Ryan OShea | de36e4a | 2020-03-13 16:26:19 +0000 | [diff] [blame] | 1 | <!-- Copyright (c) 2020 ARM Limited. --> |
| 2 | <!-- --> |
| 3 | <!-- SPDX-License-Identifier: MIT --> |
| 4 | <!-- --> |
| 5 | <!-- HTML header for doxygen 1.8.13--> |
| 6 | <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> |
| 7 | <html xmlns="http://www.w3.org/1999/xhtml"> |
| 8 | <head> |
| 9 | <meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> |
| 10 | <meta http-equiv="X-UA-Compatible" content="IE=9"/> |
| 11 | <meta name="generator" content="Doxygen 1.8.13"/> |
| 12 | <meta name="robots" content="NOINDEX, NOFOLLOW" /> |
| 13 | <meta name="viewport" content="width=device-width, initial-scale=1"/> |
| 14 | <title>ArmNN: src/backends/backendsCommon/test/layerTests/AdditionTestImpl.cpp File Reference</title> |
| 15 | <link href="tabs.css" rel="stylesheet" type="text/css"/> |
| 16 | <script type="text/javascript" src="jquery.js"></script> |
| 17 | <script type="text/javascript" src="dynsections.js"></script> |
| 18 | <link href="navtree.css" rel="stylesheet" type="text/css"/> |
| 19 | <script type="text/javascript" src="resize.js"></script> |
| 20 | <script type="text/javascript" src="navtreedata.js"></script> |
| 21 | <script type="text/javascript" src="navtree.js"></script> |
| 22 | <script type="text/javascript"> |
| 23 | $(document).ready(initResizable); |
| 24 | </script> |
| 25 | <link href="search/search.css" rel="stylesheet" type="text/css"/> |
| 26 | <script type="text/javascript" src="search/searchdata.js"></script> |
| 27 | <script type="text/javascript" src="search/search.js"></script> |
| 28 | <script type="text/x-mathjax-config"> |
| 29 | MathJax.Hub.Config({ |
| 30 | extensions: ["tex2jax.js"], |
| 31 | jax: ["input/TeX","output/HTML-CSS"], |
| 32 | }); |
| 33 | </script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> |
| 34 | <link href="doxygen.css" rel="stylesheet" type="text/css" /> |
| 35 | <link href="stylesheet.css" rel="stylesheet" type="text/css"/> |
| 36 | </head> |
| 37 | <body> |
| 38 | <div id="top"><!-- do not remove this div, it is closed by doxygen! --> |
| 39 | <div id="titlearea"> |
| 40 | <table cellspacing="0" cellpadding="0"> |
| 41 | <tbody> |
| 42 | <tr style="height: 56px;"> |
| 43 | <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> |
| 44 | <td style="padding-left: 0.5em;"> |
| 45 | <div id="projectname"> |
| 46 |  <span id="projectnumber">20.02</span> |
| 47 | </div> |
| 48 | </td> |
| 49 | </tr> |
| 50 | </tbody> |
| 51 | </table> |
| 52 | </div> |
| 53 | <!-- end header part --> |
| 54 | <!-- Generated by Doxygen 1.8.13 --> |
| 55 | <script type="text/javascript"> |
| 56 | var searchBox = new SearchBox("searchBox", "search",false,'Search'); |
| 57 | </script> |
| 58 | <script type="text/javascript" src="menudata.js"></script> |
| 59 | <script type="text/javascript" src="menu.js"></script> |
| 60 | <script type="text/javascript"> |
| 61 | $(function() { |
| 62 | initMenu('',true,false,'search.php','Search'); |
| 63 | $(document).ready(function() { init_search(); }); |
| 64 | }); |
| 65 | </script> |
| 66 | <div id="main-nav"></div> |
| 67 | </div><!-- top --> |
| 68 | <div id="side-nav" class="ui-resizable side-nav-resizable"> |
| 69 | <div id="nav-tree"> |
| 70 | <div id="nav-tree-contents"> |
| 71 | <div id="nav-sync" class="sync"></div> |
| 72 | </div> |
| 73 | </div> |
| 74 | <div id="splitbar" style="-moz-user-select:none;" |
| 75 | class="ui-resizable-handle"> |
| 76 | </div> |
| 77 | </div> |
| 78 | <script type="text/javascript"> |
| 79 | $(document).ready(function(){initNavTree('_addition_test_impl_8cpp.xhtml','');}); |
| 80 | </script> |
| 81 | <div id="doc-content"> |
| 82 | <!-- window showing the filter options --> |
| 83 | <div id="MSearchSelectWindow" |
| 84 | onmouseover="return searchBox.OnSearchSelectShow()" |
| 85 | onmouseout="return searchBox.OnSearchSelectHide()" |
| 86 | onkeydown="return searchBox.OnSearchSelectKey(event)"> |
| 87 | </div> |
| 88 | |
| 89 | <!-- iframe showing the search results (closed by default) --> |
| 90 | <div id="MSearchResultsWindow"> |
| 91 | <iframe src="javascript:void(0)" frameborder="0" |
| 92 | name="MSearchResults" id="MSearchResults"> |
| 93 | </iframe> |
| 94 | </div> |
| 95 | |
| 96 | <div class="header"> |
| 97 | <div class="summary"> |
| 98 | <a href="#func-members">Functions</a> </div> |
| 99 | <div class="headertitle"> |
| 100 | <div class="title">AdditionTestImpl.cpp File Reference</div> </div> |
| 101 | </div><!--header--> |
| 102 | <div class="contents"> |
| 103 | <div class="textblock"><code>#include "<a class="el" href="_addition_test_impl_8hpp_source.xhtml">AdditionTestImpl.hpp</a>"</code><br /> |
| 104 | <code>#include "<a class="el" href="_elementwise_test_impl_8hpp_source.xhtml">ElementwiseTestImpl.hpp</a>"</code><br /> |
| 105 | <code>#include <<a class="el" href="_quantize_helper_8hpp_source.xhtml">QuantizeHelper.hpp</a>></code><br /> |
| 106 | </div> |
| 107 | <p><a href="_addition_test_impl_8cpp_source.xhtml">Go to the source code of this file.</a></p> |
| 108 | <table class="memberdecls"> |
| 109 | <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> |
| 110 | Functions</h2></td></tr> |
| 111 | <tr class="memitem:a5f3caae0b1541a904067544dd37655f0"><td class="memTemplParams" colspan="2">template<> </td></tr> |
| 112 | <tr class="memitem:a5f3caae0b1541a904067544dd37655f0"><td class="memTemplItemLeft" align="right" valign="top">std::unique_ptr< <a class="el" href="classarmnn_1_1_i_workload.xhtml">armnn::IWorkload</a> > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#a5f3caae0b1541a904067544dd37655f0">CreateWorkload< armnn::AdditionQueueDescriptor ></a> (const <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> &info, const <a class="el" href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a> &descriptor)</td></tr> |
| 113 | <tr class="separator:a5f3caae0b1541a904067544dd37655f0"><td class="memSeparator" colspan="2"> </td></tr> |
| 114 | <tr class="memitem:a108165b4957f3790332ae0afedf37ccd"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#a108165b4957f3790332ae0afedf37ccd">AdditionTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 115 | <tr class="separator:a108165b4957f3790332ae0afedf37ccd"><td class="memSeparator" colspan="2"> </td></tr> |
| 116 | <tr class="memitem:ab102e5bc3a3b04360a0f42e25ab3c898"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 5 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#ab102e5bc3a3b04360a0f42e25ab3c898">Addition5dTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 117 | <tr class="separator:ab102e5bc3a3b04360a0f42e25ab3c898"><td class="memSeparator" colspan="2"> </td></tr> |
| 118 | <tr class="memitem:add789f43d728a34fccf9aea235179342"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> |
| 119 | <tr class="memitem:add789f43d728a34fccf9aea235179342"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#add789f43d728a34fccf9aea235179342">AdditionBroadcastTestImpl</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, float qScale, int32_t qOffset)</td></tr> |
| 120 | <tr class="separator:add789f43d728a34fccf9aea235179342"><td class="memSeparator" colspan="2"> </td></tr> |
| 121 | <tr class="memitem:ad6a320dc43ad2384cf2d7288cf9c0823"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> |
| 122 | <tr class="memitem:ad6a320dc43ad2384cf2d7288cf9c0823"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#ad6a320dc43ad2384cf2d7288cf9c0823">AdditionBroadcast1ElementTestImpl</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, float qScale, int32_t qOffset)</td></tr> |
| 123 | <tr class="separator:ad6a320dc43ad2384cf2d7288cf9c0823"><td class="memSeparator" colspan="2"> </td></tr> |
| 124 | <tr class="memitem:a9591268a5a6c7d0a0b91098deab4fe34"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#a9591268a5a6c7d0a0b91098deab4fe34">AdditionBroadcastTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 125 | <tr class="separator:a9591268a5a6c7d0a0b91098deab4fe34"><td class="memSeparator" colspan="2"> </td></tr> |
| 126 | <tr class="memitem:a0946a9b1b8cf99591b03ea7f5f7e725f"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#a0946a9b1b8cf99591b03ea7f5f7e725f">AdditionBroadcastUint8Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 127 | <tr class="separator:a0946a9b1b8cf99591b03ea7f5f7e725f"><td class="memSeparator" colspan="2"> </td></tr> |
| 128 | <tr class="memitem:a470ed90260ed36c02adc91df184fcc82"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#a470ed90260ed36c02adc91df184fcc82">AdditionBroadcastInt16Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 129 | <tr class="separator:a470ed90260ed36c02adc91df184fcc82"><td class="memSeparator" colspan="2"> </td></tr> |
| 130 | <tr class="memitem:a4bff97bff3f9fb4cf473812dee810de0"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#a4bff97bff3f9fb4cf473812dee810de0">AdditionBroadcast1ElementTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 131 | <tr class="separator:a4bff97bff3f9fb4cf473812dee810de0"><td class="memSeparator" colspan="2"> </td></tr> |
| 132 | <tr class="memitem:ad71ffd0e8547900b92a5d471f01cd69b"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#ad71ffd0e8547900b92a5d471f01cd69b">AdditionBroadcast1ElementUint8Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 133 | <tr class="separator:ad71ffd0e8547900b92a5d471f01cd69b"><td class="memSeparator" colspan="2"> </td></tr> |
| 134 | <tr class="memitem:a97579bb78890452730fff4d1e3e6fb4a"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#a97579bb78890452730fff4d1e3e6fb4a">AdditionBroadcast1ElementInt16Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 135 | <tr class="separator:a97579bb78890452730fff4d1e3e6fb4a"><td class="memSeparator" colspan="2"> </td></tr> |
