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| author | Nikhil Raj <nikhil.raj@arm.com> | 2022-06-17 13:24:58 +0100 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-06-17 13:24:58 +0100 |
| commit | d5d43d82c0137e08553e44345c609cdd1a7931c7 (patch) | |
| tree | f1509f7fa94db0373a2c127682dd3d0ccc1915bd /22.05.01/_ref_create_workload_tests_8cpp_source.xhtml | |
| parent | 549b9600a6eaf0727fa084465a75f173edf8f381 (diff) | |
| download | armnn-d5d43d82c0137e08553e44345c609cdd1a7931c7.tar.gz | |
Update Doxygen for 22.05 patch release
* Pooling3D added to tfLite delegate
* Available in tag 22.05.01
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: I8d605bba4e87d30baa2c6d7b338c78a4400dc021
Diffstat (limited to '22.05.01/_ref_create_workload_tests_8cpp_source.xhtml')
| -rw-r--r-- | 22.05.01/_ref_create_workload_tests_8cpp_source.xhtml | 135 |
1 files changed, 135 insertions, 0 deletions
diff --git a/22.05.01/_ref_create_workload_tests_8cpp_source.xhtml b/22.05.01/_ref_create_workload_tests_8cpp_source.xhtml new file mode 100644 index 0000000000..a7387c8dfa --- /dev/null +++ b/22.05.01/_ref_create_workload_tests_8cpp_source.xhtml @@ -0,0 +1,135 @@ +<!-- 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/reference/test/RefCreateWorkloadTests.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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">22.05.01</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(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('_ref_create_workload_tests_8cpp_source.xhtml','');}); +</script> +<div id="doc-content"> +<!-- window showing the filter options --> +<div id="MSearchSelectWindow" + onmouseover="return searchBox.OnSearchSelectShow()" + onmouseout="return searchBox.OnSearchSelectHide()" + onkeydown="return searchBox.OnSearchSelectKey(event)"> +</div> + +<!-- iframe showing the search results (closed by default) --> +<div id="MSearchResultsWindow"> +<iframe src="javascript:void(0)" frameborder="0" + name="MSearchResults" id="MSearchResults"> +</iframe> +</div> + +<div class="header"> + <div class="headertitle"> +<div class="title">RefCreateWorkloadTests.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_ref_create_workload_tests_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include <CreateWorkload.hpp></span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_polymorphic_downcast_8hpp.xhtml">armnn/utility/PolymorphicDowncast.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_ref_tensor_handle_8hpp.xhtml">reference/RefTensorHandle.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_ref_tensor_handle_factory_8hpp.xhtml">reference/RefTensorHandleFactory.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_ref_workload_factory_8hpp.xhtml">reference/RefWorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_ref_workloads_8hpp.xhtml">reference/workloads/RefWorkloads.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 <doctest/doctest.h></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="keyword">namespace</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> </div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="keyword">template</span><<span class="keyword">typename</span> Workload></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="keywordtype">void</span> CheckInputOutput(std::unique_ptr<Workload> workload, <span class="keyword">const</span> TensorInfo& inputInfo, <span class="keyword">const</span> TensorInfo& outputInfo)</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> {</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="keyword">auto</span> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  CHECK((inputHandle->GetTensorInfo() == inputInfo));</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  CHECK((outputHandle->GetTensorInfo() == outputInfo));</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> }</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="keyword">template</span> <<span class="keyword">typename</span> Workload></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keywordtype">void</span> CheckInputsOutput(std::unique_ptr<Workload> workload,</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keyword">const</span> TensorInfo& inputInfo0,</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keyword">const</span> TensorInfo& inputInfo1,</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keyword">const</span> TensorInfo& outputInfo)</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> {</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keyword">auto</span> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">auto</span> inputHandle0 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keyword">auto</span> inputHandle1 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[1]);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  CHECK((inputHandle0->GetTensorInfo() == inputInfo0));</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  CHECK((inputHandle1->GetTensorInfo() == inputInfo1));</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  CHECK((outputHandle->GetTensorInfo() == outputInfo));</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> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">armnn::RefWorkloadFactory</a> GetFactory()</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> {</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  std::shared_ptr<RefMemoryManager> memoryManager = std::make_shared<RefMemoryManager>();</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">return</span> RefWorkloadFactory(memoryManager);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> }</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 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"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aeae58109674c5194001eb936c8e015b7"> 52</a></span> <a class="code" href="_ref_create_workload_tests_8cpp.xhtml#aeae58109674c5194001eb936c8e015b7">TEST_SUITE</a>(<span class="stringliteral">"CreateWorkloadRef"</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="keyword">template</span> <<span class="keyword">typename</span> ActivationWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateActivationWorkloadTest()</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> {</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  Graph graph;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">auto</span> workload = CreateActivationWorkloadTest<ActivationWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="comment">// Checks that outputs are as we expect them (see definition of CreateActivationWorkloadTest).</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  TensorInfo({ 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  TensorInfo({ 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> }</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> TEST_CASE(<span class="stringliteral">"CreateActivationFloat32Workload"</span>)</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  RefCreateActivationWorkloadTest<RefActivationWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> }</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> TEST_CASE(<span class="stringliteral">"CreateActivationUint8Workload"</span>)</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  RefCreateActivationWorkloadTest<RefActivationWorkload, armnn::DataType::QAsymmU8>();</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> <span class="keyword">template</span> <<span class="keyword">typename</span> WorkloadType,</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">typename</span> DescriptorType,</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">typename</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>,</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateElementwiseWorkloadTest()</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>  Graph graph;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keyword">auto</span> workload = CreateElementwiseWorkloadTest<WorkloadType, DescriptorType, LayerType, DataType>(</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  factory, graph);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  CheckInputsOutput(std::move(workload),</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  TensorInfo({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  TensorInfo({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  TensorInfo({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</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> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> TEST_CASE(<span class="stringliteral">"CreateSubtractionWorkloadWithBlobTest"</span>)</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> {</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  Graph graph;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>;</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">auto</span> workload = CreateSubtractionWithBlobWorkloadTest<RefSubtractionWorkload<>,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  SubtractionQueueDescriptor,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  (factory, graph);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  CheckInputsOutput(std::move(workload),</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  TensorInfo({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  TensorInfo({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  TensorInfo({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> }</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> TEST_CASE(<span class="stringliteral">"CreateAdditionWorkloadWithBlobTest"</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>  Graph graph;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keyword">auto</span> workload = CreateAdditionWithBlobWorkloadTest<RefAdditionWorkload<>,</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  AdditionQueueDescriptor,</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>(factory, graph);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  CheckInputsOutput(std::move(workload),</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  TensorInfo({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  TensorInfo({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  TensorInfo({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> }</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> </div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> TEST_CASE(<span class="stringliteral">"CreateMultiplicationWorkloadWithBlobTest"</span>)</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> {</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  Graph graph;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> </div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keyword">auto</span> workload = CreateMultiplicationWithBlobWorkloadTest<RefMultiplicationWorkload<>,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  MultiplicationQueueDescriptor,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>(factory, graph);</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  CheckInputsOutput(std::move(workload),</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  TensorInfo({2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  TensorInfo({2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  TensorInfo({2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</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> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> TEST_CASE(<span class="stringliteral">"CreateAdditionFloatWorkload"</span>)</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> {</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  RefCreateElementwiseWorkloadTest<RefAdditionWorkload<>,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  AdditionQueueDescriptor,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  AdditionLayer,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>();</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> }</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> TEST_CASE(<span class="stringliteral">"CreateAdditionUint8Workload"</span>)</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> {</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  RefCreateElementwiseWorkloadTest<RefAdditionWorkload<>,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  AdditionQueueDescriptor,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  AdditionLayer,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>>();</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> }</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> </div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> TEST_CASE(<span class="stringliteral">"CreateAdditionInt16Workload"</span>)</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> {</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  RefCreateElementwiseWorkloadTest<RefAdditionWorkload<>,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  AdditionQueueDescriptor,</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  AdditionLayer,</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>>();</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> }</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> TEST_CASE(<span class="stringliteral">"CreateAdditionInt32Workload"</span>)</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> {</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  RefCreateElementwiseWorkloadTest<RefAdditionWorkload<int32_t>,</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  AdditionQueueDescriptor,</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  AdditionLayer,</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>>();</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> }</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> TEST_CASE(<span class="stringliteral">"CreateSubtractionFloat32Workload"</span>)</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>  RefCreateElementwiseWorkloadTest<RefSubtractionWorkload<>,</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  SubtractionQueueDescriptor,</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  