diff options
Diffstat (limited to '21.02/_cl_fallback_tests_8cpp.xhtml')
| -rw-r--r-- | 21.02/_cl_fallback_tests_8cpp.xhtml | 375 |
1 files changed, 375 insertions, 0 deletions
diff --git a/21.02/_cl_fallback_tests_8cpp.xhtml b/21.02/_cl_fallback_tests_8cpp.xhtml new file mode 100644 index 0000000000..2213df9c66 --- /dev/null +++ b/21.02/_cl_fallback_tests_8cpp.xhtml @@ -0,0 +1,375 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/backends/cl/test/ClFallbackTests.cpp File Reference</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">21.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_cl_fallback_tests_8cpp.xhtml','');}); +</script> +<div id="doc-content"> +<!-- window showing the filter options --> +<div id="MSearchSelectWindow" + onmouseover="return searchBox.OnSearchSelectShow()" + onmouseout="return searchBox.OnSearchSelectHide()" + onkeydown="return searchBox.OnSearchSelectKey(event)"> +</div> + +<!-- iframe showing the search results (closed by default) --> +<div id="MSearchResultsWindow"> +<iframe src="javascript:void(0)" frameborder="0" + name="MSearchResults" id="MSearchResults"> +</iframe> +</div> + +<div class="header"> + <div class="summary"> +<a href="#func-members">Functions</a> </div> + <div class="headertitle"> +<div class="title">ClFallbackTests.cpp File Reference</div> </div> +</div><!--header--> +<div class="contents"> +<div class="textblock"><code>#include <<a class="el" href="_common_test_utils_8hpp_source.xhtml">backendsCommon/test/CommonTestUtils.hpp</a>></code><br /> +<code>#include <<a class="el" href="_graph_utils_8hpp_source.xhtml">test/GraphUtils.hpp</a>></code><br /> +<code>#include <boost/test/unit_test.hpp></code><br /> +</div> +<p><a href="_cl_fallback_tests_8cpp_source.xhtml">Go to the source code of this file.</a></p> +<table class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> +Functions</h2></td></tr> +<tr class="memitem:af63c7e2def59e048cf7df08ebef3a1f0"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_cl_fallback_tests_8cpp.xhtml#af63c7e2def59e048cf7df08ebef3a1f0">BOOST_AUTO_TEST_CASE</a> (ClImportEnabledFallbackToNeon)</td></tr> +<tr class="separator:af63c7e2def59e048cf7df08ebef3a1f0"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a80907255c8ac09ae9b200c38396249b8"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_cl_fallback_tests_8cpp.xhtml#a80907255c8ac09ae9b200c38396249b8">BOOST_AUTO_TEST_CASE</a> (ClImportDisabledFallbackToNeon)</td></tr> +<tr class="separator:a80907255c8ac09ae9b200c38396249b8"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ade94e5ddaebf77f2affcff5f745e05a1"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_cl_fallback_tests_8cpp.xhtml#ade94e5ddaebf77f2affcff5f745e05a1">BOOST_AUTO_TEST_CASE</a> (ClImportEnabledFallbackSubgraphToNeon)</td></tr> +<tr class="separator:ade94e5ddaebf77f2affcff5f745e05a1"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a818d7c05921cbc3c9aa0c16c8f95a0ca"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_cl_fallback_tests_8cpp.xhtml#a818d7c05921cbc3c9aa0c16c8f95a0ca">BOOST_AUTO_TEST_CASE</a> (ClImportDisableFallbackSubgraphToNeon)</td></tr> +<tr class="separator:a818d7c05921cbc3c9aa0c16c8f95a0ca"><td class="memSeparator" colspan="2"> </td></tr> +</table> +<h2 class="groupheader">Function Documentation</h2> +<a id="af63c7e2def59e048cf7df08ebef3a1f0"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af63c7e2def59e048cf7df08ebef3a1f0">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[1/4]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">ClImportEnabledFallbackToNeon </td> + <td class="paramname"></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml#l00014">14</a> of file <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml">ClFallbackTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">IConnectableLayer::BackendSelectionHint()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00068">CheckOrder()</a>, <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">IOutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::CpuAcc</a>, <a class="el" href="_runtime_8cpp_source.xhtml#l00037">IRuntime::Create()</a>, <a class="el" href="_network_8cpp_source.xhtml#l00510">INetwork::Create()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00269">Layer::GetBackendId()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00022">GetFirstLayerWithName()</a>, <a class="el" href="_test_utils_8cpp_source.xhtml#l00025">armnn::GetGraphForTesting()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">IConnectableLayer::GetInputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00489">ProfilerManager::GetInstance()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">IConnectableLayer::GetOutputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00501">ProfilerManager::GetProfiler()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00265">Layer::GetType()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::GpuAcc</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="_i_network_8hpp_source.xhtml#l00165">OptimizerOptions::m_ImportEnabled</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::MemCopy</a>, <a class="el" href="_network_8cpp_source.xhtml#l01502">armnn::Optimize()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00522">IProfiler::Print()</a>, and <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">IOutputSlot::SetTensorInfo()</a>.</p> +<div class="fragment"><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> {</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(options));</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>());</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> </div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input0 = net->AddInputLayer(0, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input1 = net->AddInputLayer(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input2 = net->AddInputLayer(2, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* add = net->AddAdditionLayer(<span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* sub = net->AddSubtractionLayer(<span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = net->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> </div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  std::vector<BackendId> backends = { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">Compute::GpuAcc</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> };</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="comment">// Use BackendSelectionHint to specify CpuAcc for Subtraction layer</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">BackendSelectionHint</a>(backends[1]);</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>  <span class="comment">// optimize the network</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a> optOptions;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  optOptions.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a05c1bba6ba3ecc1339d4c4c10c0d8890">m_ImportEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*net, backends, runtime->GetDeviceSpec(), optOptions);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = <a class="code" href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">GetGraphForTesting</a>(optNet.get());</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer0 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer1 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer2 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer3 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer4 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ add (0) -> sub (1) ]"</span>);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer5 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer6 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// Checks order is valid.</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer0, layer1));</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer1, layer2));</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer2, layer3));</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer3, layer4));</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer4, layer5));</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer5, layer6));</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="comment">// Use memory import between backends</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  BOOST_TEST((layer4-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> </div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="comment">// Correctly use backend hint</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  BOOST_TEST((layer5-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> ));</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="comment">// Load it into the runtime. It should pass.