| 136 | <tr class="memitem:a4b5e20456506426ba2e4ea9616df978f"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#a4b5e20456506426ba2e4ea9616df978f">AdditionUint8Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 137 | <tr class="separator:a4b5e20456506426ba2e4ea9616df978f"><td class="memSeparator" colspan="2"> </td></tr> |
| 138 | <tr class="memitem:ae087613cdb8319fbab07d44e6eaf217d"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#ae087613cdb8319fbab07d44e6eaf217d">AdditionInt16Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 139 | <tr class="separator:ae087613cdb8319fbab07d44e6eaf217d"><td class="memSeparator" colspan="2"> </td></tr> |
| 140 | <tr class="memitem:aa11fe3b8a07854e2bb9dd3ccecaa96e4"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#aa11fe3b8a07854e2bb9dd3ccecaa96e4">AdditionAfterMaxPoolTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> |
| 141 | <tr class="separator:aa11fe3b8a07854e2bb9dd3ccecaa96e4"><td class="memSeparator" colspan="2"> </td></tr> |
| 142 | <tr class="memitem:a557c464592942eb098f63aa0f91e4d24"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.xhtml#a557c464592942eb098f63aa0f91e4d24">CompareAdditionTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &refWorkloadFactory)</td></tr> |
| 143 | <tr class="separator:a557c464592942eb098f63aa0f91e4d24"><td class="memSeparator" colspan="2"> </td></tr> |
| 144 | </table> |
| 145 | <h2 class="groupheader">Function Documentation</h2> |
| 146 | <a id="ab102e5bc3a3b04360a0f42e25ab3c898"></a> |
| 147 | <h2 class="memtitle"><span class="permalink"><a href="#ab102e5bc3a3b04360a0f42e25ab3c898">◆ </a></span>Addition5dTest()</h2> |
| 148 | |
| 149 | <div class="memitem"> |
| 150 | <div class="memproto"> |
| 151 | <table class="memname"> |
| 152 | <tr> |
| 153 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 5> Addition5dTest </td> |
| 154 | <td>(</td> |
| 155 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 156 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 157 | </tr> |
| 158 | <tr> |
| 159 | <td class="paramkey"></td> |
| 160 | <td></td> |
| 161 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 162 | <td class="paramname"><em>memoryManager</em> </td> |
| 163 | </tr> |
| 164 | <tr> |
| 165 | <td></td> |
| 166 | <td>)</td> |
| 167 | <td></td><td></td> |
| 168 | </tr> |
| 169 | </table> |
| 170 | </div><div class="memdoc"> |
| 171 | |
| 172 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00089">89</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 173 | <div class="fragment"><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> {</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth = 2u;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 2u;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 2u;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 2u;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = 3u;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = { depth, batchSize, channels, height, width };</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  std::vector<float> input1 =</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>  2.6f, 4.0f, 4.4f, 2.7f, 4.6f, 2.8f,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  2.3f, 1.9f, 3.4f, 2.9f, 2.2f, 4.5f,</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  2.8f, 1.9f, 2.3f, 2.6f, 4.7f, 3.5f,</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  0.4f, 1.5f, 2.1f, 0.7f, 5.0f, 1.1f,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  1.0f, 2.7f, 0.0f, 0.6f, 0.8f, 0.9f,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  1.0f, 2.6f, 0.4f, 3.8f, 0.4f, 0.8f,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  0.5f, 4.3f, 3.1f, 4.4f, 0.7f, 1.4f,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  0.4f, 4.4f, 0.7f, 0.6f, 4.7f, 1.2f,</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"> 117</span> </div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  std::vector<float> input2 =</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  {</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  4.4f, 3.0f, 1.0f, 0.0f, 3.9f, 3.1f,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  1.7f, 2.9f, 1.3f, 0.4f, 0.4f, 4.3f,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> </div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  4.5f, 0.2f, 2.2f, 4.1f, 3.9f, 3.0f,</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  0.1f, 2.5f, 4.1f, 4.6f, 1.5f, 0.0f,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> </div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  0.5f, 4.9f, 2.5f, 1.5f, 3.4f, 4.5f,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  2.0f, 3.0f, 4.9f, 1.6f, 2.4f, 3.4f,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  3.6f, 1.8f, 1.3f, 2.6f, 2.1f, 4.8f,</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  2.0f, 4.3f, 4.0f, 0.2f, 0.6f, 4.4f,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  };</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  std::vector<float> output =</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  7.0f, 7.0f, 5.4f, 2.7f, 8.5f, 5.9f,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  4.0f, 4.8f, 4.7f, 3.3f, 2.6f, 8.8f,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  7.3f, 2.1f, 4.5f, 6.7f, 8.6f, 6.5f,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  0.5f, 4.0f, 6.2f, 5.3f, 6.5f, 1.1f,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> </div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  1.5f, 7.6f, 2.5f, 2.1f, 4.2f, 5.4f,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  3.0f, 5.6f, 5.3f, 5.4f, 2.8f, 4.2f,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> </div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  4.1f, 6.1f, 4.4f, 7.0f, 2.8f, 6.2f,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  2.4f, 8.7f, 4.7f, 0.8f, 5.3f, 5.6f,</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> </div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keywordflow">return</span> ElementwiseTestHelper<5, armnn::AdditionQueueDescriptor, armnn::DataType::Float32>(</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  workloadFactory,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  memoryManager,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  shape,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  input1,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  shape,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  input2,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  shape,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  output);</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> }</div></div><!-- fragment --> |
| 174 | </div> |
| 175 | </div> |
| 176 | <a id="aa11fe3b8a07854e2bb9dd3ccecaa96e4"></a> |
| 177 | <h2 class="memtitle"><span class="permalink"><a href="#aa11fe3b8a07854e2bb9dd3ccecaa96e4">◆ </a></span>AdditionAfterMaxPoolTest()</h2> |
| 178 | |
| 179 | <div class="memitem"> |
| 180 | <div class="memproto"> |
| 181 | <table class="memname"> |
| 182 | <tr> |
| 183 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 4> AdditionAfterMaxPoolTest </td> |
| 184 | <td>(</td> |
| 185 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 186 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 187 | </tr> |
| 188 | <tr> |
| 189 | <td class="paramkey"></td> |
| 190 | <td></td> |
| 191 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 192 | <td class="paramname"><em>memoryManager</em> </td> |
| 193 | </tr> |
| 194 | <tr> |
| 195 | <td></td> |
| 196 | <td>)</td> |
| 197 | <td></td><td></td> |
| 198 | </tr> |
| 199 | </table> |
| 200 | </div><div class="memdoc"> |
| 201 | |
| 202 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00454">454</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 203 | |
| 204 | <p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01105">IWorkloadFactory::CreateAddition()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01340">IWorkloadFactory::CreatePooling2d()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00049">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00359">Pooling2dDescriptor::m_PoolHeight</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00347">Pooling2dDescriptor::m_PoolType</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00357">Pooling2dDescriptor::m_PoolWidth</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00361">Pooling2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00363">Pooling2dDescriptor::m_StrideY</a>, and <a class="el" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::Max</a>.</p> |
| 205 | |
| 206 | <p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l01123">BOOST_AUTO_TEST_CASE()</a>.</p> |