SubtractionLayer,</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>();</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> }</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> TEST_CASE(<span class="stringliteral">"CreateSubtractionFloat16Workload"</span>)</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> {</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  RefCreateElementwiseWorkloadTest<RefSubtractionWorkload<>,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  SubtractionQueueDescriptor,</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  SubtractionLayer,</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>>();</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> }</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> TEST_CASE(<span class="stringliteral">"CreateSubtractionUint8Workload"</span>)</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> {</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  RefCreateElementwiseWorkloadTest<RefSubtractionWorkload<>,</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  SubtractionQueueDescriptor,</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  SubtractionLayer,</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>>();</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> </div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> TEST_CASE(<span class="stringliteral">"CreateSubtractionInt16Workload"</span>)</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> {</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  RefCreateElementwiseWorkloadTest<RefSubtractionWorkload<>,</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  SubtractionQueueDescriptor,</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  SubtractionLayer,</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>>();</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> }</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> TEST_CASE(<span class="stringliteral">"CreateSubtractionInt32Workload"</span>)</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> {</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  RefCreateElementwiseWorkloadTest<RefSubtractionWorkload<int32_t>,</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  SubtractionQueueDescriptor,</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  SubtractionLayer,</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>>();</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> }</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> </div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> TEST_CASE(<span class="stringliteral">"CreateMultiplicationFloatWorkload"</span>)</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> {</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  RefCreateElementwiseWorkloadTest<RefMultiplicationWorkload<>,</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  MultiplicationQueueDescriptor,</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  MultiplicationLayer,</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>();</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> }</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> </div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> TEST_CASE(<span class="stringliteral">"CreateMultiplicationUint8Workload"</span>)</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> {</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  RefCreateElementwiseWorkloadTest<RefMultiplicationWorkload<>,</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  MultiplicationQueueDescriptor,</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  MultiplicationLayer,</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>>();</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> </div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> TEST_CASE(<span class="stringliteral">"CreateMultiplicationInt16Workload"</span>)</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> {</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  RefCreateElementwiseWorkloadTest<RefMultiplicationWorkload<>,</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  MultiplicationQueueDescriptor,</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  MultiplicationLayer,</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>>();</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> }</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> TEST_CASE(<span class="stringliteral">"CreateMultiplicationInt32Workload"</span>)</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> {</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  RefCreateElementwiseWorkloadTest<RefMultiplicationWorkload<int32_t>,</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  MultiplicationQueueDescriptor,</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  MultiplicationLayer,</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>>();</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> </div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> TEST_CASE(<span class="stringliteral">"CreateDivisionFloat32Workload"</span>)</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> {</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  RefCreateElementwiseWorkloadTest<RefDivisionWorkload<>,</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  DivisionQueueDescriptor,</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  DivisionLayer,</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>();</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> }</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> </div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> TEST_CASE(<span class="stringliteral">"CreateDivisionFloat16Workload"</span>)</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> {</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  RefCreateElementwiseWorkloadTest<RefDivisionWorkload<>,</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  DivisionQueueDescriptor,</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  DivisionLayer,</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>>();</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> }</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> </div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> TEST_CASE(<span class="stringliteral">"CreateDivisionUint8Workload"</span>)</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> {</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  RefCreateElementwiseWorkloadTest<RefDivisionWorkload<>,</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  DivisionQueueDescriptor,</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  DivisionLayer,</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>>();</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> }</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> </div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> TEST_CASE(<span class="stringliteral">"CreateDivisionInt16Workload"</span>)</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> {</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  RefCreateElementwiseWorkloadTest<RefDivisionWorkload<>,</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  DivisionQueueDescriptor,</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  DivisionLayer,</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>>();</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> </div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> TEST_CASE(<span class="stringliteral">"CreateDivisionInt32Workload"</span>)</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> {</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  RefCreateElementwiseWorkloadTest<RefDivisionWorkload<int32_t>,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  DivisionQueueDescriptor,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  DivisionLayer,</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>>();</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> }</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="keyword">template</span> <<span class="keyword">typename</span> BatchNormalizationWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateBatchNormalizationWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</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>  Graph graph;</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keyword">auto</span> workload = CreateBatchNormalizationWorkloadTest<BatchNormalizationWorkloadType, DataType>(factory,</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  graph,</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  dataLayout);</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> </div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  TensorShape inputShape;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  TensorShape outputShape;</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  {</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  inputShape = { 2, 4, 4, 3 };</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  outputShape = { 2, 4, 4, 3 };</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  inputShape = { 2, 3, 4, 4 };</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  outputShape = { 2, 3, 4, 4 };</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordflow">break</span>;</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> </div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest).</span></div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  CheckInputOutput(std::move(workload), TensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>), TensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> }</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> </div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> TEST_CASE(<span class="stringliteral">"CreateBatchNormalizationWithBlobFloat32Workload"</span>)</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> {</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  Graph graph;</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keyword">auto</span> dataType = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>;</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keyword">auto</span> workload = CreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload,</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>(factory, graph, DataLayout::NHWC);</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> </div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  TensorShape inputShape;</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  TensorShape outputShape;</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> </div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  inputShape = { 2, 4, 4, 3 };</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  outputShape = { 2, 4, 4, 3 };</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest).</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  CheckInputOutput(std::move(workload), TensorInfo(inputShape, dataType), TensorInfo(outputShape, dataType));</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> </div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> TEST_CASE(<span class="stringliteral">"CreateBatchNormalizationFloat32Workload"</span>)</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> {</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload,armnn::DataType::Float32></div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  (DataLayout::NCHW);</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> }</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> </div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span> TEST_CASE(<span class="stringliteral">"CreateBatchNormalizationFloat32WorkloadNhwc"</span>)</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> {</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::Float32></div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  (DataLayout::NHWC);</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span> }</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span> TEST_CASE(<span class="stringliteral">"CreateBatchNormalizationFloat16Workload"</span>)</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> {</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload,armnn::DataType::Float16></div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  (DataLayout::NCHW);</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span> }</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> </div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> TEST_CASE(<span class="stringliteral">"CreateBatchNormalizationFloat16WorkloadNhwc"</span>)</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> {</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::Float16></div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  (DataLayout::NHWC);</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> }</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> </div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> TEST_CASE(<span class="stringliteral">"CreateBatchNormalizationUint8Workload"</span>)</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span> {</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::QAsymmU8></div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  (DataLayout::NCHW);</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span> }</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> </div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span> TEST_CASE(<span class="stringliteral">"CreateBatchNormalizationUint8WorkloadNhwc"</span>)</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span> {</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::QAsymmU8></div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  (DataLayout::NHWC);</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> </div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> TEST_CASE(<span class="stringliteral">"CreateBatchNormalizationInt16Workload"</span>)</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span> {</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::QSymmS16></div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  (DataLayout::NCHW);</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> }</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> </div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> TEST_CASE(<span class="stringliteral">"CreateBatchNormalizationInt16WorkloadNhwc"</span>)</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> {</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  RefCreateBatchNormalizationWorkloadTest<RefBatchNormalizationWorkload, armnn::DataType::QSymmS16></div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  (DataLayout::NHWC);</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> }</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span> </div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> TEST_CASE(<span class="stringliteral">"CreateConvertFp16ToFp32Float32Workload"</span>)</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> {</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  Graph graph;</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="keyword">auto</span> workload = CreateConvertFp16ToFp32WorkloadTest<RefConvertFp16ToFp32Workload>(factory, graph);</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> </div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="comment">// Checks that outputs and inputs are as we expect them</span></div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  CheckInputOutput(</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  std::move(workload), TensorInfo({1, 3, 2, 3}, DataType::Float16), TensorInfo({1, 3, 2, 3}, DataType::Float32));</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> }</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span> </div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> TEST_CASE(<span class="stringliteral">"CreateConvertFp32ToFp16Float16Workload"</span>)</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> {</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  Graph graph;</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keyword">auto</span> workload = CreateConvertFp32ToFp16WorkloadTest<RefConvertFp32ToFp16Workload>(factory, graph);</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span> </div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="comment">// Checks that outputs and inputs are as we expect them</span></div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  CheckInputOutput(</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  std::move(workload), TensorInfo({1, 3, 2, 3}, DataType::Float32), TensorInfo({1, 3, 2, 3}, DataType::Float16));</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span> }</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span> </div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateConvolution2dWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout = DataLayout::NCHW)</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span> {</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  Graph graph;</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keyword">auto</span> workload = CreateConvolution2dWorkloadTest<RefConvolution2dWorkload, DataType::Float32></div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  (factory, graph, dataLayout);</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span> </div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({2, 3, 8, 16})</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  : std::initializer_list<unsigned int>({2, 8, 16, 3});</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({2, 2, 2, 10})</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  : std::initializer_list<unsigned int>({2, 2, 10, 2});</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> </div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest).</span></div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  TensorInfo(inputShape, DataType::Float32),</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  TensorInfo(outputShape, DataType::Float32));</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span> }</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span> </div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span> TEST_CASE(<span class="stringliteral">"CreateConvolution2dFloatNchwWorkload"</span>)</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span> {</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  RefCreateConvolution2dWorkloadTest(DataLayout::NCHW);</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span> }</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> </div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> TEST_CASE(<span class="stringliteral">"CreateConvolution2dFloatNhwcWorkload"</span>)</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> {</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  RefCreateConvolution2dWorkloadTest(DataLayout::NHWC);</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span> }</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span> </div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span> TEST_CASE(<span class="stringliteral">"CreateConvolution2dWithBlobWorkload"</span>)</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span> {</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout = DataLayout::NHWC;</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  Graph graph;</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keyword">auto</span> workload = CreateConvolution2dFusedActivationWithBlobWorkloadTest<RefConvolution2dWorkload, DataType::Float32></div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  (factory, graph, dataLayout);</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>  TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({2, 3, 8, 16})</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  : std::initializer_list<unsigned int>({2, 8, 16, 3});</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({2, 2, 2, 10})</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  : std::initializer_list<unsigned int>({2, 2, 10, 2});</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span> </div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest).</span></div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  TensorInfo(inputShape, DataType::Float32),</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  TensorInfo(outputShape, DataType::Float32));</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> </div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateDepthwiseConvolutionWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span> {</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  Graph graph;</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <span class="keyword">auto</span> workload = CreateDepthwiseConvolution2dWorkloadTest<RefDepthwiseConvolution2dWorkload, DataType::Float32></div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  (factory, graph, dataLayout);</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span> </div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 2, 2, 5, 5 })</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  : std::initializer_list<unsigned int>({ 2, 5, 5, 2 });</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 2, 2, 5, 5 })</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  : std::initializer_list<unsigned int>({ 2, 5, 5, 2 });</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>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateDepthwiseConvolution2dWorkloadTest).</span></div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  TensorInfo(inputShape, DataType::Float32),</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  TensorInfo(outputShape, DataType::Float32));</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span> }</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span> </div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span> TEST_CASE(<span class="stringliteral">"CreateDepthwiseConvolutionFloat32NhwcWorkload"</span>)</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span> {</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  RefCreateDepthwiseConvolutionWorkloadTest(DataLayout::NHWC);</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> </div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span> TEST_CASE(<span class="stringliteral">"RefCreateFullyConnectedWithBlobWorkloadTest"</span>)</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span> {</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  Graph graph;</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <span class="keyword">auto</span> workload = CreateFullyConnectedWithBlobWorkloadTest<RefFullyConnectedWorkload,</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>(factory, graph);</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span> </div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest).</span></div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <span class="keywordtype">float</span> inputsQScale = 0.0f;</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <span class="keywordtype">float</span> outputQScale = 0.0f;</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  TensorInfo({ 3, 1, 4, 5 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, inputsQScale),</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  TensorInfo({ 3, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, outputQScale));</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span> }</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span> </div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> TEST_CASE(<span class="stringliteral">"CreateFullyConnectedWorkloadWeightsBiasesAsInputsFloat32"</span>)</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span> {</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  Graph graph;</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span> </div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <span class="keyword">auto</span> workload =</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest<RefFullyConnectedWorkload,</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>(factory, graph);</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span> </div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest).</span></div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <span class="keywordtype">float</span> inputsQScale = 0.0f;</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <span class="keywordtype">float</span> outputQScale = 0.0f;</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  CheckInputsOutput(std::move(workload),</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  TensorInfo({ 3, 1, 4, 5 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, inputsQScale),</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  TensorInfo({ 7, 20 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, inputsQScale),</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  TensorInfo({ 3, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, outputQScale));</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> <<span class="keyword">typename</span> FullyConnectedWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateFullyConnectedWorkloadTest()</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span> {</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  Graph graph;</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <span class="keyword">auto</span> workload = CreateFullyConnectedWorkloadTest<FullyConnectedWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span> </div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest).</span></div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <span class="keywordtype">float</span> inputsQScale = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a> ? 1.0f : 0.0;</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  <span class="keywordtype">float</span> outputQScale = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a> ? 2.0f : 0.0;</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  TensorInfo({ 3, 1, 4, 5 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>, inputsQScale),</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  TensorInfo({ 3, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>, outputQScale));</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> </div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span> TEST_CASE(<span class="stringliteral">"CreateFullyConnectedWorkloadFloat32"</span>)</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>  RefCreateFullyConnectedWorkloadTest<RefFullyConnectedWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span> }</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span> </div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span> TEST_CASE(<span class="stringliteral">"CreateFullyConnectedWorkloadQuantisedAsymm8"</span>)</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span> {</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  RefCreateFullyConnectedWorkloadTest<RefFullyConnectedWorkload, armnn::DataType::QAsymmU8>();</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> </div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span> TEST_CASE(<span class="stringliteral">"CreateFullyConnectedWorkloadQuantisedSymm16"</span>)</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span> {</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  RefCreateFullyConnectedWorkloadTest<RefFullyConnectedWorkload, armnn::DataType::QSymmS16>();</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span> }</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span> </div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span> <span class="keyword">template</span> <<span class="keyword">typename</span> NormalizationWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateNormalizationWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span> {</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  Graph graph;</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  <span class="keyword">auto</span> workload = CreateNormalizationWorkloadTest<NormalizationWorkloadType, DataType>(factory, graph, dataLayout);</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>  TensorShape inputShape;</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  TensorShape outputShape;</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span> </div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  {</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  inputShape = { 3, 1, 5, 5 };</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  outputShape = { 3, 1, 5, 5 };</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  inputShape = { 3, 5, 5, 1 };</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  outputShape = { 3, 5, 5, 1 };</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  }</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span> </div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateNormalizationWorkloadTest).</span></div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  CheckInputOutput(std::move(workload), TensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>), TensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</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> </div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span> TEST_CASE(<span class="stringliteral">"CreateRefNormalizationFloat32NchwWorkload"</span>)</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span> {</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::Float32>(DataLayout::NCHW);</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span> }</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span> </div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span> TEST_CASE(<span class="stringliteral">"CreateRefNormalizationFloat32NhwcWorkload"</span>)</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span> {</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::Float32>(DataLayout::NHWC);</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span> }</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span> </div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span> TEST_CASE(<span class="stringliteral">"CreateRefNormalizationUint8NchwWorkload"</span>)</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span> {</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::QAsymmU8>(DataLayout::NCHW);</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span> }</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span> </div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span> TEST_CASE(<span class="stringliteral">"CreateRefNormalizationUint8NhwcWorkload"</span>)</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span> {</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::QAsymmU8>(DataLayout::NHWC);</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span> }</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span> </div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span> TEST_CASE(<span class="stringliteral">"CreateRefNormalizationInt16NchwWorkload"</span>)</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span> {</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::QSymmS16>(DataLayout::NCHW);</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span> }</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span> </div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span> TEST_CASE(<span class="stringliteral">"CreateRefNormalizationInt16NhwcWorkload"</span>)</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span> {</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  RefCreateNormalizationWorkloadTest<RefNormalizationWorkload, armnn::DataType::QSymmS16>(DataLayout::NHWC);</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span> }</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span> </div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span> <span class="keyword">template</span> <<span class="keyword">typename</span> Pooling2dWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreatePooling2dWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span> {</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  Graph graph;</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <span class="keyword">auto</span> workload = CreatePooling2dWorkloadTest<Pooling2dWorkloadType, DataType>(factory, graph, dataLayout);</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span> </div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  TensorShape inputShape;</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  TensorShape outputShape;</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span> </div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  {</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  inputShape = { 3, 5, 5, 2 };</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  outputShape = { 3, 2, 4, 2 };</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  inputShape = { 3, 2, 5, 5 };</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  outputShape = { 3, 2, 2, 4 };</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  }</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span> </div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreatePooling2dWorkloadTest).</span></div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  TensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  TensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span> }</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span> </div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span> TEST_CASE(<span class="stringliteral">"CreatePooling2dFloat32Workload"</span>)</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span> {</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::Float32>(DataLayout::NCHW);</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> </div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span> TEST_CASE(<span class="stringliteral">"CreatePooling2dFloat32NhwcWorkload"</span>)</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span> {</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::Float32>(DataLayout::NHWC);</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> </div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span> TEST_CASE(<span class="stringliteral">"CreatePooling2dUint8Workload"</span>)</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span> {</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::QAsymmU8>(DataLayout::NCHW);</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> TEST_CASE(<span class="stringliteral">"CreatePooling2dUint8NhwcWorkload"</span>)</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span> {</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::QAsymmU8>(DataLayout::NHWC);</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span> }</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span> </div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span> TEST_CASE(<span class="stringliteral">"CreatePooling2dInt16Workload"</span>)</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span> {</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::QSymmS16>(DataLayout::NCHW);</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span> }</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span> </div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span> TEST_CASE(<span class="stringliteral">"CreatePooling2dInt16NhwcWorkload"</span>)</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span> {</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  RefCreatePooling2dWorkloadTest<RefPooling2dWorkload, armnn::DataType::QSymmS16>(DataLayout::NHWC);</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span> }</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span> </div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span> <span class="keyword">template</span> <<span class="keyword">typename</span> SoftmaxWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateSoftmaxWorkloadTest()</div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span> {</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  Graph graph;</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <span class="keyword">auto</span> workload = CreateSoftmaxWorkloadTest<SoftmaxWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span> </div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateSoftmaxWorkloadTest).</span></div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span> </div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo({4, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>);</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>)</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>  tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(0);</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  tensorInfo.SetQuantizationScale(1.f / 256);</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  }</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>)</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  {</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  tensorInfo.SetQuantizationOffset(-128);</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  tensorInfo.SetQuantizationScale(1.f / 256);</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  }</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  CheckInputOutput(</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  std::move(workload),</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  tensorInfo,</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  tensorInfo);</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span> }</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span> </div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span> TEST_CASE(<span class="stringliteral">"CreateSoftmaxFloat32Workload"</span>)</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span> {</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  RefCreateSoftmaxWorkloadTest<RefSoftmaxWorkload, armnn::DataType::Float32>();</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> </div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span> TEST_CASE(<span class="stringliteral">"CreateSoftmaxFloat16Workload"</span>)</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span> {</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  RefCreateSoftmaxWorkloadTest<RefSoftmaxWorkload, armnn::DataType::Float16>();</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span> }</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span> </div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span> TEST_CASE(<span class="stringliteral">"CreateSoftmaxQuantisedAsymm8Workload"</span>)</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>  RefCreateSoftmaxWorkloadTest<RefSoftmaxWorkload, armnn::DataType::QAsymmU8>();</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span> }</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span> </div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span> TEST_CASE(<span class="stringliteral">"CreateSoftmaxQuantisedSymm16Workload"</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>  RefCreateSoftmaxWorkloadTest<RefSoftmaxWorkload, armnn::DataType::QSymmS16>();</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span> }</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span> </div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span> <span class="keyword">template</span> <<span class="keyword">typename</span> SplitterWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateSplitterWorkloadTest()</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span> {</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  Graph graph;</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <span class="keyword">auto</span> workload = CreateSplitterWorkloadTest<SplitterWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span> </div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  <span class="comment">// Checks that outputs are as we expect them (see definition of CreateSplitterWorkloadTest).</span></div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  SplitterQueueDescriptor queueDescriptor = workload->GetData();</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  CHECK((inputHandle->GetTensorInfo() == TensorInfo({ 5, 7, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span> </div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  <span class="keyword">auto</span> outputHandle0 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  CHECK((outputHandle0->GetTensorInfo() == TensorInfo({ 1, 7, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span> </div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <span class="keyword">auto</span> outputHandle1 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[1]);</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  CHECK((outputHandle1->GetTensorInfo() == TensorInfo({ 2, 7, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span> </div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <span class="keyword">auto</span> outputHandle2 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[2]);</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  CHECK((outputHandle2->GetTensorInfo() == TensorInfo({ 2, 7, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span> }</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span> </div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span> TEST_CASE(<span class="stringliteral">"CreateSplitterFloat32Workload"</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>  RefCreateSplitterWorkloadTest<RefSplitterWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span> }</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span> </div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span> TEST_CASE(<span class="stringliteral">"CreateSplitterFloat16Workload"</span>)</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span> {</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  RefCreateSplitterWorkloadTest<RefSplitterWorkload, armnn::DataType::Float16>();</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span> }</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span> </div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span> TEST_CASE(<span class="stringliteral">"CreateSplitterUint8Workload"</span>)</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span> {</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  RefCreateSplitterWorkloadTest<RefSplitterWorkload, armnn::DataType::QAsymmU8>();</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span> }</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span> </div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span> <span class="keyword">template</span> <<span class="keyword">typename</span> SplitterWorkloadType, <span class="keyword">typename</span> ConcatWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateSplitterConcatWorkloadTest()</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span> {</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  <span class="comment">// Tests that it is possible to decide which output of the splitter layer</span></div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  <span class="comment">// should be lined to which input of the concat layer.