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| author | Nikhil Raj <nikhil.raj@arm.com> | 2022-05-24 11:32:07 +0100 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-05-24 11:32:07 +0100 |
| commit | 549b9600a6eaf0727fa084465a75f173edf8f381 (patch) | |
| tree | 9c9b054417504444fff067b74eaa1811b74e6d06 /22.05/_execute_network_8cpp_source.xhtml | |
| parent | f4019872c1134c6fcc1d6993e5746f55c1e79208 (diff) | |
| download | armnn-549b9600a6eaf0727fa084465a75f173edf8f381.tar.gz | |
Update 22.05 Doxygen Docs after updates to main Readme
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: I56711772406a41ff81fa136a5fb6c59c9b9cf504
Diffstat (limited to '22.05/_execute_network_8cpp_source.xhtml')
| -rw-r--r-- | 22.05/_execute_network_8cpp_source.xhtml | 247 |
1 files changed, 247 insertions, 0 deletions
diff --git a/22.05/_execute_network_8cpp_source.xhtml b/22.05/_execute_network_8cpp_source.xhtml new file mode 100644 index 0000000000..ebda7c5198 --- /dev/null +++ b/22.05/_execute_network_8cpp_source.xhtml @@ -0,0 +1,247 @@ +<!-- 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: tests/ExecuteNetwork/ExecuteNetwork.cpp Source File</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">22.05</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(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('_execute_network_8cpp_source.xhtml','');}); +</script> +<div id="doc-content"> +<!-- window showing the filter options --> +<div id="MSearchSelectWindow" + onmouseover="return searchBox.OnSearchSelectShow()" + onmouseout="return searchBox.OnSearchSelectHide()" + onkeydown="return searchBox.OnSearchSelectKey(event)"> +</div> + +<!-- iframe showing the search results (closed by default) --> +<div id="MSearchResultsWindow"> +<iframe src="javascript:void(0)" frameborder="0" + name="MSearchResults" id="MSearchResults"> +</iframe> +</div> + +<div class="header"> + <div class="headertitle"> +<div class="title">ExecuteNetwork.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_execute_network_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_network_execution_utils_8hpp.xhtml">NetworkExecutionUtils/NetworkExecutionUtils.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_execute_network_program_options_8hpp.xhtml">ExecuteNetworkProgramOptions.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_i_async_execution_callback_8hpp.xhtml">armnn/IAsyncExecutionCallback.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_async_execution_callback_8hpp.xhtml">AsyncExecutionCallback.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_logging_8hpp.xhtml">armnn/Logging.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_filesystem_8hpp.xhtml">armnnUtils/Filesystem.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_t_container_8hpp.xhtml">armnnUtils/TContainer.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_profiling_options_converter_8hpp.xhtml">ProfilingOptionsConverter.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_inference_test_8hpp.xhtml">InferenceTest.hpp</a>></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#if defined(ARMNN_SERIALIZER)</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include "<a class="code" href="_i_deserializer_8hpp.xhtml">armnnDeserializer/IDeserializer.hpp</a>"</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#if defined(ARMNN_TF_LITE_PARSER)</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include "<a class="code" href="_i_tf_lite_parser_8hpp.xhtml">armnnTfLiteParser/ITfLiteParser.hpp</a>"</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#if defined(ARMNN_ONNX_PARSER)</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include "<a class="code" href="_i_onnx_parser_8hpp.xhtml">armnnOnnxParser/IOnnxParser.hpp</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#if defined(ARMNN_TFLITE_DELEGATE)</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include <<a class="code" href="armnn__delegate_8hpp.xhtml">armnn_delegate.hpp</a>></span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include <<a class="code" href="_delegate_options_8hpp.xhtml">DelegateOptions.hpp</a>></span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include <tensorflow/lite/builtin_ops.h></span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include <tensorflow/lite/c/builtin_op_data.h></span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include <tensorflow/lite/c/common.h></span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include <tensorflow/lite/optional_debug_tools.h></span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include <tensorflow/lite/kernels/builtin_op_kernels.h></span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include <tensorflow/lite/interpreter.h></span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include <tensorflow/lite/kernels/register.h></span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include <future></span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment"></span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment">/**</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="comment"> * Given a measured duration and a threshold time tell the user whether we succeeded or not.</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment"> *</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment"> * @param duration the measured inference duration.</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="comment"> * @param thresholdTime the threshold time in milliseconds.</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="comment"> * @return false if the measured time exceeded the threshold.</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"> */</span></div><div class="line"><a name="l00048"></a><span class="lineno"><a class="line" href="_execute_network_8cpp.xhtml#ab9be7e320a1879b362298cb198250dae"> 48</a></span> <span class="keywordtype">bool</span> <a class="code" href="_execute_network_8cpp.xhtml#ab9be7e320a1879b362298cb198250dae">CheckInferenceTimeThreshold</a>(<span class="keyword">const</span> std::chrono::duration<double, std::milli>& duration,</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keyword">const</span> <span class="keywordtype">double</span>& thresholdTime)</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Inference time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  << std::fixed << duration.count() << <span class="stringliteral">" ms\n"</span>;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="comment">// If thresholdTime == 0.0 (default), then it hasn't been supplied at command line</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">if</span> (thresholdTime != 0.0)</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="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Threshold time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  << std::fixed << thresholdTime << <span class="stringliteral">" ms"</span>;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">auto</span> thresholdMinusInference = thresholdTime - duration.count();</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Threshold time - Inference time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  << std::fixed << thresholdMinusInference << <span class="stringliteral">" ms"</span> << <span class="stringliteral">"\n"</span>;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordflow">if</span> (thresholdMinusInference < 0)</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  {</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  std::string errorMessage = <span class="stringliteral">"Elapsed inference time is greater than provided threshold time."