</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  std::string ignoredErrorMessage;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="structarmnn_1_1_i_network_properties.xhtml">INetworkProperties</a> networkProperties(<span class="keyword">true</span>, <span class="keyword">true</span>);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  runtime->LoadNetwork(netId, std::move(optNet), ignoredErrorMessage, networkProperties);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="comment">// Creates structures for input & output</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  std::vector<float> inputData0</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  {</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f, 6.0f</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  };</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  std::vector<float> inputData1</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  {</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  0.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  };</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  std::vector<float> inputData2</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  {</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  12.0f, 11.0f, 10.0f, 9.0f, 8.0f, 7.0f, 6.0f, 5.0f, 4.0f, 3.0f, 2.0f, 1.0f</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  };</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>  std::vector<float> outputData(12);</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> expectedOutput</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>  11.0f, 9.0f, 7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f, -7.0f, -9.0f, -11.0f</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  };</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  {</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  { 0, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 0), inputData0.data()) },</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  { 1, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 1), inputData1.data()) },</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  { 2, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 2), inputData2.data()) }</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  };</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  {</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  { 0,<a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(runtime->GetOutputTensorInfo(netId, 0), outputData.data()) }</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>  runtime->GetProfiler(netId)->EnableProfiling(<span class="keyword">true</span>);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="comment">// Do the inference</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  runtime->EnqueueWorkload(netId, inputTensors, outputTensors);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="comment">// Retrieve the Profiler.Print() output to get the workload execution</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <a class="code" href="classarmnn_1_1_profiler_manager.xhtml">ProfilerManager</a>& profilerManager = <a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a>();</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  std::stringstream ss;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  profilerManager.<a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">GetProfiler</a>()-><a class="code" href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">Print</a>(ss);;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  std::string dump = ss.str();</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="comment">// Executed Subtraction using CpuAcc</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  std::size_t found = dump.find(<span class="stringliteral">"NeonSubtractionWorkload_Execute"</span>);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="comment">// Contain CopyMemGeneric</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  found = dump.find(<span class="stringliteral">"CopyMemGeneric"</span>);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  BOOST_TEST(found != std::string::npos);</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>  <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  BOOST_TEST(outputData == expectedOutput);</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> }</div><div class="ttc" id="classarmnn_1_1_i_runtime_xhtml_ad44ecd3700748dc30dc4bbe34ba5bde7"><div class="ttname"><a href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a></div><div class="ttdeci">static IRuntimePtr Create(const CreationOptions &options)</div><div class="ttdef"><b>Definition:</b> <a href="_runtime_8cpp_source.xhtml#l00037">Runtime.cpp:37</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00062">INetwork.hpp:62</a></div></div> +<div class="ttc" id="_graph_utils_8cpp_xhtml_a5f17e02e0054dac0a691685a0464ed36"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a></div><div class="ttdeci">armnn::Layer * GetFirstLayerWithName(armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00022">GraphUtils.cpp:22</a></div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a93857080c2523bf3395e7aa7e6024d5c"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a></div><div class="ttdeci">static ProfilerManager & GetInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00489">Profiling.cpp:489</a></div></div> +<div class="ttc" id="_graph_utils_8cpp_xhtml_a21d963c71be62057ed99b5007e7bbbfd"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a></div><div class="ttdeci">bool CheckOrder(const armnn::Graph &graph, const armnn::Layer *first, const armnn::Layer *second)</div><div class="ttdoc">Checks that first comes before second in the order. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00068">GraphUtils.cpp:68</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a833170f92e96b3ef414b6cf6e5720d2b"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">armnn::IConnectableLayer::BackendSelectionHint</a></div><div class="ttdeci">virtual void BackendSelectionHint(Optional< BackendId > backend)=0</div><div class="ttdoc">Provide a hint for the optimizer as to which backend to prefer for this layer. </div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr< IRuntime, void(*)(IRuntime *runtime)> IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00026">IRuntime.hpp:26</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_profiler_xhtml_a038bb767bbc6abc0ee0d9b509616b896"><div class="ttname"><a href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">armnn::IProfiler::Print</a></div><div class="ttdeci">void Print(std::ostream &outStream) const</div><div class="ttdoc">Print stats for events in JSON Format to the given output stream. </div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00522">Profiling.cpp:522</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00340">Tensor.hpp:340</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00020">IRuntime.