ba202f7016"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a0878ba921d9497706bc243ba202f7016">Convolution3d2x2x2Dilation2x2x2TestCommon</a></div><div class="ttdeci">LayerTestResult< T, 5 > Convolution3d2x2x2Dilation2x2x2TestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00443">Conv3dTestImpl.cpp:443</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 TensorInfos of 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#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="namespacearmnn_utils_xhtml_a5135dc1ce7a8aeb97623c1a92c5a3543"><div class="ttname"><a href="namespacearmnn_utils.xhtml#a5135dc1ce7a8aeb97623c1a92c5a3543">armnnUtils::SelectiveDequantize</a></div><div class="ttdeci">float SelectiveDequantize(T value, float scale, int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_quantize_helper_8hpp_source.xhtml#l00091">QuantizeHelper.hpp:91</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a1736a9bf1b2b7f77069e129ff67e03d1"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a1736a9bf1b2b7f77069e129ff67e03d1">Convolution3dPaddingSame3x3x3TestCommon</a></div><div class="ttdeci">LayerTestResult< T, 5 > Convolution3dPaddingSame3x3x3TestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00510">Conv3dTestImpl.cpp:510</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_ac176698dda319e6958ec8fdc658f3771"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#ac176698dda319e6958ec8fdc658f3771">Convolution3d2x2x2Dilation2x2x2Int16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 5 > Convolution3d2x2x2Dilation2x2x2Int16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00979">Conv3dTestImpl.cpp:979</a></div></div> +<div class="ttc" id="_conv3d_test_impl_8cpp_xhtml_a9ca270ac2dc3cd87e835716606be9e65"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#a9ca270ac2dc3cd87e835716606be9e65">CreateQuantizedData</a></div><div class="ttdeci">std::vector< T > CreateQuantizedData(int32_t size, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00117">Conv3dTestImpl.cpp:117</a></div></div> +<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml_a861b2621ee46e4b63379988b360b8cd9"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml#a861b2621ee46e4b63379988b360b8cd9">armnnUtils::DataLayoutIndexed::GetChannelsIndex</a></div><div class="ttdeci">unsigned int GetChannelsIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00023">DataLayoutIndexed.hpp:23</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_a16543bce17aa2e4d6e81c88f74227192"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#a16543bce17aa2e4d6e81c88f74227192">armnn::Convolution3dDescriptor::m_DilationZ</a></div><div class="ttdeci">uint32_t m_DilationZ</div><div class="ttdoc">Dilation along z axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00527">Descriptors.hpp:527</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="_conv3d_test_impl_8cpp_xhtml_aff7f671b6c142a9a27f6de42163c31bc"><div class="ttname"><a href="_conv3d_test_impl_8cpp.xhtml#aff7f671b6c142a9a27f6de42163c31bc">Convolution3d2x2x2Dilation2x2x2Float32Test</a></div><div class="ttdeci">LayerTestResult< float, 5 > Convolution3d2x2x2Dilation2x2x2Float32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, bool biasEnabled, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_conv3d_test_impl_8cpp_source.xhtml#l00946">Conv3dTestImpl.cpp:946</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_a5164336f6a1b15be0d434a6bbf7289da"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#a5164336f6a1b15be0d434a6bbf7289da">armnn::Convolution3dDescriptor::m_StrideZ</a></div><div class="ttdeci">uint32_t m_StrideZ</div><div class="ttdoc">Stride value when proceeding through input for the depth dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00521">Descriptors.hpp:521</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution3d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_convolution3d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::Convolution3dDescriptor::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#l00525">Descriptors.hpp:525</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><!-- 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="_conv3d_test_impl_8cpp.xhtml">Conv3dTestImpl.cpp</a></li> + <li class="footer">Generated on Wed Nov 17 2021 12:59:34 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> |