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diff --git a/20.02/_cl_create_workload_tests_8cpp_source.xhtml b/20.02/_cl_create_workload_tests_8cpp_source.xhtml new file mode 100644 index 0000000000..6d4b25f549 --- /dev/null +++ b/20.02/_cl_create_workload_tests_8cpp_source.xhtml @@ -0,0 +1,182 @@ +<!-- 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/cl/test/ClCreateWorkloadTests.cpp Source File</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">20.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_cl_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">ClCreateWorkloadTests.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_cl_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. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_cl_context_control_fixture_8hpp.xhtml">ClContextControlFixture.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_cl_workload_factory_helper_8hpp.xhtml">ClWorkloadFactoryHelper.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_mem_copy_workload_8hpp.xhtml">backendsCommon/MemCopyWorkload.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_create_workload_cl_neon_8hpp.xhtml">aclCommon/test/CreateWorkloadClNeon.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_arm_compute_tensor_utils_8hpp.xhtml">aclCommon/ArmComputeTensorUtils.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_cl_tensor_handle_8hpp.xhtml">cl/ClTensorHandle.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_cl_workload_factory_8hpp.xhtml">cl/ClWorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_cl_workloads_8hpp.xhtml">cl/workloads/ClWorkloads.hpp</a>></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <<a class="code" href="_cl_workload_utils_8hpp.xhtml">cl/workloads/ClWorkloadUtils.hpp</a>></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00019"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e"> 19</a></span> boost::test_tools::predicate_result <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(<a class="code" href="classarmnn_1_1_i_cl_tensor_handle.xhtml">IClTensorHandle</a>* tensorHandle,</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  std::initializer_list<unsigned int> expectedDimensions)</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="keywordflow">return</span> CompareTensorHandleShape<IClTensorHandle>(tensorHandle, expectedDimensions);</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> }</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> BOOST_FIXTURE_TEST_SUITE(CreateWorkloadCl, <a class="code" href="struct_cl_context_control_fixture_base.xhtml">ClContextControlFixture</a>)</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="keyword">template</span> <armnn::DataType DataType></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreateActivationWorkloadTest()</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> {</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keyword">auto</span> workload = CreateActivationWorkloadTest<ClActivationWorkload, DataType>(factory, graph);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateActivationWorkloadTest).</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <a class="code" href="structarmnn_1_1_activation_queue_descriptor.xhtml">ActivationQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, {1, 1}));</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, {1, 1}));</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> }</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722"> 45</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateActivationFloatWorkload)</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  ClCreateActivationWorkloadTest<armnn::DataType::Float32>();</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"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ac0821cd85c88deea1e8c829b66b71d13"> 50</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateActivationFloat16Workload)</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> {</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  ClCreateActivationWorkloadTest<armnn::DataType::Float16>();</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> </div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="keyword">template</span> <<span class="keyword">typename</span> WorkloadType,</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keyword">typename</span> DescriptorType,</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">typename</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>,</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</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="l00059"></a><span class="lineno"> 59</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreateElementwiseWorkloadTest()</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">auto</span> workload = CreateElementwiseWorkloadTest<WorkloadType, DescriptorType, LayerType, DataType>(factory, graph);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateElementwiseWorkloadTest).</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  DescriptorType queueDescriptor = workload->GetData();</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">auto</span> inputHandle1 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keyword">auto</span> inputHandle2 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[1]);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle1, {2, 3}));</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle2, {2, 3}));</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, {2, 3}));</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"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a91343c247a116b44c01af985c72b1e4d"> 77</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateAdditionFloatWorkload)</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> {</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  ClCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_cl_addition_workload.xhtml">ClAdditionWorkload</a>,</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">AdditionQueueDescriptor</a>,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>,</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>();</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> }</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a3b08c46c01fef78120206b8fc825f9be"> 85</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateAdditionFloat16Workload)</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> {</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  ClCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_cl_addition_workload.xhtml">ClAdditionWorkload</a>,</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">AdditionQueueDescriptor</a>,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>,</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>>();</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> }</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div><div class="line"><a name="l00093"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a18112ff3922073508feb3c25602eace2"> 93</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSubtractionFloatWorkload)</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> {</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  ClCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_cl_subtraction_workload.xhtml">ClSubtractionWorkload</a>,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <a class="code" href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">SubtractionQueueDescriptor</a>,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <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> </div><div class="line"><a name="l00101"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a5f8370f733e76f8b7de20d2152be1bfd"> 101</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSubtractionFloat16Workload)</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> {</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  ClCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_cl_subtraction_workload.xhtml">ClSubtractionWorkload</a>,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">SubtractionQueueDescriptor</a>,</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>>();</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> }</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00109"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a82c98a04bbc6143dc77a73eda9fe0a9d"> 109</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateMultiplicationFloatWorkloadTest)</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>  ClCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_cl_multiplication_workload.xhtml">ClMultiplicationWorkload</a>,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">MultiplicationQueueDescriptor</a>,</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>();</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> }</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a2a05119050b8f68fda67b01d34cc220a"> 117</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateMultiplicationFloat16WorkloadTest)</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> {</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  ClCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_cl_multiplication_workload.xhtml">ClMultiplicationWorkload</a>,</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <a class="code" href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">MultiplicationQueueDescriptor</a>,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>>();</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> }</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </div><div class="line"><a name="l00125"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a494c3788535c8b0f026fa65bfdb07caa"> 125</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateMultiplicationUint8WorkloadTest)</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>  ClCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_cl_multiplication_workload.xhtml">ClMultiplicationWorkload</a>,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code" href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">MultiplicationQueueDescriptor</a>,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>>();</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> }</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> </div><div class="line"><a name="l00133"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a0c06371a0bca0be0ef80ed2154ff8e34"> 133</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateDivisionFloatWorkloadTest)</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> {</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  ClCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_cl_division_float_workload.xhtml">ClDivisionFloatWorkload</a>,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <a class="code" href="structarmnn_1_1_division_queue_descriptor.xhtml">DivisionQueueDescriptor</a>,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <a class="code" href="classarmnn_1_1_division_layer.xhtml">DivisionLayer</a>,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>();</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> }</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a249e970fe04687638331a2fd8fa414d7"> 141</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateDivisionFloat16WorkloadTest)</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>  ClCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_cl_division_float_workload.xhtml">ClDivisionFloatWorkload</a>,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="structarmnn_1_1_division_queue_descriptor.xhtml">DivisionQueueDescriptor</a>,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="classarmnn_1_1_division_layer.xhtml">DivisionLayer</a>,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>>();</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> }</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="keyword">template</span> <<span class="keyword">typename</span> WorkloadType, </div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keyword">typename</span> DescriptorType,</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</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="l00152"></a><span class="lineno"> 152</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreateElementwiseUnaryWorkloadTest(<a class="code" href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8">armnn::UnaryOperation</a> op)</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> {</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keyword">auto</span> workload = CreateElementwiseUnaryWorkloadTest<WorkloadType, DescriptorType, DataType>(factory, graph, op);</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> </div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  DescriptorType queueDescriptor = workload->GetData();</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> </div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, {2, 3}));</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, {2, 3}));</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> }</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a683d53553e42dcf66fe2ea86ce3d623e"> 169</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateRsqrtFloat32WorkloadTest)</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> {</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  ClCreateElementwiseUnaryWorkloadTest<ClRsqrtWorkload, RsqrtQueueDescriptor, armnn::DataType::Float32>(</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  UnaryOperation::Rsqrt);</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> <span class="keyword">template</span> <<span class="keyword">typename</span> BatchNormalizationWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreateBatchNormalizationWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> {</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreateBatchNormalizationWorkloadTest<BatchNormalizationWorkloadType, DataType></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  (factory, graph, dataLayout);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest).</span></div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">BatchNormalizationQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> </div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  {</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, { 2, 4, 4, 3 }));</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, { 2, 4, 4, 3 }));</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keywordflow">default</span>: <span class="comment">// NCHW</span></div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, { 2, 3, 4, 4 }));</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, { 2, 3, 4, 4 }));</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  }</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> }</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div><div class="line"><a name="l00202"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ae4e714990000cacf540f2f1da8220120"> 202</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloatNchwWorkload)</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> {</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  ClCreateBatchNormalizationWorkloadTest<<a class="code" href="classarmnn_1_1_cl_batch_normalization_float_workload.xhtml">ClBatchNormalizationFloatWorkload</a>,</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>(DataLayout::NCHW);</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> </div><div class="line"><a name="l00208"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#accc9f6ad24a88ccf9e8831bdf054b186"> 208</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloat16NchwWorkload)</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span> {</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  ClCreateBatchNormalizationWorkloadTest<<a class="code" href="classarmnn_1_1_cl_batch_normalization_float_workload.xhtml">ClBatchNormalizationFloatWorkload</a>,</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>>(DataLayout::NCHW);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> }</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> </div><div class="line"><a name="l00214"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a16f59a17052dcf58c1e71a70e5aac96f"> 214</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloatNhwcWorkload)</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> {</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  ClCreateBatchNormalizationWorkloadTest<<a class="code" href="classarmnn_1_1_cl_batch_normalization_float_workload.xhtml">ClBatchNormalizationFloatWorkload</a>,</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>(DataLayout::NHWC);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> }</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span> </div><div class="line"><a name="l00220"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a839bb0bcdacf08446bb91ab31e3f15c3"> 220</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationNhwcFloat16NhwcWorkload)</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>  ClCreateBatchNormalizationWorkloadTest<<a class="code" href="classarmnn_1_1_cl_batch_normalization_float_workload.xhtml">ClBatchNormalizationFloatWorkload</a>,</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>>(DataLayout::NHWC);</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> </div><div class="line"><a name="l00226"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a42cda8db468a1f3422bb56648dce81d9"> 226</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConvertFp16ToFp32Workload)</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> {</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> </div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keyword">auto</span> workload = CreateConvertFp16ToFp32WorkloadTest<ClConvertFp16ToFp32Workload>(factory, graph);</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> </div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <a class="code" href="structarmnn_1_1_convert_fp16_to_fp32_queue_descriptor.xhtml">ConvertFp16ToFp32QueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</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>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, {1, 3, 2, 3}));</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, {1, 3, 2, 3}));</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  BOOST_TEST((inputHandle->GetTensor().info()->data_type() == arm_compute::DataType::F16));</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  BOOST_TEST((outputHandle->GetTensor().info()->data_type() == arm_compute::DataType::F32));</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> }</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div><div class="line"><a name="l00244"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a343c41dca16808e3e6d78a3215f81ddc"> 244</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConvertFp32ToFp16Workload)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keyword">auto</span> workload = CreateConvertFp32ToFp16WorkloadTest<ClConvertFp32ToFp16Workload>(factory, graph);</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> </div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <a class="code" href="structarmnn_1_1_convert_fp32_to_fp16_queue_descriptor.xhtml">ConvertFp32ToFp16QueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> </div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, {1, 3, 2, 3}));</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, {1, 3, 2, 3}));</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  BOOST_TEST((inputHandle->GetTensor().info()->data_type() == arm_compute::DataType::F32));</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  BOOST_TEST((outputHandle->GetTensor().info()->data_type() == arm_compute::DataType::F16));</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> }</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> </div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> <span class="keyword">template</span> <<span class="keyword">typename</span> Convolution2dWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClConvolution2dWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> </div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keyword">auto</span> workload = CreateConvolution2dWorkloadTest<ClConvolution2dWorkload, DataType>(factory,</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  graph,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  dataLayout);</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> </div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({2, 3, 8, 16})</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  : std::initializer_list<unsigned int>({2, 8, 16, 3});</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({2, 2, 2, 10})</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  : std::initializer_list<unsigned int>({2, 2, 10, 2});</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>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest).</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">Convolution2dQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0]);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]);</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  BOOST_TEST((inputHandle->GetShape() == inputShape));</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  BOOST_TEST((outputHandle->GetShape() == outputShape));</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> }</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> </div><div class="line"><a name="l00286"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a8a2458d4f6ff9103299e72433245db5b"> 286</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFloatNchwWorkload)</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> {</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  ClConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float32>(DataLayout::NCHW);</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> }</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> </div><div class="line"><a name="l00291"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a1738342e20abb6bebf8766a796424865"> 291</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFloatNhwcWorkload)</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> {</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  ClConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float32>(DataLayout::NHWC);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> }</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> </div><div class="line"><a name="l00296"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a3d7eb8b3fb06687c2c24311ee2046326"> 296</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFloat16NchwWorkload)</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> {</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  ClConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float16>(DataLayout::NCHW);</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> }</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> </div><div class="line"><a name="l00301"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a27f53421f1c972548d1f498ae050612f"> 301</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFloat16NhwcWorkload)</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> {</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  ClConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float16>(DataLayout::NHWC);</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> }</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> </div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> <span class="keyword">template</span> <<span class="keyword">typename</span> DepthwiseConvolutionWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClDepthwiseConvolutionWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> {</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keyword">auto</span> workload = CreateDepthwiseConvolution2dWorkloadTest<DepthwiseConvolutionWorkloadType, DataType></div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  (factory, graph, dataLayout);</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>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateDepthwiseConvolution2dWorkloadTest).