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</div></div> +<div class="ttc" id="structarmnn_1_1_i_network_properties_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.xhtml">armnn::INetworkProperties</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00028">IRuntime.hpp:28</a></div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a3756986bc88b9b212d3f983c70c5c129"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">armnn::ProfilerManager::GetProfiler</a></div><div class="ttdeci">IProfiler * GetProfiler()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00501">Profiling.cpp:501</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00306">Tensor.hpp:306</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00174">INetwork.hpp:174</a></div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml">armnn::ProfilerManager</a></div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00091">Profiling.hpp:91</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml">armnn::OptimizerOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00110">INetwork.hpp:110</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_afdb1d37740e7a083b625d669588b6a0e"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">armnn::Layer::GetBackendId</a></div><div class="ttdeci">const BackendId & GetBackendId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00269">Layer.hpp:269</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml_a05c1bba6ba3ecc1339d4c4c10c0d8890"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a05c1bba6ba3ecc1339d4c4c10c0d8890">armnn::OptimizerOptions::m_ImportEnabled</a></div><div class="ttdeci">bool m_ImportEnabled</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00165">INetwork.hpp:165</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00043">IRuntime.hpp:43</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a6a2659750d6161b693d0e51616791959"><div class="ttname"><a href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">armnn::GetGraphForTesting</a></div><div class="ttdeci">Graph & GetGraphForTesting(IOptimizedNetwork *optNet)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00025">TestUtils.cpp:25</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a></div><div class="ttdoc">CPU Execution: NEON: ArmCompute. </div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0</div><div class="ttdoc">Get the const output slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00510">Network.cpp:510</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a80907255c8ac09ae9b200c38396249b8"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a80907255c8ac09ae9b200c38396249b8">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[2/4]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">ClImportDisabledFallbackToNeon </td> + <td class="paramname"></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml#l00140">140</a> of file <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml">ClFallbackTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">IConnectableLayer::BackendSelectionHint()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00068">CheckOrder()</a>, <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">IOutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::CpuAcc</a>, <a class="el" href="_runtime_8cpp_source.xhtml#l00037">IRuntime::Create()</a>, <a class="el" href="_network_8cpp_source.xhtml#l00510">INetwork::Create()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00269">Layer::GetBackendId()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00022">GetFirstLayerWithName()</a>, <a class="el" href="_test_utils_8cpp_source.xhtml#l00025">armnn::GetGraphForTesting()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">IConnectableLayer::GetInputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00489">ProfilerManager::GetInstance()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">IConnectableLayer::GetOutputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00501">ProfilerManager::GetProfiler()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00265">Layer::GetType()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::GpuAcc</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::MemCopy</a>, <a class="el" href="_network_8cpp_source.xhtml#l01502">armnn::Optimize()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00522">IProfiler::Print()</a>, and <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">IOutputSlot::SetTensorInfo()</a>.</p> +<div class="fragment"><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> {</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> </div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(options));</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> </div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>());</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> </div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input0 = net->AddInputLayer(0, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input1 = net->AddInputLayer(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input2 = net->AddInputLayer(2, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* add = net->AddAdditionLayer(<span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* sub = net->AddSubtractionLayer(<span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = net->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  std::vector<BackendId> backends = { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">Compute::GpuAcc</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> };</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="comment">// Use BackendSelectionHint to specify CpuAcc for Subtraction layer</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">BackendSelectionHint</a>(backends[1]);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="comment">// optimize the network</span></div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a> optOptions;</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*net, backends, runtime->GetDeviceSpec(), optOptions);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = <a class="code" href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">GetGraphForTesting</a>(optNet.get());</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer0 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer1 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer2 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer3 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer4 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ add (0) -> sub (1) ]"</span>);</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer5 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer6 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="comment">// Checks order is valid.</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer0, layer1));</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer1, layer2));</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer2, layer3));</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer3, layer4));</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer4, layer5));</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer5, layer6));</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// Use memory import between backends</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  BOOST_TEST((layer4-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="comment">// Correctly use backend hint</span></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  BOOST_TEST((layer5-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> ));</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>  <span class="comment">// Load it into the runtime. It should pass.</span></div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  runtime->LoadNetwork(netId, std::move(optNet));</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> </div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="comment">// Creates structures for input & output</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  std::vector<float> inputData0</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  {</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f, 6.0f</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>  std::vector<float> inputData1</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  {</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  0.