| 207 | <div class="fragment"><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>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span> </div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <span class="comment">// Create Initial Tensor</span></div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <span class="comment">// 1, 2, 3</span></div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <span class="comment">// 4, 5, 6</span></div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="comment">// 7, 8, 9</span></div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span> </div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> poolingInputTensorInfo({ 1, 1, 3, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> poolingOutputTensorInfo({ 1, 1, 2, 2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span> </div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  boost::multi_array<float, 4> poolingInput = MakeTensor<float,4>(poolingInputTensorInfo,</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  {1, 2, 3,</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  4, 5, 6,</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  7, 8, 9</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  });</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span> </div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  std::unique_ptr<armnn::ITensorHandle> poolingInputHandle =</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(poolingInputTensorInfo);</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  std::unique_ptr<armnn::ITensorHandle> poolingOutputHandle =</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(poolingOutputTensorInfo);</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>  <span class="comment">// Apply MaxPool poolSize = 1x1, stride=2x2</span></div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <span class="comment">// Result =</span></div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <span class="comment">// 1, 3</span></div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <span class="comment">// 7, 9</span></div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 1;</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = 1;</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> </div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <a class="code" href="structarmnn_1_1_pooling2d_queue_descriptor.xhtml">armnn::Pooling2dQueueDescriptor</a> queueDescriptor;</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a> = descriptor;</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  AddInputToWorkload(queueDescriptor, workloadInfo, poolingInputTensorInfo, poolingInputHandle.get());</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  AddOutputToWorkload(queueDescriptor, workloadInfo, poolingOutputTensorInfo, poolingOutputHandle.get());</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span> </div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="comment">// Create the MaxPool</span></div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a6e95afd9a55700cbf6f9e8db8089f2f2">CreatePooling2d</a>(queueDescriptor, workloadInfo);</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span> </div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <span class="comment">//LayerTestResult<float, 4> result(poolingOutputTensorInfo);</span></div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <span class="keyword">auto</span> shape( GetTensorShapeAsArray<4>(poolingOutputTensorInfo));</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  boost::multi_array<float, 4> resultMaxPool;</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  resultMaxPool.resize(shape);</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> </div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <span class="comment">// Create addition with another tensor the same size</span></div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <span class="comment">// This would be the result to apply a Conv2d with kernel ones(2) and stride 1x1</span></div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <span class="comment">// with the initial tensor.</span></div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="comment">// 12, 16</span></div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <span class="comment">// 24, 28</span></div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span> </div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> addInputTensorInfo({ 1,1,2,2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> addOutputTensorInfo({ 1,1,2,2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span> </div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  boost::multi_array<float, 4> addInput = MakeTensor<float,4>(addInputTensorInfo,</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  {12, 16,</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  24, 28,</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  });</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span> </div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="comment">// Expected output tensor after MaxPool and Addition.</span></div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float,4></a> addRet(addOutputTensorInfo);</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  addRet.outputExpected = MakeTensor<float, 4>(addOutputTensorInfo, std::vector<float>(</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>  13, 19,</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  31, 37</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  }));</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span> </div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  std::unique_ptr<armnn::ITensorHandle> addInputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(addInputTensorInfo);</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  std::unique_ptr<armnn::ITensorHandle> addOutputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(addOutputTensorInfo);</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span> </div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a> data;</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span> </div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="comment">// Add the output of the MaxPool and the new tensor</span></div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  AddInputToWorkload(data, info, poolingOutputTensorInfo, poolingOutputHandle.get());</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  AddInputToWorkload(data, info, addInputTensorInfo, addInputHandle.get());</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  AddOutputToWorkload(data, info, addOutputTensorInfo, addOutputHandle.get());</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>  std::unique_ptr<armnn::IWorkload> addWorkload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(data, info);</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span> </div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  poolingInputHandle->Allocate();</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  poolingOutputHandle->Allocate();</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  addInputHandle->Allocate();</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  addOutputHandle->Allocate();</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span> </div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(poolingInputHandle.get(), &poolingInput[0][0][0][0]);</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&resultMaxPool[0][0][0][0], poolingOutputHandle.get());</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span> </div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(poolingOutputHandle.get(), &resultMaxPool[0][0][0][0]);</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(addInputHandle.get(), &addInput[0][0][0][0]);</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>  workload->PostAllocationConfigure();</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  workload->Execute();</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  addWorkload->PostAllocationConfigure();</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  addWorkload->Execute();</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>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&addRet.output[0][0][0][0], addOutputHandle.get());</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span> </div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <span class="keywordflow">return</span> addRet;</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> |
| 208 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6d8fb685cc1ff224f25aa127fcf62c86">armnn::Pooling2dDescriptor::m_PoolWidth</a></div><div class="ttdeci">uint32_t m_PoolWidth</div><div class="ttdoc">Pooling width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00357">Descriptors.hpp:357</a></div></div> |
| 209 | <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> |
| 210 | <div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> |
| 211 | <div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00049">WorkloadData.hpp:49</a></div></div> |
| 212 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::Pooling2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00361">Descriptors.hpp:361</a></div></div> |
| 213 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a5699e8606c37d18c03910b242cd1b010">armnn::Pooling2dDescriptor::m_PoolHeight</a></div><div class="ttdeci">uint32_t m_PoolHeight</div><div class="ttdoc">Pooling height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00359">Descriptors.hpp:359</a></div></div> |
| 214 | <div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> |
| 215 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0</div></div> |
| 216 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a6e95afd9a55700cbf6f9e8db8089f2f2"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a6e95afd9a55700cbf6f9e8db8089f2f2">armnn::IWorkloadFactory::CreatePooling2d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreatePooling2d(const Pooling2dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01340">WorkloadFactory.cpp:1340</a></div></div> |