</span></div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  <span class="comment">// We tested that is is possible to specify 0th output</span></div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  <span class="comment">// of the splitter to be the 1st input to the concat and the 1st output of the splitter to be 0th input</span></div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  <span class="comment">// of the concat.</span></div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span> </div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  Graph graph;</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  <span class="keyword">auto</span> workloads = CreateSplitterConcatWorkloadTest<SplitterWorkloadType, ConcatWorkloadType, DataType></div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  (factory, graph);</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span> </div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  <span class="keyword">auto</span> wlSplitter = std::move(workloads.first);</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  <span class="keyword">auto</span> wlConcat = std::move(workloads.second);</div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span> </div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <span class="comment">//Checks that the index of inputs/outputs matches what we declared on InputDescriptor construction.</span></div><div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* sOut0 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[0]);</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* sOut1 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[1]);</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* mIn0 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">></span>(wlConcat->GetData().m_Inputs[0]);</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* mIn1 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">></span>(wlConcat->GetData().m_Inputs[1]);</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>  CHECK(sOut0);</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  CHECK(sOut1);</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  CHECK(mIn0);</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  CHECK(mIn1);</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span> </div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  <span class="keywordtype">bool</span> validDataPointers = (sOut0 == mIn1) && (sOut1 == mIn0);</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span> </div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  CHECK(validDataPointers);</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> </div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span> TEST_CASE(<span class="stringliteral">"CreateSplitterConcatFloat32"</span>)</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>  RefCreateSplitterConcatWorkloadTest<RefSplitterWorkload, RefConcatWorkload, DataType::Float32>();</div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span> }</div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span> </div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span> TEST_CASE(<span class="stringliteral">"CreateSplitterConcatFloat16"</span>)</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span> {</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  RefCreateSplitterConcatWorkloadTest<RefSplitterWorkload, RefConcatWorkload, DataType::Float16>();</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> </div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span> TEST_CASE(<span class="stringliteral">"CreateSplitterConcatUint8"</span>)</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span> {</div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  RefCreateSplitterConcatWorkloadTest<RefSplitterWorkload, RefConcatWorkload, DataType::QAsymmU8>();</div><div class="line"><a name="l00781"></a><span class="lineno"> 781</span> }</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span> </div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span> <span class="keyword">template</span> <<span class="keyword">typename</span> SplitterWorkloadType, <span class="keyword">typename</span> ActivationWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateSingleOutputMultipleInputsTest()</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span> {</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  <span class="comment">// Tests that it is possible to assign multiple (two) different layers to each of the outputs of a splitter layer.</span></div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  <span class="comment">// We created a splitter with two outputs. That each of those outputs is used by two different activation layers.</span></div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span> </div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  Graph graph;</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  std::unique_ptr<SplitterWorkloadType> wlSplitter;</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  std::unique_ptr<ActivationWorkloadType> wlActiv0_0;</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  std::unique_ptr<ActivationWorkloadType> wlActiv0_1;</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  std::unique_ptr<ActivationWorkloadType> wlActiv1_0;</div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  std::unique_ptr<ActivationWorkloadType> wlActiv1_1;</div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span> </div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  CreateSplitterMultipleInputsOneOutputWorkloadTest<SplitterWorkloadType,</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  ActivationWorkloadType, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>>(factory, graph, wlSplitter, wlActiv0_0, wlActiv0_1, wlActiv1_0, wlActiv1_1);</div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span> </div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* sOut0 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[0]);</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* sOut1 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[1]);</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* activ0_0Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">></span>(wlActiv0_0->GetData().m_Inputs[0]);</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* activ0_1Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">></span>(wlActiv0_1->GetData().m_Inputs[0]);</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* activ1_0Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">></span>(wlActiv1_0->GetData().m_Inputs[0]);</div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* activ1_1Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">></span>(wlActiv1_1->GetData().m_Inputs[0]);</div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span> </div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span> </div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  CHECK(sOut0);</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  CHECK(sOut1);</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  CHECK(activ0_0Im);</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  CHECK(activ0_1Im);</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  CHECK(activ1_0Im);</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  CHECK(activ1_1Im);</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span> </div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  <span class="keywordtype">bool</span> validDataPointers = (sOut0 == activ0_0Im) && (sOut0 == activ0_1Im) &&</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  (sOut1 == activ1_0Im) && (sOut1 == activ1_1Im);</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span> </div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  CHECK(validDataPointers);</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> </div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span> TEST_CASE(<span class="stringliteral">"CreateSingleOutputMultipleInputsFloat32"</span>)</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>  RefCreateSingleOutputMultipleInputsTest<RefSplitterWorkload, RefActivationWorkload,</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>();</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span> }</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span> </div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span> TEST_CASE(<span class="stringliteral">"CreateSingleOutputMultipleInputsUint8"</span>)</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>  RefCreateSingleOutputMultipleInputsTest<RefSplitterWorkload, RefActivationWorkload,</div><div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>>();</div><div class="line"><a name="l00831"></a><span class="lineno"> 831</span> }</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span> </div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span> <span class="keyword">template</span> <<span class="keyword">typename</span> ResizeBilinearWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateResizeBilinearTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span> {</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  Graph graph;</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  <span class="keyword">auto</span> workload = CreateResizeBilinearWorkloadTest<ResizeBilinearWorkloadType, DataType>(factory, graph, dataLayout);</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>  TensorShape inputShape;</div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  TensorShape outputShape;</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span> </div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  {</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  inputShape = { 2, 4, 4, 3 };</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  outputShape = { 2, 2, 2, 3 };</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  inputShape = { 2, 3, 4, 4 };</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  outputShape = { 2, 3, 2, 2 };</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  }</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>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateResizeBilinearWorkloadTest).</span></div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  TensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  TensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span> }</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span> </div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span> TEST_CASE(<span class="stringliteral">"CreateResizeBilinearFloat32"</span>)</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span> {</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  RefCreateResizeBilinearTest<RefResizeWorkload, armnn::DataType::Float32>(DataLayout::NCHW);</div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span> }</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span> </div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span> TEST_CASE(<span class="stringliteral">"CreateResizeBilinearFloat16"</span>)</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span> {</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span>  RefCreateResizeBilinearTest<RefResizeWorkload, armnn::DataType::Float16>(DataLayout::NCHW);</div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span> }</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span> </div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span> TEST_CASE(<span class="stringliteral">"CreateResizeBilinearUint8"</span>)</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span> {</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  RefCreateResizeBilinearTest<RefResizeWorkload, armnn::DataType::QAsymmU8>(DataLayout::NCHW);</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> </div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span> TEST_CASE(<span class="stringliteral">"CreateResizeBilinearQuantisedAsymm16"</span>)</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>  RefCreateResizeBilinearTest<RefResizeWorkload, armnn::DataType::QSymmS16>(DataLayout::NCHW);</div><div class="line"><a name="l00879"></a><span class="lineno"> 879</span> }</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span> </div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span> TEST_CASE(<span class="stringliteral">"CreateResizeBilinearFloat32Nhwc"</span>)</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span> {</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  RefCreateResizeBilinearTest<RefResizeWorkload, armnn::DataType::Float32>(DataLayout::NHWC);</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span> }</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span> </div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span> <span class="keyword">template</span> <<span class="keyword">typename</span> BatchToSpaceNdWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateBatchToSpaceNdTest()</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>  