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  };</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  std::vector<float> inputData2</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  {</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  12.0f, 11.0f, 10.0f, 9.0f, 8.0f, 7.0f, 6.0f, 5.0f, 4.0f, 3.0f, 2.0f, 1.0f</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  };</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> </div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  std::vector<float> outputData(12);</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> </div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  std::vector<float> expectedOutput</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  {</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  11.0f, 9.0f, 7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f, -7.0f, -9.0f, -11.0f</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> </div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  {</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  { 0, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 0), inputData0.data()) },</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  { 1, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 1), inputData1.data()) },</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  { 2, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 2), inputData2.data()) }</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  };</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors</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>  { 0,<a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(runtime->GetOutputTensorInfo(netId, 0), outputData.data()) }</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  };</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  runtime->GetProfiler(netId)->EnableProfiling(<span class="keyword">true</span>);</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="comment">// Do the inference</span></div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  runtime->EnqueueWorkload(netId, inputTensors, outputTensors);</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <span class="comment">// Retrieve the Profiler.Print() output to get the workload execution</span></div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <a class="code" href="classarmnn_1_1_profiler_manager.xhtml">ProfilerManager</a>& profilerManager = <a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a>();</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  std::stringstream ss;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  profilerManager.<a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">GetProfiler</a>()-><a class="code" href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">Print</a>(ss);;</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  std::string dump = ss.str();</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="comment">// Executed Subtraction using CpuAcc</span></div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  std::size_t found = dump.find(<span class="stringliteral">"NeonSubtractionWorkload_Execute"</span>);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> </div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="comment">// Contain CopyMemGeneric</span></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  found = dump.find(<span class="stringliteral">"CopyMemGeneric"</span>);</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> </div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  BOOST_TEST(outputData == expectedOutput);</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> }</div><div class="ttc" id="classarmnn_1_1_i_runtime_xhtml_ad44ecd3700748dc30dc4bbe34ba5bde7"><div class="ttname"><a href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a></div><div class="ttdeci">static IRuntimePtr Create(const CreationOptions &options)</div><div class="ttdef"><b>Definition:</b> <a href="_runtime_8cpp_source.xhtml#l00037">Runtime.cpp:37</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00062">INetwork.hpp:62</a></div></div> +<div class="ttc" id="_graph_utils_8cpp_xhtml_a5f17e02e0054dac0a691685a0464ed36"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a></div><div class="ttdeci">armnn::Layer * GetFirstLayerWithName(armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00022">GraphUtils.cpp:22</a></div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a93857080c2523bf3395e7aa7e6024d5c"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a></div><div class="ttdeci">static ProfilerManager & GetInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00489">Profiling.cpp:489</a></div></div> +<div class="ttc" id="_graph_utils_8cpp_xhtml_a21d963c71be62057ed99b5007e7bbbfd"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a></div><div class="ttdeci">bool CheckOrder(const armnn::Graph &graph, const armnn::Layer *first, const armnn::Layer *second)</div><div class="ttdoc">Checks that first comes before second in the order. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00068">GraphUtils.cpp:68</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a833170f92e96b3ef414b6cf6e5720d2b"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">armnn::IConnectableLayer::BackendSelectionHint</a></div><div class="ttdeci">virtual void BackendSelectionHint(Optional< BackendId > backend)=0</div><div class="ttdoc">Provide a hint for the optimizer as to which backend to prefer for this layer. </div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr< IRuntime, void(*)(IRuntime *runtime)> IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00026">IRuntime.hpp:26</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_profiler_xhtml_a038bb767bbc6abc0ee0d9b509616b896"><div class="ttname"><a href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">armnn::IProfiler::Print</a></div><div class="ttdeci">void Print(std::ostream &outStream) const</div><div class="ttdoc">Print stats for events in JSON Format to the given output stream. </div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00522">Profiling.cpp:522</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00340">Tensor.hpp:340</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00020">IRuntime.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a3756986bc88b9b212d3f983c70c5c129"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">armnn::ProfilerManager::GetProfiler</a></div><div class="ttdeci">IProfiler * GetProfiler()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00501">Profiling.cpp:501</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00306">Tensor.hpp:306</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00174">INetwork.hpp:174</a></div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml">armnn::ProfilerManager</a></div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00091">Profiling.hpp:91</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml">armnn::OptimizerOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00110">INetwork.hpp:110</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_afdb1d37740e7a083b625d669588b6a0e"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">armnn::Layer::GetBackendId</a></div><div class="ttdeci">const BackendId & GetBackendId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00269">Layer.hpp:269</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00043">IRuntime.hpp:43</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a6a2659750d6161b693d0e51616791959"><div class="ttname"><a href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">armnn::GetGraphForTesting</a></div><div class="ttdeci">Graph & GetGraphForTesting(IOptimizedNetwork *optNet)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00025">TestUtils.cpp:25</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a></div><div class="ttdoc">CPU Execution: NEON: ArmCompute. </div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0</div><div class="ttdoc">Get the const output slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00510">Network.cpp:510</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="ade94e5ddaebf77f2affcff5f745e05a1"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ade94e5ddaebf77f2affcff5f745e05a1">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[3/4]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">ClImportEnabledFallbackSubgraphToNeon </td> + <td class="paramname"></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml#l00262">262</a> of file <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml">ClFallbackTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">IConnectableLayer::BackendSelectionHint()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00068">CheckOrder()</a>, <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">IOutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::CpuAcc</a>, <a class="el" href="_runtime_8cpp_source.xhtml#l00037">IRuntime::Create()</a>, <a class="el" href="_network_8cpp_source.xhtml#l00510">INetwork::Create()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00269">Layer::GetBackendId()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00022">GetFirstLayerWithName()</a>, <a class="el" href="_test_utils_8cpp_source.xhtml#l00025">armnn::GetGraphForTesting()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">IConnectableLayer::GetInputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00489">ProfilerManager::GetInstance()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">IConnectableLayer::GetOutputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00501">ProfilerManager::GetProfiler()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00265">Layer::GetType()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::GpuAcc</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="_i_network_8hpp_source.xhtml#l00165">OptimizerOptions::m_ImportEnabled</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::MemCopy</a>, <a class="el" href="_network_8cpp_source.xhtml#l01502">armnn::Optimize()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00522">IProfiler::Print()</a>, and <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">IOutputSlot::SetTensorInfo()</a>.