| 217 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a0031997bf43bd2747656c31e4977793a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a0031997bf43bd2747656c31e4977793a">armnn::Pooling2dDescriptor::m_PoolType</a></div><div class="ttdeci">PoolingAlgorithm m_PoolType</div><div class="ttdoc">The pooling algorithm to use (Max. Average, L2). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00347">Descriptors.hpp:347</a></div></div> |
| 218 | <div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> |
| 219 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateAddition(const AdditionQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01105">WorkloadFactory.cpp:1105</a></div></div> |
| 220 | <div class="ttc" id="namespacearmnn_xhtml_a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a></div></div> |
| 221 | <div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> |
| 222 | <div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> |
| 223 | <div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div> |
| 224 | <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> |
| 225 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00313">Descriptors.hpp:313</a></div></div> |
| 226 | <div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Pooling2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00363">Descriptors.hpp:363</a></div></div> |
| 227 | <div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> |
| 228 | </div><!-- fragment --> |
| 229 | </div> |
| 230 | </div> |
| 231 | <a id="a97579bb78890452730fff4d1e3e6fb4a"></a> |
| 232 | <h2 class="memtitle"><span class="permalink"><a href="#a97579bb78890452730fff4d1e3e6fb4a">◆ </a></span>AdditionBroadcast1ElementInt16Test()</h2> |
| 233 | |
| 234 | <div class="memitem"> |
| 235 | <div class="memproto"> |
| 236 | <table class="memname"> |
| 237 | <tr> |
| 238 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><int16_t, 4> AdditionBroadcast1ElementInt16Test </td> |
| 239 | <td>(</td> |
| 240 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 241 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 242 | </tr> |
| 243 | <tr> |
| 244 | <td class="paramkey"></td> |
| 245 | <td></td> |
| 246 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 247 | <td class="paramname"><em>memoryManager</em> </td> |
| 248 | </tr> |
| 249 | <tr> |
| 250 | <td></td> |
| 251 | <td>)</td> |
| 252 | <td></td><td></td> |
| 253 | </tr> |
| 254 | </table> |
| 255 | </div><div class="memdoc"> |
| 256 | |
| 257 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00362">362</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 258 | <div class="fragment"><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>  <span class="keywordflow">return</span> AdditionBroadcast1ElementTestImpl<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  workloadFactory, memoryManager, 0.1333333f, 0);</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> }</div></div><!-- fragment --> |
| 259 | </div> |
| 260 | </div> |
| 261 | <a id="a4bff97bff3f9fb4cf473812dee810de0"></a> |
| 262 | <h2 class="memtitle"><span class="permalink"><a href="#a4bff97bff3f9fb4cf473812dee810de0">◆ </a></span>AdditionBroadcast1ElementTest()</h2> |
| 263 | |
| 264 | <div class="memitem"> |
| 265 | <div class="memproto"> |
| 266 | <table class="memname"> |
| 267 | <tr> |
| 268 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 4> AdditionBroadcast1ElementTest </td> |
| 269 | <td>(</td> |
| 270 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 271 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 272 | </tr> |
| 273 | <tr> |
| 274 | <td class="paramkey"></td> |
| 275 | <td></td> |
| 276 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 277 | <td class="paramname"><em>memoryManager</em> </td> |
| 278 | </tr> |
| 279 | <tr> |
| 280 | <td></td> |
| 281 | <td>)</td> |
| 282 | <td></td><td></td> |
| 283 | </tr> |
| 284 | </table> |
| 285 | </div><div class="memdoc"> |
| 286 | |
| 287 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00346">346</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 288 | <div class="fragment"><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> {</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">return</span> AdditionBroadcast1ElementTestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  workloadFactory, memoryManager, 0.0f, 0);</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> }</div></div><!-- fragment --> |
| 289 | </div> |
| 290 | </div> |
| 291 | <a id="ad6a320dc43ad2384cf2d7288cf9c0823"></a> |
| 292 | <h2 class="memtitle"><span class="permalink"><a href="#ad6a320dc43ad2384cf2d7288cf9c0823">◆ </a></span>AdditionBroadcast1ElementTestImpl()</h2> |
| 293 | |
| 294 | <div class="memitem"> |
| 295 | <div class="memproto"> |
| 296 | <table class="memname"> |
| 297 | <tr> |
| 298 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> AdditionBroadcast1ElementTestImpl </td> |
| 299 | <td>(</td> |
| 300 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 301 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 302 | </tr> |
| 303 | <tr> |
| 304 | <td class="paramkey"></td> |
| 305 | <td></td> |
| 306 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 307 | <td class="paramname"><em>memoryManager</em>, </td> |
| 308 | </tr> |
| 309 | <tr> |
| 310 | <td class="paramkey"></td> |
| 311 | <td></td> |
| 312 | <td class="paramtype">float </td> |
| 313 | <td class="paramname"><em>qScale</em>, </td> |
| 314 | </tr> |
| 315 | <tr> |
| 316 | <td class="paramkey"></td> |
| 317 | <td></td> |
| 318 | <td class="paramtype">int32_t </td> |
| 319 | <td class="paramname"><em>qOffset</em> </td> |
| 320 | </tr> |
| 321 | <tr> |
| 322 | <td></td> |
| 323 | <td>)</td> |
| 324 | <td></td><td></td> |
| 325 | </tr> |
| 326 | </table> |
| 327 | </div><div class="memdoc"> |
| 328 | |
| 329 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00245">245</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 330 | |
| 331 | <p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01105">IWorkloadFactory::CreateAddition()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00040">LayerTestResult< T, n >::output</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00041">LayerTestResult< T, n >::outputExpected</a>, <a class="el" href="_tensor_8cpp_source.xhtml#l00275">TensorInfo::SetQuantizationOffset()</a>, and <a class="el" href="_tensor_8cpp_source.xhtml#l00259">TensorInfo::SetQuantizationScale()</a>.</p> |
| 332 | <div class="fragment"><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> {</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo1 = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({1, 3, 2, 3}, ArmnnType);</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo2 = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({1, 1, 1, 1}, ArmnnType);</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({1, 3, 2, 3}, ArmnnType);</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>  <span class="keywordflow">if</span> (armnn::IsQuantizedType<T>())</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  {</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  inputTensorInfo1.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  inputTensorInfo1.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  inputTensorInfo2.SetQuantizationScale(qScale);</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  inputTensorInfo2.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  outputTensorInfo.SetQuantizationScale(qScale);</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  outputTensorInfo.SetQuantizationOffset(qOffset);</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> </div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keyword">auto</span> input1 = MakeTensor<T, 4>(inputTensorInfo1, armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  {</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  0.0f, 1.0f, 2.0f,</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  6.0f, 7.0f, 8.0f,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  9.0f, 10.0f, 11.0f,</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  12.0f, 13.0f, 14.0f,</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  15.0f, 16.0f, 17.0f,</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  },</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  qScale, qOffset));</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> </div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="keyword">auto</span> input2 = MakeTensor<T, 4>(inputTensorInfo2, armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  {</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  0.5f,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  },</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  qScale, qOffset));</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> </div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T,4></a> ret(outputTensorInfo);</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  {</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  0.5f, 1.5f, 2.5f,</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  3.5f, 4.5f, 5.5f,</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  6.5f, 7.5f, 8.5f,</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  9.5f, 10.5f, 11.5f,</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  12.5f, 13.5f, 14.5f,</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  15.5f, 16.5f, 17.5f,</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>  qScale, qOffset));</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>  std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo1);</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo2);</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a> data;</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get());</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get());</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</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>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(data, info);</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> </div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  inputHandle1->Allocate();</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  inputHandle2->Allocate();</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  outputHandle->Allocate();</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> </div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle1.get(), &input1[0][0][0][0]);</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle2.get(), &input2[0][0][0][0]);</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> </div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  workload->PostAllocationConfigure();</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  workload->Execute();</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> </div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> </div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> |