Graph graph;</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  RefWorkloadFactory factory;</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span> </div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  <span class="keyword">auto</span> workload = CreateBatchToSpaceNdWorkloadTest<BatchToSpaceNdWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span> </div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  TensorInfo({ 1, 1, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  TensorInfo({ 1, 1, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span> }</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span> </div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span> TEST_CASE(<span class="stringliteral">"CreateBatchToSpaceNdFloat32"</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>  RefCreateBatchToSpaceNdTest<RefBatchToSpaceNdWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span> }</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span> </div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span> TEST_CASE(<span class="stringliteral">"CreateBatchToSpaceNdFloat16"</span>)</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span> {</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  RefCreateBatchToSpaceNdTest<RefBatchToSpaceNdWorkload, armnn::DataType::Float16>();</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span> }</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span> </div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span> TEST_CASE(<span class="stringliteral">"CreateBatchToSpaceNdUint8"</span>)</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span> {</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  RefCreateBatchToSpaceNdTest<RefBatchToSpaceNdWorkload, armnn::DataType::QAsymmU8>();</div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span> }</div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span> </div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span> TEST_CASE(<span class="stringliteral">"CreateBatchToSpaceNdQSymm16"</span>)</div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span> {</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  RefCreateBatchToSpaceNdTest<RefBatchToSpaceNdWorkload, armnn::DataType::QSymmS16>();</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span> }</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span> </div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span> <span class="keyword">template</span> <<span class="keyword">typename</span> L2NormalizationWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateL2NormalizationTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span> {</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  Graph graph;</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  <span class="keyword">auto</span> workload =</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  CreateL2NormalizationWorkloadTest<L2NormalizationWorkloadType, DataType>(factory, graph, dataLayout);</div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span> </div><div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  TensorShape inputShape;</div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  TensorShape outputShape;</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span> </div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  {</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  inputShape = { 5, 50, 67, 20 };</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  outputShape = { 5, 50, 67, 20 };</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  inputShape = { 5, 20, 50, 67 };</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  outputShape = { 5, 20, 50, 67 };</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  }</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span> </div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateL2NormalizationWorkloadTest).</span></div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  CheckInputOutput(std::move(workload), TensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>), TensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span> }</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span> </div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span> TEST_CASE(<span class="stringliteral">"CreateL2NormalizationFloat32"</span>)</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span> {</div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::Float32>(DataLayout::NCHW);</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span> }</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span> </div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span> TEST_CASE(<span class="stringliteral">"CreateL2NormalizationFloat32Nhwc"</span>)</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span> {</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::Float32>(DataLayout::NHWC);</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"> 957</span> TEST_CASE(<span class="stringliteral">"CreateL2NormalizationInt16"</span>)</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span> {</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::QSymmS16>(DataLayout::NCHW);</div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span> }</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span> </div><div class="line"><a name="l00962"></a><span class="lineno"> 962</span> TEST_CASE(<span class="stringliteral">"CreateL2NormalizationInt16Nhwc"</span>)</div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span> {</div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::QSymmS16>(DataLayout::NHWC);</div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span> }</div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span> </div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span> TEST_CASE(<span class="stringliteral">"CreateL2NormalizationUint8"</span>)</div><div class="line"><a name="l00968"></a><span class="lineno"> 968</span> {</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::QAsymmU8>(DataLayout::NCHW);</div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span> }</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span> </div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span> TEST_CASE(<span class="stringliteral">"CreateL2NormalizationUint8Nhwc"</span>)</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span> {</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  RefCreateL2NormalizationTest<RefL2NormalizationWorkload, armnn::DataType::QAsymmU8>(DataLayout::NHWC);</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span> }</div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span> </div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span> <span class="keyword">template</span> <<span class="keyword">typename</span> ReshapeWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateReshapeWorkloadTest()</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span> {</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  Graph graph;</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  <span class="keyword">auto</span> workload = CreateReshapeWorkloadTest<ReshapeWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span> </div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest).</span></div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  CheckInputOutput(</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  std::move(workload),</div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  TensorInfo({ 4, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  TensorInfo({ 1, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span> }</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span> </div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span> TEST_CASE(<span class="stringliteral">"CreateReshapeWorkloadFloat32"</span>)</div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span> {</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span>  RefCreateReshapeWorkloadTest<RefReshapeWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span> }</div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span> </div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span> TEST_CASE(<span class="stringliteral">"CreateReshapeWorkloadQuantisedAsymm8"</span>)</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span> {</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  RefCreateReshapeWorkloadTest<RefReshapeWorkload, armnn::DataType::QAsymmU8>();</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"> 1001</span> TEST_CASE(<span class="stringliteral">"CreateReshapeWorkloadQuantisedSymm16"</span>)</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span> {</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>  RefCreateReshapeWorkloadTest<RefReshapeWorkload, armnn::DataType::QSymmS16>();</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span> }</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span> </div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span> <span class="keyword">template</span> <<span class="keyword">typename</span> ConcatWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateConcatWorkloadTest(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& outputShape,</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> concatAxis)</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span> {</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>  Graph graph;</div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  <span class="keyword">auto</span> workload = CreateConcatWorkloadTest<ConcatWorkloadType, DataType>(factory, graph, outputShape, concatAxis);</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span> </div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  CheckInputsOutput(std::move(workload),</div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  TensorInfo({ 2, 3, 2, 5 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  TensorInfo({ 2, 3, 2, 5 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  TensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</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> </div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span> TEST_CASE(<span class="stringliteral">"CreateConcatDim0Float32Workload"</span>)</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>  RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::Float32>({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l01023"></a><span class="lineno"> 1023</span> }</div><div class="line"><a name="l01024"></a><span class="lineno"> 1024</span> </div><div class="line"><a name="l01025"></a><span class="lineno"> 1025</span> TEST_CASE(<span class="stringliteral">"CreateConcatDim0Float16Workload"</span>)</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span> {</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::Float16>({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l01028"></a><span class="lineno"> 1028</span> }</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> TEST_CASE(<span class="stringliteral">"CreateConcatDim0Uint8Workload"</span>)</div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span> {</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::QAsymmU8>({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l01033"></a><span class="lineno"> 1033</span> }</div><div class="line"><a name="l01034"></a><span class="lineno"> 1034</span> </div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span> TEST_CASE(<span class="stringliteral">"CreateConcatDim0Uint16Workload"</span>)</div><div class="line"><a name="l01036"></a><span class="lineno"> 1036</span> {</div><div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>  RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::QSymmS16>({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span> }</div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span> </div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span> TEST_CASE(<span class="stringliteral">"CreateConcatDim1Float32Workload"</span>)</div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span> {</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::Float32>({ 2, 6, 2, 5 }, 1);</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"> 1045</span> TEST_CASE(<span class="stringliteral">"CreateConcatDim1Uint8Workload"</span>)</div><div class="line"><a name="l01046"></a><span class="lineno"> 1046</span> {</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::QAsymmU8>({ 2, 6, 2, 5 }, 1);</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span> }</div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span> </div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span> TEST_CASE(<span class="stringliteral">"CreateConcatDim2Float32Workload"</span>)</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>  RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::Float32>({ 2, 3, 4, 5 }, 2);</div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span> }</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> TEST_CASE(<span class="stringliteral">"CreateConcatDim2Uint8Workload"</span>)</div><div class="line"><a name="l01056"></a><span class="lineno"> 1056</span> {</div><div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::QAsymmU8>({ 2, 3, 4, 5 }, 2);</div><div class="line"><a name="l01058"></a><span class="lineno"> 1058</span> }</div><div class="line"><a name="l01059"></a><span class="lineno"> 1059</span> </div><div class="line"><a name="l01060"></a><span class="lineno"> 1060</span> TEST_CASE(<span class="stringliteral">"CreateConcatDim3Float32Workload"</span>)</div><div class="line"><a name="l01061"></a><span class="lineno"> 1061</span> {</div><div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>  RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::Float32>({ 2, 3, 2, 10 }, 3);</div><div class="line"><a name="l01063"></a><span class="lineno"> 1063</span> }</div><div class="line"><a name="l01064"></a><span class="lineno"> 1064</span> </div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span> TEST_CASE(<span