</p> +<div class="fragment"><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> {</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> </div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(options));</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> </div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>());</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">Pooling2dDescriptor</a> desc;</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> </div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input0 = net->AddInputLayer(0, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input1 = net->AddInputLayer(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input2 = net->AddInputLayer(2, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* add = net->AddAdditionLayer(<span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* sub = net->AddSubtractionLayer(<span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* pooling = net->AddPooling2dLayer(desc, <span class="stringliteral">"pooling"</span>);</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = net->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> </div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> </div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> poolingInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> </div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(poolingInfo);</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>  std::vector<BackendId> backends = { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">Compute::GpuAcc</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> };</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="comment">// Use BackendSelectionHint to specify CpuAcc for Subtraction layer</span></div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">BackendSelectionHint</a>(backends[1]);</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> </div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="comment">// optimize the network</span></div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a> optOptions;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  optOptions.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a05c1bba6ba3ecc1339d4c4c10c0d8890">m_ImportEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*net, backends, runtime->GetDeviceSpec(), optOptions);</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> </div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = <a class="code" href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">GetGraphForTesting</a>(optNet.get());</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> </div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer0 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer1 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer2 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer3 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer4 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ add (0) -> sub (1) ]"</span>);</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer5 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer6 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ sub (0) -> pooling (0) ]"</span>);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer7 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"pooling"</span>);</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer8 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> </div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="comment">// Checks order is valid.</span></div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer0, layer1));</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer1, layer2));</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer2, layer3));</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer3, layer4));</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer4, layer5));</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer5, layer6));</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer6, layer7));</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer7, layer8));</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="comment">// Use memory import between backends</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  BOOST_TEST((layer4-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  BOOST_TEST((layer6-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> </div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="comment">// Correctly use backend hint</span></div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  BOOST_TEST((layer5-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> ));</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> </div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="comment">// Load it into the runtime. It should pass.</span></div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  std::string ignoredErrorMessage;</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <a class="code" href="structarmnn_1_1_i_network_properties.xhtml">INetworkProperties</a> networkProperties(<span class="keyword">true</span>, <span class="keyword">true</span>);</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> </div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  runtime->LoadNetwork(netId, std::move(optNet), ignoredErrorMessage, networkProperties);</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span> </div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="comment">// Creates structures for input & output</span></div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  std::vector<float> inputData0</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  {</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f, 6.0f</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  };</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  std::vector<float> inputData1</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  {</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  0.