| 333 | <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> |
| 334 | <div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> |
| 335 | <div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00259">Tensor.cpp:259</a></div></div> |
| 336 | <div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> |
| 337 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0</div></div> |
| 338 | <div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> |
| 339 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateAddition(const AdditionQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01105">WorkloadFactory.cpp:1105</a></div></div> |
| 340 | <div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> |
| 341 | <div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div> |
| 342 | <div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00275">Tensor.cpp:275</a></div></div> |
| 343 | <div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> |
| 344 | </div><!-- fragment --> |
| 345 | </div> |
| 346 | </div> |
| 347 | <a id="ad71ffd0e8547900b92a5d471f01cd69b"></a> |
| 348 | <h2 class="memtitle"><span class="permalink"><a href="#ad71ffd0e8547900b92a5d471f01cd69b">◆ </a></span>AdditionBroadcast1ElementUint8Test()</h2> |
| 349 | |
| 350 | <div class="memitem"> |
| 351 | <div class="memproto"> |
| 352 | <table class="memname"> |
| 353 | <tr> |
| 354 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><uint8_t, 4> AdditionBroadcast1ElementUint8Test </td> |
| 355 | <td>(</td> |
| 356 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 357 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 358 | </tr> |
| 359 | <tr> |
| 360 | <td class="paramkey"></td> |
| 361 | <td></td> |
| 362 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 363 | <td class="paramname"><em>memoryManager</em> </td> |
| 364 | </tr> |
| 365 | <tr> |
| 366 | <td></td> |
| 367 | <td>)</td> |
| 368 | <td></td><td></td> |
| 369 | </tr> |
| 370 | </table> |
| 371 | </div><div class="memdoc"> |
| 372 | |
| 373 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00354">354</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 374 | <div class="fragment"><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> {</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordflow">return</span> AdditionBroadcast1ElementTestImpl<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  workloadFactory, memoryManager, 0.1333333f, 128);</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span> }</div></div><!-- fragment --> |
| 375 | </div> |
| 376 | </div> |
| 377 | <a id="a470ed90260ed36c02adc91df184fcc82"></a> |
| 378 | <h2 class="memtitle"><span class="permalink"><a href="#a470ed90260ed36c02adc91df184fcc82">◆ </a></span>AdditionBroadcastInt16Test()</h2> |
| 379 | |
| 380 | <div class="memitem"> |
| 381 | <div class="memproto"> |
| 382 | <table class="memname"> |
| 383 | <tr> |
| 384 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><int16_t, 4> AdditionBroadcastInt16Test </td> |
| 385 | <td>(</td> |
| 386 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 387 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 388 | </tr> |
| 389 | <tr> |
| 390 | <td class="paramkey"></td> |
| 391 | <td></td> |
| 392 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 393 | <td class="paramname"><em>memoryManager</em> </td> |
| 394 | </tr> |
| 395 | <tr> |
| 396 | <td></td> |
| 397 | <td>)</td> |
| 398 | <td></td><td></td> |
| 399 | </tr> |
| 400 | </table> |
| 401 | </div><div class="memdoc"> |
| 402 | |
| 403 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00338">338</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 404 | <div class="fragment"><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="keywordflow">return</span> AdditionBroadcastTestImpl<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  workloadFactory, memoryManager, 2.f, 0);</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span> }</div></div><!-- fragment --> |
| 405 | </div> |
| 406 | </div> |
| 407 | <a id="a9591268a5a6c7d0a0b91098deab4fe34"></a> |
| 408 | <h2 class="memtitle"><span class="permalink"><a href="#a9591268a5a6c7d0a0b91098deab4fe34">◆ </a></span>AdditionBroadcastTest()</h2> |
| 409 | |
| 410 | <div class="memitem"> |
| 411 | <div class="memproto"> |
| 412 | <table class="memname"> |
| 413 | <tr> |
| 414 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 4> AdditionBroadcastTest </td> |
| 415 | <td>(</td> |
| 416 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 417 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 418 | </tr> |
| 419 | <tr> |
| 420 | <td class="paramkey"></td> |
| 421 | <td></td> |
| 422 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 423 | <td class="paramname"><em>memoryManager</em> </td> |
| 424 | </tr> |
| 425 | <tr> |
| 426 | <td></td> |
| 427 | <td>)</td> |
| 428 | <td></td><td></td> |
| 429 | </tr> |
| 430 | </table> |
| 431 | </div><div class="memdoc"> |
| 432 | |
| 433 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00322">322</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 434 | <div class="fragment"><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>  <span class="keywordflow">return</span> AdditionBroadcastTestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  workloadFactory, memoryManager, 0.0f, 0);</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> }</div></div><!-- fragment --> |
| 435 | </div> |
| 436 | </div> |
| 437 | <a id="add789f43d728a34fccf9aea235179342"></a> |
| 438 | <h2 class="memtitle"><span class="permalink"><a href="#add789f43d728a34fccf9aea235179342">◆ </a></span>AdditionBroadcastTestImpl()</h2> |
| 439 | |
| 440 | <div class="memitem"> |
| 441 | <div class="memproto"> |
| 442 | <table class="memname"> |
| 443 | <tr> |
| 444 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> AdditionBroadcastTestImpl </td> |
| 445 | <td>(</td> |
| 446 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 447 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 448 | </tr> |
| 449 | <tr> |
| 450 | <td class="paramkey"></td> |
| 451 | <td></td> |
| 452 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 453 | <td class="paramname"><em>memoryManager</em>, </td> |
| 454 | </tr> |
| 455 | <tr> |
| 456 | <td class="paramkey"></td> |
| 457 | <td></td> |
| 458 | <td class="paramtype">float </td> |
| 459 | <td class="paramname"><em>qScale</em>, </td> |
| 460 | </tr> |
| 461 | <tr> |
| 462 | <td class="paramkey"></td> |
| 463 | <td></td> |
| 464 | <td class="paramtype">int32_t </td> |
| 465 | <td class="paramname"><em>qOffset</em> </td> |
| 466 | </tr> |
| 467 | <tr> |
| 468 | <td></td> |
| 469 | <td>)</td> |
| 470 | <td></td><td></td> |
| 471 | </tr> |
| 472 | </table> |
| 473 | </div><div class="memdoc"> |
| 474 | |
| 475 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00162">162</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 476 | |
| 477 | <p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01105">IWorkloadFactory::CreateAddition()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00040">LayerTestResult< T, n >::output</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00041">LayerTestResult< T, n >::outputExpected</a>, <a class="el" href="_tensor_8cpp_source.xhtml#l00275">TensorInfo::SetQuantizationOffset()</a>, and <a class="el" href="_tensor_8cpp_source.xhtml#l00259">TensorInfo::SetQuantizationScale()</a>.</p> |