class="stringliteral">"CreateConcatDim3Uint8Workload"</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"> 1067</span>  RefCreateConcatWorkloadTest<RefConcatWorkload, armnn::DataType::QAsymmU8>({ 2, 3, 2, 10 }, 3);</div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span> }</div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</span> </div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span> <span class="keyword">template</span> <<span class="keyword">typename</span> ConstantWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateConstantWorkloadTest(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& outputShape)</div><div class="line"><a name="l01072"></a><span class="lineno"> 1072</span> {</div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>  <span class="keyword">auto</span> workload = CreateConstantWorkloadTest<ConstantWorkloadType, DataType>(factory, graph, outputShape);</div><div class="line"><a name="l01076"></a><span class="lineno"> 1076</span> </div><div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>  <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>  <span class="keyword">auto</span> queueDescriptor = workload->GetData();</div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>  CHECK((outputHandle->GetTensorInfo() == TensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l01081"></a><span class="lineno"> 1081</span> }</div><div class="line"><a name="l01082"></a><span class="lineno"> 1082</span> </div><div class="line"><a name="l01083"></a><span class="lineno"> 1083</span> TEST_CASE(<span class="stringliteral">"CreateConstantUint8Workload"</span>)</div><div class="line"><a name="l01084"></a><span class="lineno"> 1084</span> {</div><div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>  RefCreateConstantWorkloadTest<RefConstantWorkload, armnn::DataType::QAsymmU8>({ 2, 3, 2, 10 });</div><div class="line"><a name="l01086"></a><span class="lineno"> 1086</span> }</div><div class="line"><a name="l01087"></a><span class="lineno"> 1087</span> </div><div class="line"><a name="l01088"></a><span class="lineno"> 1088</span> TEST_CASE(<span class="stringliteral">"CreateConstantInt16Workload"</span>)</div><div class="line"><a name="l01089"></a><span class="lineno"> 1089</span> {</div><div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>  RefCreateConstantWorkloadTest<RefConstantWorkload, armnn::DataType::QSymmS16>({ 2, 3, 2, 10 });</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span> }</div><div class="line"><a name="l01092"></a><span class="lineno"> 1092</span> </div><div class="line"><a name="l01093"></a><span class="lineno"> 1093</span> TEST_CASE(<span class="stringliteral">"CreateConstantFloat32Workload"</span>)</div><div class="line"><a name="l01094"></a><span class="lineno"> 1094</span> {</div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  RefCreateConstantWorkloadTest<RefConstantWorkload, armnn::DataType::Float32>({ 2, 3, 2, 10 });</div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span> }</div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span> </div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span> TEST_CASE(<span class="stringliteral">"CreateConstantSigned32Workload"</span>)</div><div class="line"><a name="l01099"></a><span class="lineno"> 1099</span> {</div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  RefCreateConstantWorkloadTest<RefConstantWorkload, armnn::DataType::Signed32>({ 2, 3, 2, 10 });</div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</span> }</div><div class="line"><a name="l01102"></a><span class="lineno"> 1102</span> </div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreatePreluWorkloadTest(<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="l01104"></a><span class="lineno"> 1104</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& alphaShape,</div><div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& outputShape,</div><div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> dataType)</div><div class="line"><a name="l01107"></a><span class="lineno"> 1107</span> {</div><div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>  RefWorkloadFactory factory;</div><div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>  <span class="keyword">auto</span> workload = CreatePreluWorkloadTest<RefPreluWorkload>(factory,</div><div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  graph,</div><div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  inputShape,</div><div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>  alphaShape,</div><div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  outputShape,</div><div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>  dataType);</div><div class="line"><a name="l01116"></a><span class="lineno"> 1116</span> </div><div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>  <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>  <span class="keyword">auto</span> queueDescriptor = workload->GetData();</div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  CHECK((outputHandle->GetTensorInfo() == TensorInfo(outputShape, dataType)));</div><div class="line"><a name="l01121"></a><span class="lineno"> 1121</span> }</div><div class="line"><a name="l01122"></a><span class="lineno"> 1122</span> </div><div class="line"><a name="l01123"></a><span class="lineno"> 1123</span> TEST_CASE(<span class="stringliteral">"CreatePreluFloat32Workload"</span>)</div><div class="line"><a name="l01124"></a><span class="lineno"> 1124</span> {</div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span> }</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span> </div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span> TEST_CASE(<span class="stringliteral">"CreatePreluFloat16Workload"</span>)</div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span> {</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>  RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span> }</div><div class="line"><a name="l01132"></a><span class="lineno"> 1132</span> </div><div class="line"><a name="l01133"></a><span class="lineno"> 1133</span> TEST_CASE(<span class="stringliteral">"CreatePreluUint8Workload"</span>)</div><div class="line"><a name="l01134"></a><span class="lineno"> 1134</span> {</div><div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>  RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>);</div><div class="line"><a name="l01136"></a><span class="lineno"> 1136</span> }</div><div class="line"><a name="l01137"></a><span class="lineno"> 1137</span> </div><div class="line"><a name="l01138"></a><span class="lineno"> 1138</span> TEST_CASE(<span class="stringliteral">"CreatePreluInt16Workload"</span>)</div><div class="line"><a name="l01139"></a><span class="lineno"> 1139</span> {</div><div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>  RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>);</div><div class="line"><a name="l01141"></a><span class="lineno"> 1141</span> }</div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span> </div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span> TEST_CASE(<span class="stringliteral">"CreatePreluFloat32NoBroadcastWorkload"</span>)</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span> {</div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>  CHECK_THROWS_AS(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 },</div><div class="line"><a name="l01146"></a><span class="lineno"> 1146</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>),</div><div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>  <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>);</div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span> }</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span> </div><div class="line"><a name="l01150"></a><span class="lineno"> 1150</span> TEST_CASE(<span class="stringliteral">"CreatePreluFloat16NoBroadcastWorkload"</span>)</div><div class="line"><a name="l01151"></a><span class="lineno"> 1151</span> {</div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>  CHECK_THROWS_AS(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 },</div><div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>),</div><div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>  <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>);</div><div class="line"><a name="l01155"></a><span class="lineno"> 1155</span> }</div><div class="line"><a name="l01156"></a><span class="lineno"> 1156</span> </div><div class="line"><a name="l01157"></a><span class="lineno"> 1157</span> TEST_CASE(<span class="stringliteral">"CreatePreluUint8NoBroadcastWorkload"</span>)</div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span> {</div><div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>  CHECK_THROWS_AS(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 },</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>),</div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>);</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span> }</div><div class="line"><a name="l01163"></a><span class="lineno"> 1163</span> </div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span> TEST_CASE(<span class="stringliteral">"CreatePreluInt16NoBroadcastWorkload"</span>)</div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span> {</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  CHECK_THROWS_AS(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 },</div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>),</div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>  <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>);</div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span> }</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span> </div><div class="line"><a name="l01171"></a><span class="lineno"> 1171</span> <span class="keyword">template</span> <<span class="keyword">typename</span> SpaceToDepthWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l01172"></a><span class="lineno"> 1172</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateSpaceToDepthWorkloadTest()</div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span> {</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  Graph graph;</div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>  RefWorkloadFactory factory;</div><div class="line"><a name="l01176"></a><span class="lineno"> 1176</span> </div><div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>  <span class="keyword">auto</span> workload = CreateSpaceToDepthWorkloadTest<SpaceToDepthWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l01178"></a><span class="lineno"> 1178</span> </div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>  CheckInputOutput(std::move(workload),</div><div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  TensorInfo({ 1, 2, 2, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>  TensorInfo({ 1, 1, 1, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l01182"></a><span class="lineno"> 1182</span> }</div><div class="line"><a name="l01183"></a><span class="lineno"> 1183</span> </div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span> TEST_CASE(<span class="stringliteral">"CreateSpaceToDepthWorkloadFloat32"</span>)</div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span> {</div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  RefCreateSpaceToDepthWorkloadTest<RefSpaceToDepthWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l01187"></a><span class="lineno"> 1187</span> }</div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span> </div><div class="line"><a name="l01189"></a><span class="lineno"> 1189</span> TEST_CASE(<span class="stringliteral">"CreateSpaceToDepthWorkloadFloat16"</span>)</div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span> {</div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>  RefCreateSpaceToDepthWorkloadTest<RefSpaceToDepthWorkload, armnn::DataType::Float16>();</div><div class="line"><a name="l01192"></a><span class="lineno"> 1192</span> }</div><div class="line"><a name="l01193"></a><span class="lineno"> 1193</span> </div><div class="line"><a name="l01194"></a><span class="lineno"> 1194</span> TEST_CASE(<span class="stringliteral">"CreateSpaceToDepthWorkloadQASymm8"</span>)</div><div class="line"><a name="l01195"></a><span class="lineno"> 1195</span> {</div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>  RefCreateSpaceToDepthWorkloadTest<RefSpaceToDepthWorkload, armnn::DataType::QAsymmU8>();</div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span> }</div><div class="line"><a name="l01198"></a><span class="lineno"> 1198</span> </div><div class="line"><a name="l01199"></a><span class="lineno"> 1199</span> TEST_CASE(<span class="stringliteral">"CreateSpaceToDepthWorkloadQSymm16"</span>)</div><div class="line"><a name="l01200"></a><span class="lineno"> 1200</span> {</div><div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>  RefCreateSpaceToDepthWorkloadTest<RefSpaceToDepthWorkload, armnn::DataType::QSymmS16>();</div><div class="line"><a name="l01202"></a><span class="lineno"> 1202</span> }</div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span> </div><div class="line"><a name="l01204"></a><span class="lineno"> 1204</span> <span class="keyword">template</span> <armnn::DataType DataType></div><div class="line"><a name="l01205"></a><span class="lineno"> 1205</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateStackWorkloadTest(<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="l01206"></a><span class="lineno"> 1206</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& outputShape,</div><div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axis,</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs)</div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</span> {</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>  RefWorkloadFactory factory;</div><div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>  <span class="keyword">auto</span> workload = CreateStackWorkloadTest<RefStackWorkload, DataType>(factory,</div><div class="line"><a name="l01213"></a><span class="lineno"> 1213</span>  