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  };</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  std::vector<float> inputData2</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  {</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  12.0f, 11.0f, 10.0f, 9.0f, 8.0f, 7.0f, 6.0f, 5.0f, 4.0f, 3.0f, 2.0f, 1.0f</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  };</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> </div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  std::vector<float> outputData(2);</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span> </div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  std::vector<float> expectedOutput{ 11.0f, -1.0f };</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span> </div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  {</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  { 0, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 0), inputData0.data()) },</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  { 1, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 1), inputData1.data()) },</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  { 2, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 2), inputData2.data()) }</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  };</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  {</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  { 0,<a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(runtime->GetOutputTensorInfo(netId, 0), outputData.data()) }</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  };</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> </div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  runtime->GetProfiler(netId)->EnableProfiling(<span class="keyword">true</span>);</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> </div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="comment">// Do the inference</span></div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  runtime->EnqueueWorkload(netId, inputTensors, outputTensors);</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="comment">// Retrieve the Profiler.Print() output to get the workload execution</span></div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <a class="code" href="classarmnn_1_1_profiler_manager.xhtml">ProfilerManager</a>& profilerManager = <a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a>();</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  std::stringstream ss;</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  profilerManager.<a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">GetProfiler</a>()-><a class="code" href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">Print</a>(ss);;</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  std::string dump = ss.str();</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> </div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="comment">// Executed Subtraction using CpuAcc</span></div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  std::size_t found = dump.find(<span class="stringliteral">"NeonSubtractionWorkload_Execute"</span>);</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> </div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="comment">// Correctly switch back to GpuAcc</span></div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  found = dump.find(<span class="stringliteral">"ClPooling2dWorkload_Execute"</span>);</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> </div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="comment">// Contain CopyMemGeneric</span></div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  found = dump.find(<span class="stringliteral">"CopyMemGeneric"</span>);</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> </div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  BOOST_TEST(outputData == expectedOutput);</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span> }</div><div class="ttc" id="classarmnn_1_1_i_runtime_xhtml_ad44ecd3700748dc30dc4bbe34ba5bde7"><div class="ttname"><a href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a></div><div class="ttdeci">static IRuntimePtr Create(const CreationOptions &options)</div><div class="ttdef"><b>Definition:</b> <a href="_runtime_8cpp_source.xhtml#l00037">Runtime.cpp:37</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00062">INetwork.hpp:62</a></div></div> +<div class="ttc" id="_graph_utils_8cpp_xhtml_a5f17e02e0054dac0a691685a0464ed36"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a></div><div class="ttdeci">armnn::Layer * GetFirstLayerWithName(armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00022">GraphUtils.cpp:22</a></div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a93857080c2523bf3395e7aa7e6024d5c"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a></div><div class="ttdeci">static ProfilerManager & GetInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00489">Profiling.cpp:489</a></div></div> +<div class="ttc" id="_graph_utils_8cpp_xhtml_a21d963c71be62057ed99b5007e7bbbfd"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a></div><div class="ttdeci">bool CheckOrder(const armnn::Graph &graph, const armnn::Layer *first, const armnn::Layer *second)</div><div class="ttdoc">Checks that first comes before second in the order. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00068">GraphUtils.cpp:68</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a833170f92e96b3ef414b6cf6e5720d2b"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">armnn::IConnectableLayer::BackendSelectionHint</a></div><div class="ttdeci">virtual void BackendSelectionHint(Optional< BackendId > backend)=0</div><div class="ttdoc">Provide a hint for the optimizer as to which backend to prefer for this layer. </div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr< IRuntime, void(*)(IRuntime *runtime)> IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00026">IRuntime.hpp:26</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_profiler_xhtml_a038bb767bbc6abc0ee0d9b509616b896"><div class="ttname"><a href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">armnn::IProfiler::Print</a></div><div class="ttdeci">void Print(std::ostream &outStream) const</div><div class="ttdoc">Print stats for events in JSON Format to the given output stream. </div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00522">Profiling.cpp:522</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00340">Tensor.hpp:340</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00020">IRuntime.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</div></div> +<div class="ttc" id="structarmnn_1_1_i_network_properties_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.xhtml">armnn::INetworkProperties</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00028">IRuntime.hpp:28</a></div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a3756986bc88b9b212d3f983c70c5c129"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">armnn::ProfilerManager::GetProfiler</a></div><div class="ttdeci">IProfiler * GetProfiler()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00501">Profiling.cpp:501</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00306">Tensor.hpp:306</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00174">INetwork.hpp:174</a></div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml">armnn::ProfilerManager</a></div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00091">Profiling.hpp:91</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml">armnn::OptimizerOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00110">INetwork.hpp:110</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_afdb1d37740e7a083b625d669588b6a0e"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">armnn::Layer::GetBackendId</a></div><div class="ttdeci">const BackendId & GetBackendId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00269">Layer.hpp:269</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml_a05c1bba6ba3ecc1339d4c4c10c0d8890"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a05c1bba6ba3ecc1339d4c4c10c0d8890">armnn::OptimizerOptions::m_ImportEnabled</a></div><div class="ttdeci">bool m_ImportEnabled</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00165">INetwork.hpp:165</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00043">IRuntime.hpp:43</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a6a2659750d6161b693d0e51616791959"><div class="ttname"><a href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">armnn::GetGraphForTesting</a></div><div class="ttdeci">Graph & GetGraphForTesting(IOptimizedNetwork *optNet)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00025">TestUtils.cpp:25</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a></div><div class="ttdoc">CPU Execution: NEON: ArmCompute. </div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0</div><div class="ttdoc">Get the const output slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</div></div> +<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#l00329">Descriptors.hpp:329</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00510">Network.cpp:510</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a818d7c05921cbc3c9aa0c16c8f95a0ca"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a818d7c05921cbc3c9aa0c16c8f95a0ca">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[4/4]</span></h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">BOOST_AUTO_TEST_CASE </td> + <td>(</td> + <td class="paramtype">ClImportDisableFallbackSubgraphToNeon </td> + <td class="paramname"></td><td>)</td> + <td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml#l00400">400</a> of file <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml">ClFallbackTests.cpp</a>.