| 478 | <div class="fragment"><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>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo1 = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({1, 3, 2, 1}, ArmnnType);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo2 = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({1, 1, 2, 3}, ArmnnType);</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({1, 3, 2, 3}, ArmnnType);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keywordflow">if</span> (armnn::IsQuantizedType<T>())</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>  inputTensorInfo1.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  inputTensorInfo1.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  inputTensorInfo2.SetQuantizationScale(qScale);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  inputTensorInfo2.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  outputTensorInfo.SetQuantizationScale(qScale);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  outputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  }</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keyword">auto</span> input1 = MakeTensor<T, 4>(inputTensorInfo1, armnnUtils::QuantizedVector<T>(</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>  0.0f,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  1.0f,</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  2.0f,</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  3.0f,</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  4.0f,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  5.0f,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  },</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  qScale, qOffset));</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keyword">auto</span> input2 = MakeTensor<T, 4>(inputTensorInfo2, armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  {</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  0.5f, 1.5f, 2.5f,</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  3.5f, 4.5f, 5.5f,</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>  qScale, qOffset));</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> </div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T,4></a> ret(outputTensorInfo);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  {</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  0.5f, 1.5f, 2.5f,</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  4.5f, 5.5f, 6.5f,</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> </div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  2.5f, 3.5f, 4.5f,</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  6.5f, 7.5f, 8.5f,</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> </div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  4.5f, 5.5f, 6.5f,</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  8.5f, 9.5f, 10.5f,</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  },</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  qScale, qOffset));</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> </div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo1);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo2);</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> </div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a> data;</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get());</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get());</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(data, info);</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> </div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  inputHandle1->Allocate();</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  inputHandle2->Allocate();</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  outputHandle->Allocate();</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> </div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle1.get(), &input1[0][0][0][0]);</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle2.get(), &input2[0][0][0][0]);</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> </div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  workload->PostAllocationConfigure();</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  workload->Execute();</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> |
| 479 | <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> |
| 480 | <div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> |
| 481 | <div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00259">Tensor.cpp:259</a></div></div> |
| 482 | <div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> |
| 483 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0</div></div> |
| 484 | <div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> |
| 485 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateAddition(const AdditionQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01105">WorkloadFactory.cpp:1105</a></div></div> |
| 486 | <div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> |
| 487 | <div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div> |
| 488 | <div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00275">Tensor.cpp:275</a></div></div> |
| 489 | <div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> |
| 490 | </div><!-- fragment --> |
| 491 | </div> |
| 492 | </div> |
| 493 | <a id="a0946a9b1b8cf99591b03ea7f5f7e725f"></a> |
| 494 | <h2 class="memtitle"><span class="permalink"><a href="#a0946a9b1b8cf99591b03ea7f5f7e725f">◆ </a></span>AdditionBroadcastUint8Test()</h2> |
| 495 | |
| 496 | <div class="memitem"> |
| 497 | <div class="memproto"> |
| 498 | <table class="memname"> |
| 499 | <tr> |
| 500 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><uint8_t, 4> AdditionBroadcastUint8Test </td> |
| 501 | <td>(</td> |
| 502 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 503 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 504 | </tr> |
| 505 | <tr> |
| 506 | <td class="paramkey"></td> |
| 507 | <td></td> |
| 508 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 509 | <td class="paramname"><em>memoryManager</em> </td> |
| 510 | </tr> |
| 511 | <tr> |
| 512 | <td></td> |
| 513 | <td>)</td> |
| 514 | <td></td><td></td> |
| 515 | </tr> |
| 516 | </table> |
| 517 | </div><div class="memdoc"> |
| 518 | |
| 519 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00330">330</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 520 | <div class="fragment"><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>  <span class="keywordflow">return</span> AdditionBroadcastTestImpl<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  workloadFactory, memoryManager, 2.f, 0);</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> }</div></div><!-- fragment --> |
| 521 | </div> |
| 522 | </div> |
| 523 | <a id="ae087613cdb8319fbab07d44e6eaf217d"></a> |
| 524 | <h2 class="memtitle"><span class="permalink"><a href="#ae087613cdb8319fbab07d44e6eaf217d">◆ </a></span>AdditionInt16Test()</h2> |
| 525 | |
| 526 | <div class="memitem"> |
| 527 | <div class="memproto"> |
| 528 | <table class="memname"> |
| 529 | <tr> |
| 530 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><int16_t, 4> AdditionInt16Test </td> |
| 531 | <td>(</td> |
| 532 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 533 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 534 | </tr> |
| 535 | <tr> |
| 536 | <td class="paramkey"></td> |
| 537 | <td></td> |
| 538 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 539 | <td class="paramname"><em>memoryManager</em> </td> |
| 540 | </tr> |
| 541 | <tr> |
| 542 | <td></td> |
| 543 | <td>)</td> |
| 544 | <td></td><td></td> |
| 545 | </tr> |
| 546 | </table> |
| 547 | </div><div class="memdoc"> |
| 548 | |
| 549 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00412">412</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 550 | <div class="fragment"><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> {</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape0[] = { 1, 2, 2, 3 };</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape1[] = { 1, 2, 2, 3 };</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> </div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  std::vector<int16_t> input0 =</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>  63, 35, 77, 70, 56, 112, <span class="comment">// 441, 245, 539, 490, 392, 184</span></div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  203, 28, 252, 168, 245, 91 <span class="comment">// 1421, 196, 1764, 1176, 1715, 637</span></div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  };</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span> </div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  std::vector<int16_t> input1 =</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  {</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  21, 7, 175, 231, 175, 210, <span class="comment">// 126, 28, 1204, 1596, 1204, 1449</span></div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  126, 161, 63, 21, 105, 126 <span class="comment">// 861, 1106, 420, 126, 714, 861</span></div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  };</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span> </div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  std::vector<int16_t> output =</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>  84, 42, 252, 301, 231, 322, <span class="comment">// 588, 294, 1764, 2107(clamped), 1617, 2254(clamped)</span></div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  329, 189, 315, 189, 350, 217, <span class="comment">// 2303(clamped), 1323, 2205(clamped), 1323, 2450(clamped), 1519</span></div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  };</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keywordflow">return</span> ElementwiseTestHelper<4, armnn::AdditionQueueDescriptor, armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  workloadFactory,</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  memoryManager,</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  shape0,</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  input0,</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  7.0f,</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  0,</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  shape1,</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  input1,</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  7.0f,</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  0,</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  shape0,</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  output,</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  7.0f,</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  0);</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span> }</div></div><!-- fragment --> |