</span></div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">DepthwiseConvolution2dQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> </div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 2, 2, 5, 5 })</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  : std::initializer_list<unsigned int>({ 2, 5, 5, 2 });</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 2, 2, 5, 5 })</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  : std::initializer_list<unsigned int>({ 2, 5, 5, 2 });</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> </div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  BOOST_TEST((inputHandle->GetShape() == inputShape));</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  BOOST_TEST((outputHandle->GetShape() == outputShape));</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> }</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div><div class="line"><a name="l00330"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ac96201c573891d4b179bf38af48a5fe5"> 330</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateDepthwiseConvolutionFloat32NhwcWorkload)</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> {</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  ClDepthwiseConvolutionWorkloadTest<ClDepthwiseConvolutionWorkload, DataType::Float32>(DataLayout::NHWC);</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> </div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> <span class="keyword">template</span> <<span class="keyword">typename</span> Convolution2dWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClDirectConvolution2dWorkloadTest()</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> {</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> </div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keyword">auto</span> workload = CreateDirectConvolution2dWorkloadTest<ClConvolution2dWorkload, DataType>(factory, graph);</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span> </div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateDirectConvolution2dWorkloadTest).</span></div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">Convolution2dQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, {2, 3, 6, 6}));</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, {2, 2, 6, 6}));</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"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#aa8bc0651cf474eba480143e1582535df"> 352</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateDirectConvolution2dFloatWorkload)</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>  ClDirectConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> }</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> </div><div class="line"><a name="l00357"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ac390f3b99338a7f8fc89d966f9c12372"> 357</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateDirectConvolution2dFloat16Workload)</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> {</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  ClDirectConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float16>();</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span> }</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span> </div><div class="line"><a name="l00362"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a7a40f27954eff6088526f5c9f91104fe"> 362</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateDirectConvolution2dUint8Workload)</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>  ClDirectConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::QAsymmU8>();</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> </div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span> <span class="keyword">template</span> <<span class="keyword">typename</span> FullyConnectedWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreateFullyConnectedWorkloadTest()</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> </div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keyword">auto</span> workload =</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  CreateFullyConnectedWorkloadTest<FullyConnectedWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> </div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest).</span></div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <a class="code" href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml">FullyConnectedQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, {3, 1, 4, 5}));</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, {3, 7}));</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> </div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> </div><div class="line"><a name="l00386"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a6de57fe77ebce6f21c43b05f2a72f408"> 386</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateFullyConnectedFloatWorkloadTest)</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>  ClCreateFullyConnectedWorkloadTest<ClFullyConnectedWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span> }</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span> </div><div class="line"><a name="l00391"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a4fbf5f0fc078aec0653966e04c02b7c5"> 391</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateFullyConnectedFloat16WorkloadTest)</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>  ClCreateFullyConnectedWorkloadTest<ClFullyConnectedWorkload, armnn::DataType::Float16>();</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> </div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span> <span class="keyword">template</span> <<span class="keyword">typename</span> NormalizationWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClNormalizationWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span> </div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <span class="keyword">auto</span> workload = CreateNormalizationWorkloadTest<NormalizationWorkloadType, DataType>(factory, graph, dataLayout);</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> </div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateNormalizationWorkloadTest).</span></div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  <a class="code" href="structarmnn_1_1_normalization_queue_descriptor.xhtml">NormalizationQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> </div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({3, 5, 5, 1})</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  : std::initializer_list<unsigned int>({3, 1, 5, 5});</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({3, 5, 5, 1})</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  : std::initializer_list<unsigned int>({3, 1, 5, 5});</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> </div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  BOOST_TEST((inputHandle->GetShape() == inputShape));</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  BOOST_TEST((outputHandle->GetShape() == outputShape));</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> }</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> </div><div class="line"><a name="l00419"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ad20aa0961362720f87ce4900305d29e1"> 419</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateNormalizationFloat32NchwWorkload)</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>  ClNormalizationWorkloadTest<ClNormalizationFloatWorkload, armnn::DataType::Float32>(DataLayout::NCHW);</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span> }</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span> </div><div class="line"><a name="l00424"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ac38e4735e1da44f60e980124712372a8"> 424</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateNormalizationFloat16NchwWorkload)</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>  ClNormalizationWorkloadTest<ClNormalizationFloatWorkload, armnn::DataType::Float16>(DataLayout::NCHW);</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> }</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> </div><div class="line"><a name="l00429"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ae644106a34c2df59a87550f1db76ce3c"> 429</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateNormalizationFloat32NhwcWorkload)</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>  ClNormalizationWorkloadTest<ClNormalizationFloatWorkload, armnn::DataType::Float32>(DataLayout::NHWC);</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span> }</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span> </div><div class="line"><a name="l00434"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ae2a04d98596b5e0580471dfe7610b3f1"> 434</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateNormalizationFloat16NhwcWorkload)</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span> {</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  ClNormalizationWorkloadTest<ClNormalizationFloatWorkload, armnn::DataType::Float16>(DataLayout::NHWC);</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span> }</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> </div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span> <span class="keyword">template</span> <<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClPooling2dWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span> {</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span> </div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <span class="keyword">auto</span> workload = CreatePooling2dWorkloadTest<ClPooling2dWorkload, DataType>(factory, graph, dataLayout);</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span> </div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({3, 2, 5, 5})</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  : std::initializer_list<unsigned int>({3, 5, 5, 2});</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({3, 2, 2, 4})</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  : std::initializer_list<unsigned int>({3, 2, 4, 2});</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>  <span class="comment">// Check that inputs/outputs are as we expect them (see definition of CreatePooling2dWorkloadTest).</span></div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <a class="code" href="structarmnn_1_1_pooling2d_queue_descriptor.xhtml">Pooling2dQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0]);</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]);</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>  BOOST_TEST((inputHandle->GetShape() == inputShape));</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  BOOST_TEST((outputHandle->GetShape() == outputShape));</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span> }</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span> </div><div class="line"><a name="l00462"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#af32a90a1a11f2fabc7eb0508325f99e0"> 462</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dFloatNchwWorkload)</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span> {</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  ClPooling2dWorkloadTest<armnn::DataType::Float32>(DataLayout::NCHW);</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span> }</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span> </div><div class="line"><a name="l00467"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a11ff4c042447da348642135ed106597c"> 467</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dFloatNhwcWorkload)</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>  ClPooling2dWorkloadTest<armnn::DataType::Float32>(DataLayout::NHWC);</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> </div><div class="line"><a name="l00472"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a8cded3755b3d277d7f8d2d3d695855a6"> 472</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dFloat16NchwWorkload)</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>  ClPooling2dWorkloadTest<armnn::DataType::Float16>(DataLayout::NCHW);</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> </div><div class="line"><a name="l00477"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ac934609acb2906ca0f7a573462872aba"> 477</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dFloat16NhwcWorkload)</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span> {</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  ClPooling2dWorkloadTest<armnn::DataType::Float16>(DataLayout::NHWC);</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> </div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreatePreluWorkloadTest(<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="l00483"></a><span class="lineno"> 483</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="l00484"></a><span class="lineno"> 484</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="l00485"></a><span class="lineno"> 485</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> dataType)</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span> {</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreatePreluWorkloadTest<ClPreluWorkload>(factory,</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  graph,</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  inputShape,</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  alphaShape,</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  outputShape,</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  dataType);</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 CreatePreluWorkloadTest).