</p> + +<p class="reference">References <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">IConnectableLayer::BackendSelectionHint()</a>, <a class="el" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00068">CheckOrder()</a>, <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">IOutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::CpuAcc</a>, <a class="el" href="_runtime_8cpp_source.xhtml#l00037">IRuntime::Create()</a>, <a class="el" href="_network_8cpp_source.xhtml#l00510">INetwork::Create()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00269">Layer::GetBackendId()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00022">GetFirstLayerWithName()</a>, <a class="el" href="_test_utils_8cpp_source.xhtml#l00025">armnn::GetGraphForTesting()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">IConnectableLayer::GetInputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00489">ProfilerManager::GetInstance()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">IConnectableLayer::GetOutputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00501">ProfilerManager::GetProfiler()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00265">Layer::GetType()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::GpuAcc</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::MemCopy</a>, <a class="el" href="_network_8cpp_source.xhtml#l01502">armnn::Optimize()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00522">IProfiler::Print()</a>, and <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">IOutputSlot::SetTensorInfo()</a>.</p> +<div class="fragment"><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> {</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span> </div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(options));</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span> </div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>());</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> </div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">Pooling2dDescriptor</a> desc;</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> </div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input0 = net->AddInputLayer(0, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input1 = net->AddInputLayer(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input2 = net->AddInputLayer(2, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* add = net->AddAdditionLayer(<span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* sub = net->AddSubtractionLayer(<span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* pooling = net->AddPooling2dLayer(desc, <span class="stringliteral">"pooling"</span>);</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = net->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> </div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> poolingInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</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>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(poolingInfo);</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>  std::vector<BackendId> backends = { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">Compute::GpuAcc</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> };</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <span class="comment">// Use BackendSelectionHint to specify CpuAcc for Subtraction layer</span></div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">BackendSelectionHint</a>(backends[1]);</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span> </div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="comment">// optimize the network</span></div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a> optOptions;</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*net, backends, runtime->GetDeviceSpec(), optOptions);</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span> </div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = <a class="code" href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">GetGraphForTesting</a>(optNet.get());</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span> </div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer0 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer1 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer2 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer3 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer4 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ add (0) -> sub (1) ]"</span>);</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer5 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer6 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ sub (0) -> pooling (0) ]"</span>);</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer7 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"pooling"</span>);</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer8 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="comment">// Checks order is valid.</span></div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer0, layer1));</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer1, layer2));</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer2, layer3));</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer3, layer4));</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer4, layer5));</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer5, layer6));</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer6, layer7));</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer7, layer8));</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span> </div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="comment">// Use memory import between backends</span></div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  BOOST_TEST((layer4-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  BOOST_TEST((layer6-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span> </div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="comment">// Correctly use backend hint</span></div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  BOOST_TEST((layer5-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> ));</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>  <span class="comment">// Load it into the runtime. It should pass.</span></div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  runtime->LoadNetwork(netId, std::move(optNet));</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span> </div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <span class="comment">// Creates structures for input & output</span></div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  std::vector<float> inputData0</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  {</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f, 6.0f</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  };</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  std::vector<float> inputData1</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  {</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  0.