</span>;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << errorMessage;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  }</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  }</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> }</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="preprocessor">#if defined(ARMNN_TFLITE_DELEGATE)</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="keywordtype">int</span> TfLiteDelegateMainImpl(<span class="keyword">const</span> <a class="code" href="struct_execute_network_params.xhtml">ExecuteNetworkParams</a>& params, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a> runtimeOptions)</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="comment">// Build model and corresponding interpreter</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keyword">using namespace </span><a class="code" href="namespacetflite.xhtml">tflite</a>;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  std::unique_ptr<tflite::FlatBufferModel> model = tflite::FlatBufferModel::BuildFromFile(params.<a class="code" href="struct_execute_network_params.xhtml#a4fa312cf0d60fbd3988a7c76ab8e2980">m_ModelPath</a>.c_str());</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">auto</span> tfLiteInterpreter = std::make_unique<Interpreter>();</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  tflite::ops::builtin::BuiltinOpResolver resolver;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  tflite::InterpreterBuilder builder(*model, resolver);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  builder(&tfLiteInterpreter);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  tfLiteInterpreter->AllocateTensors();</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordtype">int</span> status = 0;</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>  <span class="comment">// Create & populate Armnn Delegate, then register it to TfLiteInterpreter</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a876462c8d3a74b51c890820df24f42f9">m_TfLiteExecutor</a> == <a class="code" href="struct_execute_network_params.xhtml#a721fa5f104533ca06589330accc2857da34feb52e49daeff4cae20f668187ec5c">ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteDelegate</a>)</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  {</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="comment">// Create the Armnn Delegate</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="comment">// Populate a DelegateOptions from the ExecuteNetworkParams.</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="classarmnn_delegate_1_1_delegate_options.xhtml">armnnDelegate::DelegateOptions</a> delegateOptions = params.ToDelegateOptions();</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  delegateOptions.<a class="code" href="classarmnn_delegate_1_1_delegate_options.xhtml#abfd26a0521c63aaf8857067e4b6b6e3e">SetExternalProfilingParams</a>(</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <a class="code" href="namespacearm_1_1pipe.xhtml#aedd5bf7f3d6df99a1b42e7826c5b380b">arm::pipe::ConvertExternalProfilingOptions</a>(runtimeOptions.<a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml#a30412a91cadff138686eaeb12f5357cc">m_ProfilingOptions</a>));</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  theArmnnDelegate(<a class="code" href="namespacearmnn_delegate.xhtml#aaab840e387d9a4e7de223fbc8c969eb3">armnnDelegate::TfLiteArmnnDelegateCreate</a>(delegateOptions),</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="namespacearmnn_delegate.xhtml#a29bbb05765039d65532d61301b56749e">armnnDelegate::TfLiteArmnnDelegateDelete</a>);</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="comment">// Register armnn_delegate to TfLiteInterpreter</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  status = tfLiteInterpreter->ModifyGraphWithDelegate(std::move(theArmnnDelegate));</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordflow">if</span> (status != kTfLiteOk)</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  {</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Could not register ArmNN TfLite Delegate to TfLiteInterpreter!"</span>;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  }</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  }</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  {</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  std::cout << <span class="stringliteral">"Running on TfLite without ArmNN delegate\n"</span>;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  }</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="comment">// Load (or generate) input data for inference</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<std::string></a> dataFile = params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  ? <a class="code" href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a>()</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  : armnn::MakeOptional<std::string>(params.<a class="code" href="struct_execute_network_params.xhtml#ae3c3ae097395afea488cd3e0244269fa">m_InputTensorDataFilePaths</a>[0]);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> numInputs = params.<a class="code" href="struct_execute_network_params.xhtml#aaf3c7f286030842a31025309ab6a8329">m_InputNames</a>.size();</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="comment">// Populate input tensor of interpreter</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputIndex = 0; inputIndex < numInputs; ++inputIndex)</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordtype">int</span> input = tfLiteInterpreter->inputs()[inputIndex];</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  TfLiteIntArray* inputDims = tfLiteInterpreter->tensor(input)->dims;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = 1;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>.size() > 0)</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  {</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  inputSize = params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>[inputIndex]->GetNumElements();</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  }</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  {</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dim = 0; dim < static_cast<unsigned int>(inputDims->size); ++dim)</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  {</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  inputSize *= inputDims->data[dim];</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  }</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  }</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex].compare(<span class="stringliteral">"float"</span>) == 0)</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  {</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">auto</span> inputData = tfLiteInterpreter->typed_tensor<<span class="keywordtype">float</span>>(input);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keywordflow">if</span>(inputData == NULL)</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  {</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Input tensor is null, input type: "</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="stringliteral">"\""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex] << <span class="stringliteral">"\" may be incorrect."