</span></div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <a class="code" href="structarmnn_1_1_prelu_queue_descriptor.xhtml">PreluQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  <span class="keyword">auto</span> alphaHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[1]);</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span> </div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  BOOST_TEST((inputHandle->GetShape() == inputShape));</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  BOOST_TEST((alphaHandle->GetShape() == alphaShape));</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  BOOST_TEST((outputHandle->GetShape() == outputShape));</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span> }</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span> </div><div class="line"><a name="l00509"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#aa73ba7a4ea3327d87efd4618c083b333"> 509</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreatePreluFloat16Workload)</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span> {</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  ClCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, DataType::Float16);</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span> }</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span> </div><div class="line"><a name="l00514"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ac5559e752bd51c12a4bd1b3b50fa5837"> 514</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreatePreluFloatWorkload)</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span> {</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  ClCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, DataType::Float32);</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span> }</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span> </div><div class="line"><a name="l00519"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a12d17284981e1fff8f0fc76da9293e2c"> 519</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreatePreluUint8Workload)</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>  ClCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, DataType::QAsymmU8);</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</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> <span class="keyword">template</span> <<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreateReshapeWorkloadTest()</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span> {</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreateReshapeWorkloadTest<ClReshapeWorkload, DataType>(factory, graph);</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span> </div><div class="line"><a name="l00533"></a><span class="lineno"> 533</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="l00534"></a><span class="lineno"> 534</span>  <a class="code" href="structarmnn_1_1_reshape_queue_descriptor.xhtml">ReshapeQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span> </div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, {4, 1}));</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, {1, 4}));</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span> }</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span> </div><div class="line"><a name="l00542"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a5e917bb46b0281f715abb63b979ccb41"> 542</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateReshapeFloatWorkload)</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>  ClCreateReshapeWorkloadTest<armnn::DataType::Float32>();</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span> }</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span> </div><div class="line"><a name="l00547"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ac7ca80fe245601e4996a82bc5e067705"> 547</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateReshapeFloat16Workload)</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>  ClCreateReshapeWorkloadTest<armnn::DataType::Float16>();</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span> }</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span> </div><div class="line"><a name="l00552"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#aa4153a7dc499db9b5eddfb42976968db"> 552</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateReshapeUint8Workload)</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span> {</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  ClCreateReshapeWorkloadTest<armnn::DataType::QAsymmU8>();</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span> }</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span> </div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span> <span class="keyword">template</span> <<span class="keyword">typename</span> SoftmaxWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClSoftmaxWorkloadTest()</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreateSoftmaxWorkloadTest<SoftmaxWorkloadType, DataType>(factory, graph);</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>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of ClSoftmaxFloatWorkload).</span></div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <a class="code" href="structarmnn_1_1_softmax_queue_descriptor.xhtml">SoftmaxQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</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>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, {4, 1}));</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, {4, 1}));</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> </div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span> </div><div class="line"><a name="l00576"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a93649a3613e8a8fb52da1ad0cb11e062"> 576</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSoftmaxFloatWorkloadTest)</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>  ClSoftmaxWorkloadTest<ClSoftmaxFloatWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</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"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a54039376034c970df44d7f51703ec4e4"> 581</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSoftmaxFloat16WorkloadTest)</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>  ClSoftmaxWorkloadTest<ClSoftmaxFloatWorkload, armnn::DataType::Float16>();</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span> }</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span> </div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span> <span class="keyword">template</span> <<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClSplitterWorkloadTest()</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreateSplitterWorkloadTest<ClSplitterWorkload, DataType>(factory, graph);</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span> </div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="comment">// Checks that outputs are as we expect them (see definition of CreateSplitterWorkloadTest).</span></div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <a class="code" href="structarmnn_1_1_splitter_queue_descriptor.xhtml">SplitterQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, {5, 7, 7}));</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span> </div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keyword">auto</span> outputHandle1 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[1]);</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle1, {2, 7, 7}));</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span> </div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <span class="keyword">auto</span> outputHandle2 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[2]);</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle2, {2, 7, 7}));</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span> </div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keyword">auto</span> outputHandle0 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle0, {1, 7, 7}));</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span> }</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span> </div><div class="line"><a name="l00610"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a3554a4d6ef7bd581c3b8ab0e07f7bd60"> 610</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSplitterFloatWorkload)</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span> {</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  ClSplitterWorkloadTest<armnn::DataType::Float32>();</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span> }</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span> </div><div class="line"><a name="l00615"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a856e926d6587c6025a56faa2ae276c03"> 615</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSplitterFloat16Workload)</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span> {</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  ClSplitterWorkloadTest<armnn::DataType::Float16>();</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span> }</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span> </div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span> <span class="keyword">template</span> <<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClSplitterConcatTest()</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span> {</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <span class="comment">// Tests that it is possible to decide which output of the splitter layer</span></div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <span class="comment">// should be lined to which input of the concat layer.</span></div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  <span class="comment">// We test that is is possible to specify 0th output</span></div><div class="line"><a name="l00626"></a><span class="lineno"> 626</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="l00627"></a><span class="lineno"> 627</span>  <span class="comment">// of the concat.</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span> </div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <span class="keyword">auto</span> workloads =</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  CreateSplitterConcatWorkloadTest<ClSplitterWorkload, ClConcatWorkload, DataType></div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  (factory, graph);</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span> </div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <span class="keyword">auto</span> wlSplitter = std::move(workloads.first);</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  <span class="keyword">auto</span> wlConcat = std::move(workloads.second);</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span> </div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  <span class="comment">//Checks that the index of inputs/outputs matches what we declared on InputDescriptor construction.