| 551 | </div> |
| 552 | </div> |
| 553 | <a id="a108165b4957f3790332ae0afedf37ccd"></a> |
| 554 | <h2 class="memtitle"><span class="permalink"><a href="#a108165b4957f3790332ae0afedf37ccd">◆ </a></span>AdditionTest()</h2> |
| 555 | |
| 556 | <div class="memitem"> |
| 557 | <div class="memproto"> |
| 558 | <table class="memname"> |
| 559 | <tr> |
| 560 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float,4> AdditionTest </td> |
| 561 | <td>(</td> |
| 562 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 563 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 564 | </tr> |
| 565 | <tr> |
| 566 | <td class="paramkey"></td> |
| 567 | <td></td> |
| 568 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 569 | <td class="paramname"><em>memoryManager</em> </td> |
| 570 | </tr> |
| 571 | <tr> |
| 572 | <td></td> |
| 573 | <td>)</td> |
| 574 | <td></td><td></td> |
| 575 | </tr> |
| 576 | </table> |
| 577 | </div><div class="memdoc"> |
| 578 | |
| 579 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00021">21</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 580 | <div class="fragment"><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> {</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 2u;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 2u;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 2u;</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = 3u;</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = { batchSize, channels, height, width };</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  std::vector<float> input1 =</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>  0.0f, 2.0f, 1.0f,</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  0.2f, 1.0f, 2.0f,</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> </div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  1.0f, 2.0f, 1.0f,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  0.2f, 1.0f, 2.0f,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  0.0f, 2.0f, 1.0f,</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  4.2f, 1.0f, 2.0f,</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  0.0f, 0.0f, 1.0f,</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  0.2f, 1.0f, 2.0f,</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  };</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  std::vector<float> input2 =</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>  1.0f, 2.0f, 1.0f,</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  0.0f, 1.0f, 2.0f,</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>  1.0f, 2.0f, -2.0f,</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  0.2f, 1.0f, 2.0f,</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>  0.0f, 2.0f, 1.0f,</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  4.2f, 0.0f, -3.0f,</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  0.0f, 0.0f, 1.0f,</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  0.7f, 1.0f, 5.0f,</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> </div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  std::vector<float> output</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>  1.0f, 4.0f, 2.0f,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  0.2f, 2.0f, 4.0f,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  2.0f, 4.0f, -1.0f,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  0.4f, 2.0f, 4.0f,</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  0.0f, 4.0f, 2.0f,</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  8.4f, 1.0f, -1.0f,</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  0.0f, 0.0f, 2.0f,</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  0.9f, 2.0f, 7.0f,</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  };</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">return</span> ElementwiseTestHelper<4, armnn::AdditionQueueDescriptor, armnn::DataType::Float32>(</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  workloadFactory,</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  memoryManager,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  shape,</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  input1,</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  shape,</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  input2,</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  shape,</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  output);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> }</div></div><!-- fragment --> |
| 581 | </div> |
| 582 | </div> |
| 583 | <a id="a4b5e20456506426ba2e4ea9616df978f"></a> |
| 584 | <h2 class="memtitle"><span class="permalink"><a href="#a4b5e20456506426ba2e4ea9616df978f">◆ </a></span>AdditionUint8Test()</h2> |
| 585 | |
| 586 | <div class="memitem"> |
| 587 | <div class="memproto"> |
| 588 | <table class="memname"> |
| 589 | <tr> |
| 590 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><uint8_t, 4> AdditionUint8Test </td> |
| 591 | <td>(</td> |
| 592 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 593 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 594 | </tr> |
| 595 | <tr> |
| 596 | <td class="paramkey"></td> |
| 597 | <td></td> |
| 598 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 599 | <td class="paramname"><em>memoryManager</em> </td> |
| 600 | </tr> |
| 601 | <tr> |
| 602 | <td></td> |
| 603 | <td>)</td> |
| 604 | <td></td><td></td> |
| 605 | </tr> |
| 606 | </table> |
| 607 | </div><div class="memdoc"> |
| 608 | |
| 609 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00370">370</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 610 | <div class="fragment"><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">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape0[] = { 1, 2, 2, 3 };</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape1[] = { 1, 2, 2, 3 };</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>  std::vector<uint8_t> input0(</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  {</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  63, 35, 77, 70, 56, 112, <span class="comment">// 420, 224, 518, 469, 371, 763</span></div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  203, 28, 252, 168, 245, 91 <span class="comment">// 1400, 175, 1743, 1155, 1694, 616</span></div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  });</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> </div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  std::vector<uint8_t> input1(</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>  21, 7, 175, 231, 175, 210, <span class="comment">// 126, 28, 1204, 1596, 1204, 1449</span></div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  126, 161, 63, 21, 105, 126 <span class="comment">// 861, 1106, 420, 126, 714, 861</span></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> </div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  std::vector<uint8_t> output(</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  {</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  81, 39, 249, 255, 228, 255, <span class="comment">// 546, 252, 1722, 2065(clamped), 1575, 2212(clamped)</span></div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  255, 186, 255, 186, 255, 214, <span class="comment">// 2261(clamped), 1281, 2163(clamped), 1281, 2408(clamped), 1477</span></div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  });</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> </div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="keywordflow">return</span> ElementwiseTestHelper<4, armnn::AdditionQueueDescriptor, armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  workloadFactory,</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  memoryManager,</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  shape0,</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  input0,</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  7.0f,</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  3,</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  shape1,</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  input1,</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  7.0f,</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  3,</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  shape0,</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  output,</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  7.0f,</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  3);</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span> }</div></div><!-- fragment --> |
| 611 | </div> |
| 612 | </div> |
| 613 | <a id="a557c464592942eb098f63aa0f91e4d24"></a> |
| 614 | <h2 class="memtitle"><span class="permalink"><a href="#a557c464592942eb098f63aa0f91e4d24">◆ </a></span>CompareAdditionTest()</h2> |
| 615 | |
| 616 | <div class="memitem"> |
| 617 | <div class="memproto"> |
| 618 | <table class="memname"> |
| 619 | <tr> |
| 620 | <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float,4> CompareAdditionTest </td> |
| 621 | <td>(</td> |