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  };</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  std::vector<float> inputData2</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  {</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  12.0f, 11.0f, 10.0f, 9.0f, 8.0f, 7.0f, 6.0f, 5.0f, 4.0f, 3.0f, 2.0f, 1.0f</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  };</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span> </div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  std::vector<float> outputData(2);</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span> </div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  std::vector<float> expectedOutput{ 11.0f, -1.0f };</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>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  {</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  { 0, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 0), inputData0.data()) },</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  { 1, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 1), inputData1.data()) },</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  { 2, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 2), inputData2.data()) }</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  };</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors</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>  { 0,<a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(runtime->GetOutputTensorInfo(netId, 0), outputData.data()) }</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  };</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span> </div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  runtime->GetProfiler(netId)->EnableProfiling(<span class="keyword">true</span>);</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span> </div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <span class="comment">// Do the inference</span></div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  runtime->EnqueueWorkload(netId, inputTensors, outputTensors);</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span> </div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <span class="comment">// Retrieve the Profiler.Print() output to get the workload execution</span></div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  <a class="code" href="classarmnn_1_1_profiler_manager.xhtml">ProfilerManager</a>& profilerManager = <a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a>();</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  std::stringstream ss;</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  profilerManager.<a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">GetProfiler</a>()-><a class="code" href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">Print</a>(ss);;</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  std::string dump = ss.str();</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>  <span class="comment">// Executed Subtraction using CpuAcc</span></div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  std::size_t found = dump.find(<span class="stringliteral">"NeonSubtractionWorkload_Execute"</span>);</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span> </div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <span class="comment">// Correctly switch back to GpuAcc</span></div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  found = dump.find(<span class="stringliteral">"ClPooling2dWorkload_Execute"</span>);</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  BOOST_TEST(found != std::string::npos);</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>  <span class="comment">// Contain CopyMemGeneric</span></div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  found = dump.find(<span class="stringliteral">"CopyMemGeneric"</span>);</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  BOOST_TEST(found != std::string::npos);</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>  <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  BOOST_TEST(outputData == expectedOutput);</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span> }</div><div class="ttc" id="classarmnn_1_1_i_runtime_xhtml_ad44ecd3700748dc30dc4bbe34ba5bde7"><div class="ttname"><a href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a></div><div class="ttdeci">static IRuntimePtr Create(const CreationOptions &options)</div><div class="ttdef"><b>Definition:</b> <a href="_runtime_8cpp_source.xhtml#l00037">Runtime.cpp:37</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00062">INetwork.hpp:62</a></div></div> +<div class="ttc" id="_graph_utils_8cpp_xhtml_a5f17e02e0054dac0a691685a0464ed36"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a></div><div class="ttdeci">armnn::Layer * GetFirstLayerWithName(armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00022">GraphUtils.cpp:22</a></div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a93857080c2523bf3395e7aa7e6024d5c"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a></div><div class="ttdeci">static ProfilerManager & GetInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00489">Profiling.cpp:489</a></div></div> +<div class="ttc" id="_graph_utils_8cpp_xhtml_a21d963c71be62057ed99b5007e7bbbfd"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a></div><div class="ttdeci">bool CheckOrder(const armnn::Graph &graph, const armnn::Layer *first, const armnn::Layer *second)</div><div class="ttdoc">Checks that first comes before second in the order. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00068">GraphUtils.cpp:68</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a833170f92e96b3ef414b6cf6e5720d2b"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">armnn::IConnectableLayer::BackendSelectionHint</a></div><div class="ttdeci">virtual void BackendSelectionHint(Optional< BackendId > backend)=0</div><div class="ttdoc">Provide a hint for the optimizer as to which backend to prefer for this layer. </div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr< IRuntime, void(*)(IRuntime *runtime)> IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00026">IRuntime.hpp:26</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_profiler_xhtml_a038bb767bbc6abc0ee0d9b509616b896"><div class="ttname"><a href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">armnn::IProfiler::Print</a></div><div class="ttdeci">void Print(std::ostream &outStream) const</div><div class="ttdoc">Print stats for events in JSON Format to the given output stream. </div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00522">Profiling.cpp:522</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00340">Tensor.hpp:340</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00020">IRuntime.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a3756986bc88b9b212d3f983c70c5c129"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">armnn::ProfilerManager::GetProfiler</a></div><div class="ttdeci">IProfiler * GetProfiler()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00501">Profiling.cpp:501</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00306">Tensor.hpp:306</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00174">INetwork.hpp:174</a></div></div> +<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml">armnn::ProfilerManager</a></div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00091">Profiling.hpp:91</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml">armnn::OptimizerOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00110">INetwork.hpp:110</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_afdb1d37740e7a083b625d669588b6a0e"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">armnn::Layer::GetBackendId</a></div><div class="ttdeci">const BackendId & GetBackendId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00269">Layer.hpp:269</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00043">IRuntime.hpp:43</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a6a2659750d6161b693d0e51616791959"><div class="ttname"><a href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">armnn::GetGraphForTesting</a></div><div class="ttdeci">Graph & GetGraphForTesting(IOptimizedNetwork *optNet)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00025">TestUtils.cpp:25</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a></div><div class="ttdoc">CPU Execution: NEON: ArmCompute. </div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0</div><div class="ttdoc">Get the const output slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</div></div> +<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#l00329">Descriptors.hpp:329</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00510">Network.cpp:510</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</a></div></div> +</div><!-- fragment --> +</div> +</div> +</div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_1ad86c6d39ab715a831555571b9e98a5.xhtml">cl</a></li><li class="navelem"><a class="el" href="dir_02bab2737bbb2fb3882a0be567244fbf.xhtml">test</a></li><li class="navelem"><a class="el" href="_cl_fallback_tests_8cpp.xhtml">ClFallbackTests.cpp</a></li> + <li class="footer">Generated on Thu Feb 25 2021 17:27:55 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + </ul> +</div> +</body> +</html> |