</span></div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  <a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>* sOut0 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[0]);</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  <a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>* sOut1 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[1]);</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  <a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>* mIn0 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>*<span class="keyword">></span>(wlConcat->GetData().m_Inputs[0]);</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>* mIn1 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>*<span class="keyword">></span>(wlConcat->GetData().m_Inputs[1]);</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>  BOOST_TEST(sOut0);</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  BOOST_TEST(sOut1);</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  BOOST_TEST(mIn0);</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  BOOST_TEST(mIn1);</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>  <span class="comment">//Fliped order of inputs/outputs.</span></div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  <span class="keywordtype">bool</span> validDataPointers = (sOut0 == mIn1) && (sOut1 == mIn0);</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  BOOST_TEST(validDataPointers);</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> </div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <span class="comment">//Also make sure that the inputs are subtensors of one tensor and outputs are sub tensors of another tensor.</span></div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <span class="keywordtype">bool</span> validSubTensorParents = (mIn0-><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml#acc4bae0ff435653e44b6e6eed89c08fa">GetTensor</a>().parent() == mIn1-><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml#acc4bae0ff435653e44b6e6eed89c08fa">GetTensor</a>().parent())</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  && (sOut0-><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml#acc4bae0ff435653e44b6e6eed89c08fa">GetTensor</a>().parent() == sOut1-><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml#acc4bae0ff435653e44b6e6eed89c08fa">GetTensor</a>().parent());</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span> </div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  BOOST_TEST(validSubTensorParents);</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span> }</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span> </div><div class="line"><a name="l00663"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a50aa757aa4a97a25b35284809c557609"> 663</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSplitterConcatFloatWorkload)</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span> {</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  ClSplitterConcatTest<armnn::DataType::Float32>();</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> </div><div class="line"><a name="l00668"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a54e94a9adb7a0cc1a9cf6e168fd0754a"> 668</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSplitterConcatFloat16Workload)</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span> {</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  ClSplitterConcatTest<armnn::DataType::Float16>();</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> </div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span> </div><div class="line"><a name="l00674"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ad1867af9782d8dc17efb28c13096f5cf"> 674</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSingleOutputMultipleInputs)</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span> {</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  <span class="comment">// Test 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="l00677"></a><span class="lineno"> 677</span>  <span class="comment">// We create a splitter with two outputs. That each of those outputs is used by two different activation layers.</span></div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span> </div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</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>  std::unique_ptr<ClSplitterWorkload> wlSplitter;</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  std::unique_ptr<ClActivationWorkload> wlActiv0_0;</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  std::unique_ptr<ClActivationWorkload> wlActiv0_1;</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  std::unique_ptr<ClActivationWorkload> wlActiv1_0;</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  std::unique_ptr<ClActivationWorkload> wlActiv1_1;</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span> </div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  CreateSplitterMultipleInputsOneOutputWorkloadTest<<a class="code" href="classarmnn_1_1_cl_splitter_workload.xhtml">ClSplitterWorkload</a>,</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <a class="code" href="classarmnn_1_1_cl_activation_workload.xhtml">ClActivationWorkload</a>, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>(factory, graph, wlSplitter, wlActiv0_0, wlActiv0_1,</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  wlActiv1_0, wlActiv1_1);</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>  <span class="comment">//Checks that the index of inputs/outputs matches what we declared on InputDescriptor construction.</span></div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  <a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>* sOut0 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[0]);</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>* sOut1 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[1]);</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  <a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>* activ0_0Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>*<span class="keyword">></span>(wlActiv0_0->GetData().m_Inputs[0]);</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  <a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>* activ0_1Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>*<span class="keyword">></span>(wlActiv0_1->GetData().m_Inputs[0]);</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  <a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>* activ1_0Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>*<span class="keyword">></span>(wlActiv1_0->GetData().m_Inputs[0]);</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  <a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>* activ1_1Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a>*<span class="keyword">></span>(wlActiv1_1->GetData().m_Inputs[0]);</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> </div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  BOOST_TEST(sOut0);</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  BOOST_TEST(sOut1);</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  BOOST_TEST(activ0_0Im);</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  BOOST_TEST(activ0_1Im);</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  BOOST_TEST(activ1_0Im);</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  BOOST_TEST(activ1_1Im);</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span> </div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  <span class="keywordtype">bool</span> validDataPointers = (sOut0 == activ0_0Im) && (sOut0 == activ0_1Im) &&</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  (sOut1 == activ1_0Im) && (sOut1 == activ1_1Im);</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span> </div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  BOOST_TEST(validDataPointers);</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span> }</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span> </div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span> <span class="preprocessor">#if defined(ARMNNREF_ENABLED)</span></div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span> </div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span> <span class="comment">// This test unit needs the reference backend, it's not available if the reference backend is not built</span></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> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateMemCopyWorkloadsCl)</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span> {</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</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>  CreateMemCopyWorkloads<IClTensorHandle>(factory);</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</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> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span> </div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span> <span class="keyword">template</span> <<span class="keyword">typename</span> L2NormalizationWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClL2NormalizationWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span> {</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span> </div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  <span class="keyword">auto</span> workload =</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  CreateL2NormalizationWorkloadTest<L2NormalizationWorkloadType, DataType>(factory, graph, dataLayout);</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span> </div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateNormalizationWorkloadTest).</span></div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  <a class="code" href="structarmnn_1_1_l2_normalization_queue_descriptor.xhtml">L2NormalizationQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</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>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 5, 20, 50, 67 })</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  : std::initializer_list<unsigned int>({ 5, 50, 67, 20 });</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 5, 20, 50, 67 })</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  : std::initializer_list<unsigned int>({ 5, 50, 67, 20 });</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>  BOOST_TEST((inputHandle->GetShape() == inputShape));</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  BOOST_TEST((outputHandle->GetShape() == outputShape));</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> </div><div class="line"><a name="l00753"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a8efb123460d78779f2adc478907b81f5"> 753</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationFloatNchwWorkload)</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span> {</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  ClL2NormalizationWorkloadTest<ClL2NormalizationFloatWorkload, armnn::DataType::Float32>(DataLayout::NCHW);</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span> }</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span> </div><div class="line"><a name="l00758"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a910eb90bb742d08643e1386ec07dba0a"> 758</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationFloatNhwcWorkload)</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span> {</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  ClL2NormalizationWorkloadTest<ClL2NormalizationFloatWorkload, armnn::DataType::Float32>(DataLayout::NHWC);</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span> }</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span> </div><div class="line"><a name="l00763"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a08eba80387993983d420dc5b3af258e3"> 763</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationFloat16NchwWorkload)</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>  ClL2NormalizationWorkloadTest<ClL2NormalizationFloatWorkload, armnn::DataType::Float16>(DataLayout::NCHW);</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"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ac983b5968432e4c6fa456d565f382808"> 768</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationFloat16NhwcWorkload)</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>  ClL2NormalizationWorkloadTest<ClL2NormalizationFloatWorkload, armnn::DataType::Float16>(DataLayout::NHWC);</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> <span class="keyword">template</span> <<span class="keyword">typename</span> LstmWorkloadType></div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreateLstmWorkloadTest()</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span> {</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreateLstmWorkloadTest<LstmWorkloadType>(factory, graph);</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>  <a