graph,</div><div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  inputShape,</div><div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>  outputShape,</div><div class="line"><a name="l01216"></a><span class="lineno"> 1216</span>  axis,</div><div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>  numInputs);</div><div class="line"><a name="l01218"></a><span class="lineno"> 1218</span> </div><div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>  <span class="comment">// Check inputs and output are as expected</span></div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  StackQueueDescriptor queueDescriptor = workload->GetData();</div><div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputs; ++i)</div><div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  {</div><div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[i]);</div><div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>  CHECK((inputHandle->GetTensorInfo() == TensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>  }</div><div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>  CHECK((outputHandle->GetTensorInfo() == TensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l01228"></a><span class="lineno"> 1228</span> }</div><div class="line"><a name="l01229"></a><span class="lineno"> 1229</span> </div><div class="line"><a name="l01230"></a><span class="lineno"> 1230</span> TEST_CASE(<span class="stringliteral">"CreateStackFloat32Workload"</span>)</div><div class="line"><a name="l01231"></a><span class="lineno"> 1231</span> {</div><div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>  RefCreateStackWorkloadTest<armnn::DataType::Float32>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l01233"></a><span class="lineno"> 1233</span> }</div><div class="line"><a name="l01234"></a><span class="lineno"> 1234</span> </div><div class="line"><a name="l01235"></a><span class="lineno"> 1235</span> TEST_CASE(<span class="stringliteral">"CreateStackUint8Workload"</span>)</div><div class="line"><a name="l01236"></a><span class="lineno"> 1236</span> {</div><div class="line"><a name="l01237"></a><span class="lineno"> 1237</span>  RefCreateStackWorkloadTest<armnn::DataType::QAsymmU8>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l01238"></a><span class="lineno"> 1238</span> }</div><div class="line"><a name="l01239"></a><span class="lineno"> 1239</span> </div><div class="line"><a name="l01240"></a><span class="lineno"> 1240</span> TEST_CASE(<span class="stringliteral">"CreateStackUint16Workload"</span>)</div><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span> {</div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>  RefCreateStackWorkloadTest<armnn::DataType::QSymmS16>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l01243"></a><span class="lineno"> 1243</span> }</div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</span> </div><div class="line"><a name="l01245"></a><span class="lineno"> 1245</span> <span class="keyword">template</span> <<span class="keyword">typename</span> QLstmWorkloadType></div><div class="line"><a name="l01246"></a><span class="lineno"> 1246</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateQLstmWorkloadTest()</div><div class="line"><a name="l01247"></a><span class="lineno"> 1247</span> {</div><div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>  Graph graph;</div><div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>  RefWorkloadFactory factory;</div><div class="line"><a name="l01250"></a><span class="lineno"> 1250</span> </div><div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>  <span class="keyword">auto</span> workload = CreateQLstmWorkloadTest<QLstmWorkloadType>(factory, graph);</div><div class="line"><a name="l01252"></a><span class="lineno"> 1252</span> </div><div class="line"><a name="l01253"></a><span class="lineno"> 1253</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({2 , 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.0078125f, 0);</div><div class="line"><a name="l01254"></a><span class="lineno"> 1254</span> </div><div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> cellStateInfo({2 , 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>, 3.05176e-05f, 0);</div><div class="line"><a name="l01256"></a><span class="lineno"> 1256</span> </div><div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({2 , 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.007f, 0);</div><div class="line"><a name="l01258"></a><span class="lineno"> 1258</span> </div><div class="line"><a name="l01259"></a><span class="lineno"> 1259</span>  QLstmQueueDescriptor queueDescriptor = workload->GetData();</div><div class="line"><a name="l01260"></a><span class="lineno"> 1260</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>  <span class="keyword">auto</span> cellStateOutHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[1]);</div><div class="line"><a name="l01262"></a><span class="lineno"> 1262</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[2]);</div><div class="line"><a name="l01263"></a><span class="lineno"> 1263</span> </div><div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>  CHECK((inputHandle->GetTensorInfo() == inputInfo));</div><div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>  CHECK((cellStateOutHandle->GetTensorInfo() == cellStateInfo));</div><div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>  CHECK((outputHandle->GetTensorInfo() == outputInfo));</div><div class="line"><a name="l01267"></a><span class="lineno"> 1267</span> }</div><div class="line"><a name="l01268"></a><span class="lineno"> 1268</span> </div><div class="line"><a name="l01269"></a><span class="lineno"> 1269</span> TEST_CASE(<span class="stringliteral">"CreateQLstmWorkload"</span>)</div><div class="line"><a name="l01270"></a><span class="lineno"> 1270</span> {</div><div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>  RefCreateQLstmWorkloadTest<RefQLstmWorkload>();</div><div class="line"><a name="l01272"></a><span class="lineno"> 1272</span> }</div><div class="line"><a name="l01273"></a><span class="lineno"> 1273</span> </div><div class="line"><a name="l01274"></a><span class="lineno"> 1274</span> <span class="keyword">template</span> <armnn::DataType DataType></div><div class="line"><a name="l01275"></a><span class="lineno"> 1275</span> <span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateActivationWorkloadReplaceFunctionsTest()</div><div class="line"><a name="l01276"></a><span class="lineno"> 1276</span> {</div><div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>  Graph graph;</div><div class="line"><a name="l01278"></a><span class="lineno"> 1278</span>  RefWorkloadFactory factory = GetFactory();</div><div class="line"><a name="l01279"></a><span class="lineno"> 1279</span>  <span class="comment">// input and output are created as armnn::TensorInfo tensorInfo({1, 1}, DataType)</span></div><div class="line"><a name="l01280"></a><span class="lineno"> 1280</span>  <span class="keyword">auto</span> workloadPtr = CreateActivationWorkloadTest<RefActivationWorkload, DataType>(factory, graph);</div><div class="line"><a name="l01281"></a><span class="lineno"> 1281</span> </div><div class="line"><a name="l01282"></a><span class="lineno"> 1282</span>  <span class="comment">// new input and output tensor handlers are created and then replace in the workload</span></div><div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>  shared_ptr<RefMemoryManager> memoryManager = make_shared<RefMemoryManager>();</div><div class="line"><a name="l01284"></a><span class="lineno"> 1284</span>  <span class="keyword">const</span> RefTensorHandleFactory tensorHandleFactory(memoryManager);</div><div class="line"><a name="l01285"></a><span class="lineno"> 1285</span>  TensorInfo inputInfo({2 , 2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l01286"></a><span class="lineno"> 1286</span>  TensorInfo outputInfo({2 , 2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l01287"></a><span class="lineno"> 1287</span>  unique_ptr<ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputInfo);</div><div class="line"><a name="l01288"></a><span class="lineno"> 1288</span>  unique_ptr<ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputInfo);</div><div class="line"><a name="l01289"></a><span class="lineno"> 1289</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> slot = 0;</div><div class="line"><a name="l01290"></a><span class="lineno"> 1290</span>  workloadPtr->ReplaceInputTensorHandle(inputHandle.get(), slot);</div><div class="line"><a name="l01291"></a><span class="lineno"> 1291</span>  workloadPtr->ReplaceOutputTensorHandle(outputHandle.get(), slot);</div><div class="line"><a name="l01292"></a><span class="lineno"> 1292</span> </div><div class="line"><a name="l01293"></a><span class="lineno"> 1293</span>  <span class="comment">// Check if the tensor handlers inside the workload are the same as ones we replace with</span></div><div class="line"><a name="l01294"></a><span class="lineno"> 1294</span>  <span class="keyword">auto</span> queueDescriptor = workloadPtr->GetData();</div><div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>  <span class="keyword">auto</span> inputHandleTest = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l01296"></a><span class="lineno"> 1296</span>  <span class="keyword">auto</span> outputHandleTest = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>  CHECK((inputHandleTest->GetTensorInfo() == inputInfo));</div><div class="line"><a name="l01298"></a><span class="lineno"> 1298</span>  CHECK((outputHandleTest->GetTensorInfo() == outputInfo));</div><div class="line"><a name="l01299"></a><span class="lineno"> 1299</span>  CHECK(inputHandle.get() == inputHandleTest);</div><div class="line"><a name="l01300"></a><span class="lineno"> 1300</span>  CHECK(outputHandle.get() == outputHandleTest);</div><div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>  inputHandle->Allocate();</div><div class="line"><a name="l01302"></a><span class="lineno"> 1302</span>  CHECK(inputHandle->Map() == inputHandleTest->Map());</div><div class="line"><a name="l01303"></a><span class="lineno"> 1303</span>  outputHandle->Allocate();</div><div class="line"><a name="l01304"></a><span class="lineno"> 1304</span>  CHECK(outputHandle->Map() == outputHandleTest->Map());</div><div class="line"><a name="l01305"></a><span class="lineno"> 1305</span> }</div><div class="line"><a name="l01306"></a><span class="lineno"> 1306</span> </div><div class="line"><a name="l01307"></a><span class="lineno"> 1307</span> TEST_CASE(<span class="stringliteral">"ReplaceFunctionsfromFloat32toFloat16ActivationWorkload"</span>)</div><div class="line"><a name="l01308"></a><span class="lineno"> 1308</span> {</div><div class="line"><a name="l01309"></a><span class="lineno"> 1309</span>  RefCreateActivationWorkloadReplaceFunctionsTest<armnn::DataType::Float32>();</div><div class="line"><a name="l01310"></a><span class="lineno"> 1310</span> }</div><div class="line"><a name="l01311"></a><span class="lineno"> 1311</span> </div><div class="line"><a name="l01312"></a><span class="lineno"> 1312</span> TEST_CASE(<span class="stringliteral">"ReplaceFunctionsfromUint8toFloat16ActivationWorkload"</span>)</div><div class="line"><a name="l01313"></a><span class="lineno"> 1313</span> {</div><div class="line"><a name="l01314"></a><span class="lineno"> 1314</span>  RefCreateActivationWorkloadReplaceFunctionsTest<armnn::DataType::QAsymmU8>();</div><div class="line"><a name="l01315"></a><span class="lineno"> 1315</span> }</div><div class="line"><a name="l01316"></a><span class="lineno"> 1316</span> </div><div class="line"><a name="l01317"></a><span class="lineno"> 1317</span> }</div><div class="ttc" id="_ref_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_ref_workload_factory_8hpp.xhtml">RefWorkloadFactory.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#l00062">Types.hpp:62</a></div></div> +<div class="ttc" id="classarmnn_1_1_ref_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_ref_tensor_handle_8hpp_source.xhtml#l00015">RefTensorHandle.hpp:15</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="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</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="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</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="_polymorphic_downcast_8hpp_xhtml"><div class="ttname"><a href="_polymorphic_downcast_8hpp.xhtml">PolymorphicDowncast.hpp</a></div></div> +<div class="ttc" id="_ref_workloads_8hpp_xhtml"><div class="ttname"><a href="_ref_workloads_8hpp.xhtml">RefWorkloads.hpp</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#l00048">Types.hpp:48</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="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div> +<div class="ttc" id="classarmnn_1_1_ref_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_ref_workload_factory.xhtml">armnn::RefWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_factory_8hpp_source.xhtml#l00030">RefWorkloadFactory.hpp:30</a></div></div> +<div class="ttc" id="_ref_create_workload_tests_8cpp_xhtml_aeae58109674c5194001eb936c8e015b7"><div class="ttname"><a href="_ref_create_workload_tests_8cpp.xhtml#aeae58109674c5194001eb936c8e015b7">TEST_SUITE</a></div><div class="ttdeci">TEST_SUITE("CreateWorkloadRef")</div><div class="ttdef"><b>Definition:</b> <a href="_ref_create_workload_tests_8cpp_source.xhtml#l00052">RefCreateWorkloadTests.cpp:52</a></div></div> +<div class="ttc" id="classarmnn_1_1_invalid_argument_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00080">Exceptions.hpp:80</a></div></div> +<div class="ttc" id="_ref_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_ref_tensor_handle_8hpp.xhtml">RefTensorHandle.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00030">Graph.hpp:30</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00489">Tensor.cpp:489</a></div></div> +<div class="ttc" id="_ref_tensor_handle_factory_8hpp_xhtml"><div class="ttname"><a href="_ref_tensor_handle_factory_8hpp.xhtml">RefTensorHandleFactory.hpp</a></div></div> +<div class="ttc" 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