| 622 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 623 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 624 | </tr> |
| 625 | <tr> |
| 626 | <td class="paramkey"></td> |
| 627 | <td></td> |
| 628 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> |
| 629 | <td class="paramname"><em>memoryManager</em>, </td> |
| 630 | </tr> |
| 631 | <tr> |
| 632 | <td class="paramkey"></td> |
| 633 | <td></td> |
| 634 | <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 635 | <td class="paramname"><em>refWorkloadFactory</em> </td> |
| 636 | </tr> |
| 637 | <tr> |
| 638 | <td></td> |
| 639 | <td>)</td> |
| 640 | <td></td><td></td> |
| 641 | </tr> |
| 642 | </table> |
| 643 | </div><div class="memdoc"> |
| 644 | |
| 645 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00561">561</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 646 | |
| 647 | <p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01105">IWorkloadFactory::CreateAddition()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, and <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>.</p> |
| 648 | <div class="fragment"><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>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 4;</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 1;</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 2;</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = 3;</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span> </div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo1, inputTensorInfo2;</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span> </div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = {batchSize, channels, height, width};</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span> </div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  inputTensorInfo1 = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  inputTensorInfo2 = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span> </div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="keyword">auto</span> input1 = MakeRandomTensor<float, 4>(inputTensorInfo1, 1232);</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  <span class="keyword">auto</span> input2 = MakeRandomTensor<float, 4>(inputTensorInfo2, 456);</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span> </div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float,4></a> ret(outputTensorInfo);</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>  std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo1);</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle2 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo2);</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span> </div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle1Ref = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo1);</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle2Ref = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo2);</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span> </div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a> data;</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get());</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get());</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</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>  <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a> refData = data;</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> refInfo = info;</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  SetWorkloadInput(refData, refInfo, 0, inputTensorInfo1, inputHandle1Ref.get());</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  SetWorkloadInput(refData, refInfo, 1, inputTensorInfo2, inputHandle2Ref.get());</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get());</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>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(data, info);</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(refData, refInfo);</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>  inputHandle1->Allocate();</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  inputHandle2->Allocate();</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  outputHandle->Allocate();</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  inputHandle1Ref->Allocate();</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  inputHandle2Ref->Allocate();</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  outputHandleRef->Allocate();</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span> </div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle1.get(), &input1[0][0][0][0]);</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle2.get(), &input2[0][0][0][0]);</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle1Ref.get(), &input1[0][0][0][0]);</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle2Ref.get(), &input2[0][0][0][0]);</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span> </div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  workload->PostAllocationConfigure();</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  workload->Execute();</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  workloadRef->PostAllocationConfigure();</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  workloadRef->Execute();</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span> </div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret.outputExpected[0][0][0][0], outputHandleRef.get());</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>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div> |
| 649 | <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> |
| 650 | <div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> |
| 651 | <div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> |
| 652 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0</div></div> |
| 653 | <div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> |
| 654 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateAddition(const AdditionQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01105">WorkloadFactory.cpp:1105</a></div></div> |
| 655 | <div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> |
| 656 | <div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> |
| 657 | <div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div> |
| 658 | <div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> |
| 659 | </div><!-- fragment --> |
| 660 | </div> |
| 661 | </div> |
| 662 | <a id="a5f3caae0b1541a904067544dd37655f0"></a> |
| 663 | <h2 class="memtitle"><span class="permalink"><a href="#a5f3caae0b1541a904067544dd37655f0">◆ </a></span>CreateWorkload< armnn::AdditionQueueDescriptor >()</h2> |
| 664 | |
| 665 | <div class="memitem"> |
| 666 | <div class="memproto"> |
| 667 | <table class="memname"> |
| 668 | <tr> |
| 669 | <td class="memname">std::unique_ptr<<a class="el" href="classarmnn_1_1_i_workload.xhtml">armnn::IWorkload</a>> <a class="el" href="_elementwise_unary_test_impl_8hpp.xhtml#aa50938ed8f91e09acd4af904dcf5543a">CreateWorkload</a>< <a class="el" href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a> > </td> |
| 670 | <td>(</td> |
| 671 | <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> |
| 672 | <td class="paramname"><em>workloadFactory</em>, </td> |
| 673 | </tr> |
| 674 | <tr> |
| 675 | <td class="paramkey"></td> |
| 676 | <td></td> |
| 677 | <td class="paramtype">const <a class="el" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> & </td> |
| 678 | <td class="paramname"><em>info</em>, </td> |
| 679 | </tr> |
| 680 | <tr> |
| 681 | <td class="paramkey"></td> |
| 682 | <td></td> |
| 683 | <td class="paramtype">const <a class="el" href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a> & </td> |
| 684 | <td class="paramname"><em>descriptor</em> </td> |
| 685 | </tr> |
| 686 | <tr> |
| 687 | <td></td> |
| 688 | <td>)</td> |
| 689 | <td></td><td></td> |
| 690 | </tr> |
| 691 | </table> |
| 692 | </div><div class="memdoc"> |
| 693 | |
| 694 | <p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.xhtml#l00013">13</a> of file <a class="el" href="_addition_test_impl_8cpp_source.xhtml">AdditionTestImpl.cpp</a>.</p> |
| 695 | <div class="fragment"><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> {</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="keywordflow">return</span> workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(descriptor, info);</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> }</div><div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateAddition(const AdditionQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01105">WorkloadFactory.cpp:1105</a></div></div> |
| 696 | </div><!-- fragment --> |
| 697 | </div> |
| 698 | </div> |
| 699 | </div><!-- contents --> |
| 700 | </div><!-- doc-content --> |
| 701 | <!-- start footer part --> |
| 702 | <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> |
| 703 | <ul> |
| 704 | <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.xhtml">backendsCommon</a></li><li class="navelem"><a class="el" href="dir_28bfe507f7e135bdae07c2a6b7f66696.xhtml">test</a></li><li class="navelem"><a class="el" href="dir_99a30439342d160875b21dac3498ad7f.xhtml">layerTests</a></li><li class="navelem"><a class="el" href="_addition_test_impl_8cpp.xhtml">AdditionTestImpl.cpp</a></li> |
| 705 | <li class="footer">Generated on Fri Mar 13 2020 16:09:14 for ArmNN by |
| 706 | <a href="http://www.doxygen.org/index.html"> |
| 707 | <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> |
| 708 | </ul> |
| 709 | </div> |
| 710 | </body> |
| 711 | </html> |