class="code" href="structarmnn_1_1_lstm_queue_descriptor.xhtml">LstmQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[1]);</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, { 2, 2 }));</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, { 2, 4 }));</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</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"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a15cb5d6986ed78434fa442039242b3fe"> 789</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateLSTMWorkloadFloatWorkload)</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span> {</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  ClCreateLstmWorkloadTest<ClLstmFloatWorkload>();</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span> }</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span> </div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span> <span class="keyword">template</span> <<span class="keyword">typename</span> ResizeWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClResizeWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span> </div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  <span class="keyword">auto</span> workload = CreateResizeBilinearWorkloadTest<ResizeWorkloadType, DataType>(factory, graph, dataLayout);</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span> </div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <span class="keyword">auto</span> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span> </div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</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>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  {</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, { 2, 4, 4, 3 }));</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, { 2, 2, 2, 3 }));</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, { 2, 3, 4, 4 }));</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, { 2, 3, 2, 2 }));</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  }</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span> }</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span> </div><div class="line"><a name="l00821"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#acecd2490c8eb6763c8500e3ae925c190"> 821</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateResizeFloat32NchwWorkload)</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>  ClResizeWorkloadTest<ClResizeWorkload, armnn::DataType::Float32>(DataLayout::NCHW);</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span> }</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span> </div><div class="line"><a name="l00826"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a2b3d75b4380f3ebdf3a8f02b00e4e929"> 826</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateResizeFloat16NchwWorkload)</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span> {</div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  ClResizeWorkloadTest<ClResizeWorkload, armnn::DataType::Float16>(DataLayout::NCHW);</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span> }</div><div class="line"><a name="l00830"></a><span class="lineno"> 830</span> </div><div class="line"><a name="l00831"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ac932bc28ac59c177e36c62e4364735a0"> 831</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateResizeUint8NchwWorkload)</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>  ClResizeWorkloadTest<ClResizeWorkload, armnn::DataType::QAsymmU8>(DataLayout::NCHW);</div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span> }</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span> </div><div class="line"><a name="l00836"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a6699397e086ed473ba164574ffbcd2e4"> 836</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateResizeFloat32NhwcWorkload)</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span> {</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  ClResizeWorkloadTest<ClResizeWorkload, armnn::DataType::Float32>(DataLayout::NHWC);</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> </div><div class="line"><a name="l00841"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#adda190567d36383cf30cfff21a274978"> 841</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateResizeFloat16NhwcWorkload)</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>  ClResizeWorkloadTest<ClResizeWorkload, armnn::DataType::Float16>(DataLayout::NHWC);</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> </div><div class="line"><a name="l00846"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a455f9af7175c5499cd667cc21b6fd96b"> 846</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateResizeUint8NhwcWorkload)</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span> {</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  ClResizeWorkloadTest<ClResizeWorkload, armnn::DataType::QAsymmU8>(DataLayout::NHWC);</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span> }</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span> </div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span> <span class="keyword">template</span> <<span class="keyword">typename</span> MeanWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClMeanWorkloadTest()</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span> </div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  <span class="keyword">auto</span> workload = CreateMeanWorkloadTest<MeanWorkloadType, DataType>(factory, graph);</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>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateMeanWorkloadTest).</span></div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  <a class="code" href="structarmnn_1_1_mean_queue_descriptor.xhtml">MeanQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</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>  <span class="comment">// The first dimension (batch size) in both input and output is singular thus it has been reduced by ACL.</span></div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, { 1, 3, 7, 4 }));</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, { 1, 4 }));</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span> }</div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span> </div><div class="line"><a name="l00870"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#aa9d0429b4a5edb81168bbbd256e6a807"> 870</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateMeanFloat32Workload)</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span> {</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  ClMeanWorkloadTest<ClMeanWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span> }</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span> </div><div class="line"><a name="l00875"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a3c90a48cfa87be055de22f62926b755e"> 875</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateMeanFloat16Workload)</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span> {</div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  ClMeanWorkloadTest<ClMeanWorkload, armnn::DataType::Float16>();</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span> }</div><div class="line"><a name="l00879"></a><span class="lineno"> 879</span> </div><div class="line"><a name="l00880"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a71ca2a3630a71cb48f61d55db31d2fc5"> 880</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateMeanUint8Workload)</div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span> {</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  ClMeanWorkloadTest<ClMeanWorkload, armnn::DataType::QAsymmU8>();</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span> }</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> <span class="keyword">template</span> <<span class="keyword">typename</span> ConcatWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreateConcatWorkloadTest(std::initializer_list<unsigned int> outputShape,</div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> concatAxis)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span> </div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  <span class="keyword">auto</span> workload = CreateConcatWorkloadTest<ConcatWorkloadType, DataType>(factory, graph, outputShape, concatAxis);</div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span> </div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  <a class="code" href="structarmnn_1_1_concat_queue_descriptor.xhtml">ConcatQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  <span class="keyword">auto</span> inputHandle0 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  <span class="keyword">auto</span> inputHandle1 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[1]);</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span> </div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle0, { 2, 3, 2, 5 }));</div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle1, { 2, 3, 2, 5 }));</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, outputShape));</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> </div><div class="line"><a name="l00905"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a8782f9dbea0bfb27baa047d5c961ff3e"> 905</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim0Float32Workload)</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span> {</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  ClCreateConcatWorkloadTest<ClConcatWorkload, armnn::DataType::Float32>({ 4, 3, 2, 5 }, 0);</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> </div><div class="line"><a name="l00910"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a6e908cfa4b2b0d235a7a83bb450af212"> 910</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim1Float32Workload)</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span> {</div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  ClCreateConcatWorkloadTest<ClConcatWorkload, armnn::DataType::Float32>({ 2, 6, 2, 5 }, 1);</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> </div><div class="line"><a name="l00915"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a15c6731388ff09e4fb01e12100138e40"> 915</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim3Float32Workload)</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span> {</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  ClCreateConcatWorkloadTest<ClConcatWorkload, armnn::DataType::Float32>({ 2, 3, 2, 10 }, 3);</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> </div><div class="line"><a name="l00920"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ab4f6f715f63bf06d9bb87a21e77f2129"> 920</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim0Uint8Workload)</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>  ClCreateConcatWorkloadTest<ClConcatWorkload, armnn::DataType::QAsymmU8>({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span> }</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span> </div><div class="line"><a name="l00925"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ad76e3bac3ab907f6ebf516ca8f40ad49"> 925</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim1Uint8Workload)</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>  ClCreateConcatWorkloadTest<ClConcatWorkload, armnn::DataType::QAsymmU8>({ 2, 6, 2, 5 }, 1);</div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span> }</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span> </div><div class="line"><a name="l00930"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a41bdcd447af6e0fe880fd6c746830468"> 930</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim3Uint8Workload)</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>  ClCreateConcatWorkloadTest<ClConcatWorkload, armnn::DataType::QAsymmU8>({ 2, 3, 2, 10 }, 3);</div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span> }</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span> </div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span> <span class="keyword">template</span> <<span class="keyword">typename</span> SpaceToDepthWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClSpaceToDepthWorkloadTest()</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span> {</div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span> </div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  <span class="keyword">auto</span> workload = CreateSpaceToDepthWorkloadTest<SpaceToDepthWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span> </div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  <a class="code" href="structarmnn_1_1_space_to_depth_queue_descriptor.xhtml">SpaceToDepthQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span> </div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, { 1, 2, 2, 1 }));</div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, { 1, 1, 1, 4 }));</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"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a1c4700174743960fe55fea9802ca7943"> 952</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthFloat32Workload)</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>  ClSpaceToDepthWorkloadTest<ClSpaceToDepthWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span> }</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span> </div><div class="line"><a name="l00957"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a59f3a522fe899842007639e90ced8ef4"> 957</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthFloat16Workload)</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>  ClSpaceToDepthWorkloadTest<ClSpaceToDepthWorkload, armnn::DataType::Float16>();</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"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a8675faeba30ecf6ea82ed14e7e03e5ab"> 962</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthQAsymm8Workload)</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>  ClSpaceToDepthWorkloadTest<ClSpaceToDepthWorkload, armnn::DataType::QAsymmU8>();</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"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a43e4abafcf0700a7531d8dc7f27d7eb6"> 967</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthQSymm16Workload)</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>  ClSpaceToDepthWorkloadTest<ClSpaceToDepthWorkload, armnn::DataType::QSymmS16>();</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> <span class="keyword">template</span> <armnn::DataType DataType></div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreateStackWorkloadTest(<span class="keyword">const</span> std::initializer_list<unsigned int>& inputShape,</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  <span class="keyword">const</span> std::initializer_list<unsigned int>& outputShape,</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axis,</div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs)</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span> {</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span> </div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  <span class="keyword">auto</span> workload = CreateStackWorkloadTest<ClStackWorkload, DataType>(factory,</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  graph,</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(inputShape),</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(outputShape),</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  axis,</div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  numInputs);</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span> </div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  <span class="comment">// Check inputs and output are as expected</span></div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  <a class="code" href="structarmnn_1_1_stack_queue_descriptor.xhtml">StackQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</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="l00992"></a><span class="lineno"> 992</span>  {</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span>  <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[i]);</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(inputHandle, inputShape));</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>  <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  BOOST_TEST(<a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a>(outputHandle, outputShape));</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span> }</div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span> </div><div class="line"><a name="l01000"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a72d6262ab8544dbfa7cfc22910e3011c"> 1000</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateStackFloat32Workload)</div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span> {</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  ClCreateStackWorkloadTest<armnn::DataType::Float32>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span> }</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span> </div><div class="line"><a name="l01005"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#ab0649f45ba567b07c038f5f6afd6d393"> 1005</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateStackFloat16Workload)</div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span> {</div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  ClCreateStackWorkloadTest<armnn::DataType::Float16>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span> }</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span> </div><div class="line"><a name="l01010"></a><span class="lineno"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#a966e80d9fbe654c47b44265d982d3c33"> 1010</a></span> <a class="code" href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a>(CreateStackUint8Workload)</div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span> {</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  ClCreateStackWorkloadTest<armnn::DataType::QAsymmU8>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</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> </div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span> <span class="keyword">template</span> <<span class="keyword">typename</span> QuantizedLstmWorkloadType></div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span> <span class="keyword">static</span> <span class="keywordtype">void</span> ClCreateQuantizedLstmWorkloadTest()</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span> {</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn_1_1armcomputetensorutils.xhtml">armnn::armcomputetensorutils</a>;</div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#a28f9c43e98211c77e579a14fb465bc77">boost::polymorphic_downcast</a>;</div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span> </div><div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">ClWorkloadFactory</a> factory =</div><div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreateQuantizedLstmWorkloadTest<QuantizedLstmWorkloadType>(factory, graph);</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>  <a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml">QuantizedLstmQueueDescriptor</a> queueDescriptor = workload->GetData();</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>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* inputHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>  BOOST_TEST((inputHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 2})));</div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  BOOST_TEST((inputHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QASYMM8));</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span> </div><div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* cellStateInHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]);</div><div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>  BOOST_TEST((cellStateInHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>  BOOST_TEST((cellStateInHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QSYMM16));</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>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* outputStateInHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[2]);</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  BOOST_TEST((outputStateInHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  BOOST_TEST((outputStateInHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QASYMM8));</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span> </div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* cellStateOutHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  BOOST_TEST((cellStateOutHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  BOOST_TEST((cellStateOutHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QSYMM16));</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>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* outputStateOutHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]);</div><div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>  BOOST_TEST((outputStateOutHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  BOOST_TEST((outputStateOutHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QASYMM8));</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"><a class="line" href="_cl_create_workload_tests_8cpp.xhtml#aed3a050eccd0708a65889e9fd33a8cbd"> 1050</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateQuantizedLstmWorkload)</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>  ClCreateQuantizedLstmWorkloadTest<ClQuantizedLstmWorkload>();</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> <a class="code" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="ttc" id="structarmnn_1_1_multiplication_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">armnn::MultiplicationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00222">WorkloadData.hpp:222</a></div></div> +<div class="ttc" id="_mem_copy_workload_8hpp_xhtml"><div class="ttname"><a href="_mem_copy_workload_8hpp.xhtml">MemCopyWorkload.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_cl_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_cl_workload_factory.xhtml">armnn::ClWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_workload_factory_8hpp_source.xhtml#l00017">ClWorkloadFactory.hpp:17</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a28f9c43e98211c77e579a14fb465bc77"><div class="ttname"><a href="namespacearmnn.xhtml#a28f9c43e98211c77e579a14fb465bc77">armnn::polymorphic_downcast</a></div><div class="ttdeci">DestType polymorphic_downcast(SourceType value)</div><div class="ttdef"><b>Definition:</b> <a href="_polymorphic_downcast_8hpp_source.xhtml#l00033">PolymorphicDowncast.hpp:33</a></div></div> +<div class="ttc" id="_cl_workload_factory_helper_8hpp_xhtml"><div class="ttname"><a href="_cl_workload_factory_helper_8hpp.xhtml">ClWorkloadFactoryHelper.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00049">Types.hpp:49</a></div></div> +<div class="ttc" id="structarmnn_1_1_splitter_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_splitter_queue_descriptor.xhtml">armnn::SplitterQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00083">WorkloadData.hpp:83</a></div></div> +<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml">armnn::QuantizedLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00512">WorkloadData.hpp:512</a></div></div> +<div class="ttc" id="_cl_create_workload_tests_8cpp_xhtml_a7906dccbc8d08250fd4d7a79d4d9c722"><div class="ttname"><a href="_cl_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722">BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(CreateActivationFloatWorkload)</div><div class="ttdef"><b>Definition:</b> <a href="_cl_create_workload_tests_8cpp_source.xhtml#l00045">ClCreateWorkloadTests.cpp:45</a></div></div> +<div class="ttc" id="_cl_workloads_8hpp_xhtml"><div class="ttname"><a href="_cl_workloads_8hpp.xhtml">ClWorkloads.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_cl_addition_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_cl_addition_workload.xhtml">armnn::ClAdditionWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_addition_workload_8hpp_source.xhtml#l00015">ClAdditionWorkload.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_stack_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stack_queue_descriptor.xhtml">armnn::StackQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00124">WorkloadData.hpp:124</a></div></div> +<div class="ttc" id="_arm_compute_tensor_utils_8hpp_xhtml"><div class="ttname"><a href="_arm_compute_tensor_utils_8hpp.xhtml">ArmComputeTensorUtils.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_addition_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00216">WorkloadData.hpp:216</a></div></div> +<div class="ttc" id="_cl_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_cl_workload_factory_8hpp.xhtml">ClWorkloadFactory.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_fully_connected_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml">armnn::FullyConnectedQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00141">WorkloadData.hpp:141</a></div></div> +<div class="ttc" id="structarmnn_1_1_prelu_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_prelu_queue_descriptor.xhtml">armnn::PreluQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00489">WorkloadData.hpp:489</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_acl_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_tensor_handle_8hpp_source.xhtml#l00016">ArmComputeTensorHandle.hpp:16</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="structarmnn_1_1_softmax_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_softmax_queue_descriptor.xhtml">armnn::SoftmaxQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00077">WorkloadData.hpp:77</a></div></div> +<div class="ttc" id="structarmnn_1_1_division_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_division_queue_descriptor.xhtml">armnn::DivisionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00228">WorkloadData.hpp:228</a></div></div> +<div class="ttc" id="structarmnn_1_1_subtraction_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">armnn::SubtractionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00234">WorkloadData.hpp:234</a></div></div> +<div class="ttc" id="structarmnn_1_1_concat_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_concat_queue_descriptor.xhtml">armnn::ConcatQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00102">WorkloadData.hpp:102</a></div></div> +<div class="ttc" id="_create_workload_cl_neon_8hpp_xhtml"><div class="ttname"><a href="_create_workload_cl_neon_8hpp.xhtml">CreateWorkloadClNeon.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_space_to_depth_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_queue_descriptor.xhtml">armnn::SpaceToDepthQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00348">WorkloadData.hpp:348</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_acl_tensor_handle_xhtml_a3767f569fc55323ddf7b2ee57987d9c5"><div class="ttname"><a href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">armnn::IAclTensorHandle::GetDataType</a></div><div class="ttdeci">virtual arm_compute::DataType GetDataType() const =0</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#l00032">Types.hpp:32</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_queue_descriptor.xhtml">armnn::LstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00358">WorkloadData.hpp:358</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_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="structarmnn_1_1_convert_fp16_to_fp32_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convert_fp16_to_fp32_queue_descriptor.xhtml">armnn::ConvertFp16ToFp32QueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00410">WorkloadData.hpp:410</a></div></div> +<div class="ttc" id="classarmnn_1_1_cl_splitter_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_cl_splitter_workload.xhtml">armnn::ClSplitterWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_splitter_workload_8hpp_source.xhtml#l00022">ClSplitterWorkload.hpp:22</a></div></div> +<div class="ttc" id="classarmnn_1_1_cl_activation_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_cl_activation_workload.xhtml">armnn::ClActivationWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_activation_workload_8hpp_source.xhtml#l00018">ClActivationWorkload.hpp:18</a></div></div> +<div class="ttc" id="classarmnn_1_1_cl_multiplication_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_cl_multiplication_workload.xhtml">armnn::ClMultiplicationWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_multiplication_workload_8hpp_source.xhtml#l00019">ClMultiplicationWorkload.hpp:19</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a10d15f3df1ab52b3b915a4be1dbf386b"><div class="ttname"><a href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">armnn::BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00170">ConstTensorLayerVisitor.cpp:170</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_xhtml_affd5aae75cad90f472f96cfd25a13f29"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">armnn::ITensorHandle::GetShape</a></div><div class="ttdeci">virtual TensorShape GetShape() const =0</div><div class="ttdoc">Get the number of elements for each dimension ordered from slowest iterating dimension to fastest ite...</div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="structarmnn_1_1_convert_fp32_to_fp16_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convert_fp32_to_fp16_queue_descriptor.xhtml">armnn::ConvertFp32ToFp16QueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00415">WorkloadData.hpp:415</a></div></div> +<div class="ttc" id="classarmnn_1_1_addition_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_addition_layer.xhtml">armnn::AdditionLayer</a></div><div class="ttdoc">This layer represents an addition operation. </div><div class="ttdef"><b>Definition:</b> <a href="_addition_layer_8hpp_source.xhtml#l00013">AdditionLayer.hpp:13</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">armnn::Convolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00168">WorkloadData.hpp:168</a></div></div> +<div class="ttc" id="_profiler_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div> +<div class="ttc" id="classarmnn_1_1_subtraction_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_subtraction_layer.xhtml">armnn::SubtractionLayer</a></div><div class="ttdoc">This layer represents a subtraction operation. </div><div class="ttdef"><b>Definition:</b> <a href="_subtraction_layer_8hpp_source.xhtml#l00014">SubtractionLayer.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_l2_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_queue_descriptor.xhtml">armnn::L2NormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00316">WorkloadData.hpp:316</a></div></div> +<div class="ttc" id="_cl_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cl_tensor_handle_8hpp.xhtml">ClTensorHandle.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_cl_sub_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_cl_sub_tensor_handle.xhtml">armnn::ClSubTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_tensor_handle_8hpp_source.xhtml#l00174">ClTensorHandle.hpp:174</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00031">WorkloadData.hpp:31</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_cl_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_cl_tensor_handle.xhtml">armnn::IClTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_tensor_handle_8hpp_source.xhtml#l00025">ClTensorHandle.hpp:25</a></div></div> +<div class="ttc" id="_cl_create_workload_tests_8cpp_xhtml_a6355f6187af6b3d95c55b85ac79a732e"><div class="ttname"><a href="_cl_create_workload_tests_8cpp.xhtml#a6355f6187af6b3d95c55b85ac79a732e">CompareIClTensorHandleShape</a></div><div class="ttdeci">boost::test_tools::predicate_result CompareIClTensorHandleShape(IClTensorHandle *tensorHandle, std::initializer_list< unsigned int > expectedDimensions)</div><div class="ttdef"><b>Definition:</b> <a href="_cl_create_workload_tests_8cpp_source.xhtml#l00019">ClCreateWorkloadTests.cpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">armnn::BatchNormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00269">WorkloadData.hpp:269</a></div></div> +<div class="ttc" id="classarmnn_1_1_cl_division_float_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_cl_division_float_workload.xhtml">armnn::ClDivisionFloatWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_division_float_workload_8hpp_source.xhtml#l00019">ClDivisionFloatWorkload.hpp:19</a></div></div> +<div class="ttc" id="classarmnn_1_1_division_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_division_layer.xhtml">armnn::DivisionLayer</a></div><div class="ttdoc">This layer represents a division operation. </div><div class="ttdef"><b>Definition:</b> <a href="_division_layer_8hpp_source.xhtml#l00014">DivisionLayer.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a1cfaa710db2a54673b21d2ea2da757c8"><div class="ttname"><a href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8">armnn::UnaryOperation</a></div><div class="ttdeci">UnaryOperation</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00087">Types.hpp:87</a></div></div> +<div class="ttc" id="_cl_context_control_fixture_8hpp_xhtml"><div class="ttname"><a href="_cl_context_control_fixture_8hpp.xhtml">ClContextControlFixture.hpp</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="struct_cl_context_control_fixture_base_xhtml"><div class="ttname"><a href="struct_cl_context_control_fixture_base.xhtml">ClContextControlFixtureBase</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_context_control_fixture_8hpp_source.xhtml#l00012">ClContextControlFixture.hpp:12</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00030">WorkloadData.hpp:30</a></div></div> +<div class="ttc" id="classarmnn_1_1_cl_subtraction_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_cl_subtraction_workload.xhtml">armnn::ClSubtractionWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_subtraction_workload_8hpp_source.xhtml#l00015">ClSubtractionWorkload.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_pooling2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_queue_descriptor.xhtml">armnn::Pooling2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00162">WorkloadData.hpp:162</a></div></div> +<div class="ttc" id="structarmnn_1_1_mean_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mean_queue_descriptor.xhtml">armnn::MeanQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00246">WorkloadData.hpp:246</a></div></div> +<div class="ttc" id="namespacearmnn_1_1armcomputetensorutils_xhtml"><div class="ttname"><a href="namespacearmnn_1_1armcomputetensorutils.xhtml">armnn::armcomputetensorutils</a></div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_tensor_utils_8cpp_source.xhtml#l00013">ArmComputeTensorUtils.cpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_multiplication_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_multiplication_layer.xhtml">armnn::MultiplicationLayer</a></div><div class="ttdoc">This layer represents a multiplication operation. </div><div class="ttdef"><b>Definition:</b> <a href="_multiplication_layer_8hpp_source.xhtml#l00014">MultiplicationLayer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_cl_sub_tensor_handle_xhtml_acc4bae0ff435653e44b6e6eed89c08fa"><div class="ttname"><a href="classarmnn_1_1_cl_sub_tensor_handle.xhtml#acc4bae0ff435653e44b6e6eed89c08fa">armnn::ClSubTensorHandle::GetTensor</a></div><div class="ttdeci">arm_compute::CLSubTensor & GetTensor() override</div><div class="ttdef"><b>Definition:</b> <a href="_cl_tensor_handle_8hpp_source.xhtml#l00185">ClTensorHandle.hpp:185</a></div></div> +<div class="ttc" id="_cl_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_cl_workload_utils_8hpp.xhtml">ClWorkloadUtils.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_reshape_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_reshape_queue_descriptor.xhtml">armnn::ReshapeQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00338">WorkloadData.hpp:338</a></div></div> +<div class="ttc" id="classarmnn_1_1_cl_batch_normalization_float_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_cl_batch_normalization_float_workload.xhtml">armnn::ClBatchNormalizationFloatWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_batch_normalization_float_workload_8hpp_source.xhtml#l00024">ClBatchNormalizationFloatWorkload.hpp:24</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">armnn::DepthwiseConvolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00183">WorkloadData.hpp:183</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_queue_descriptor.xhtml">armnn::ActivationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00130">WorkloadData.hpp:130</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8hpp_source.xhtml#l00014">InternalTypes.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_normalization_queue_descriptor.xhtml">armnn::NormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00210">WorkloadData.hpp:210</a></div></div> +</div><!-- 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