</span>;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  }</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> </div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  std::vector<float> tensorData;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  PopulateTensorWithDataGeneric<float>(tensorData,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  inputSize,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  dataFile,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  [](<span class="keyword">const</span> std::string& s)</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  { <span class="keywordflow">return</span> std::stof(s); });</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>  std::copy(tensorData.begin(), tensorData.end(), inputData);</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  }</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex].compare(<span class="stringliteral">"qsymms8"</span>) == 0 ||</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex].compare(<span class="stringliteral">"qasymms8"</span>) == 0)</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  {</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">auto</span> inputData = tfLiteInterpreter->typed_tensor<int8_t>(input);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> </div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">if</span>(inputData == NULL)</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  {</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Input tensor is null, input type: "</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="stringliteral">"\""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex] << <span class="stringliteral">"\" may be incorrect."</span>;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  }</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<int8_t> tensorData;</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  PopulateTensorWithDataGeneric<int8_t>(tensorData,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  inputSize,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  dataFile,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  [](<span class="keyword">const</span> std::string& s)</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  { <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><int8_t>(std::stoi(s)); });</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> </div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  std::copy(tensorData.begin(), tensorData.end(), inputData);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  }</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex].compare(<span class="stringliteral">"int"</span>) == 0)</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  {</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keyword">auto</span> inputData = tfLiteInterpreter->typed_tensor<int32_t>(input);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> </div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordflow">if</span>(inputData == NULL)</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  {</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Input tensor is null, input type: "</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="stringliteral">"\""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex] << <span class="stringliteral">"\" may be incorrect."</span>;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  }</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> </div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  std::vector<int32_t> tensorData;</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  PopulateTensorWithDataGeneric<int32_t>(tensorData,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  inputSize,</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  dataFile,</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  [](<span class="keyword">const</span> std::string& s)</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  { <span class="keywordflow">return</span> std::stoi(s); });</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  std::copy(tensorData.begin(), tensorData.end(), inputData);</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="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex].compare(<span class="stringliteral">"qasymm8"</span>) == 0 ||</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex].compare(<span class="stringliteral">"qasymmu8"</span>) == 0)</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="keyword">auto</span> inputData = tfLiteInterpreter->typed_tensor<uint8_t>(input);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordflow">if</span>(inputData == NULL)</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>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Input tensor is null, input type: "</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="stringliteral">"\""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex] << <span class="stringliteral">"\" may be incorrect."</span>;</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  }</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> </div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  std::vector<uint8_t> tensorData;</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  PopulateTensorWithDataGeneric<uint8_t>(tensorData,</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  inputSize,</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  dataFile,</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  [](<span class="keyword">const</span> std::string& s)</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  { <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><uint8_t>(std::stoi(s)); });</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  std::copy(tensorData.begin(), tensorData.end(), inputData);</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  }</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  {</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Unsupported input tensor data type \""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[inputIndex] << <span class="stringliteral">"\". "</span>;</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  }</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>  <span class="comment">// Run inference, print the output of the inference</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> x = 0; x < params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>; x++)</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  {</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="comment">// Start timer to record inference time in milliseconds.</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keyword">const</span> <span class="keyword">auto</span> start_time = <a class="code" href="namespacearmnn.xhtml#ac895f6f6897ce335b7b433201bae0b48">armnn::GetTimeNow</a>();</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="comment">// Run the inference</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  status = tfLiteInterpreter->Invoke();</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <span class="keyword">const</span> <span class="keyword">auto</span> duration = <a class="code" href="namespacearmnn.xhtml#a441621f00fd5665898c81a5ae3473c6b">armnn::GetTimeDuration</a>(start_time);</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="comment">// The TFLite interpreter's outputs might be in a different order than the user inputted output names.</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  std::map<unsigned int, int> paramToTfliteOutputIndex;</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> paramIndex = 0; paramIndex < params.<a class="code" href="struct_execute_network_params.xhtml#a982d4141ecde3eb220a136610d853df2">m_OutputNames</a>.size(); ++paramIndex)</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>  paramToTfliteOutputIndex[paramIndex] = -1;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> tfLiteIndex = 0; tfLiteIndex < tfLiteInterpreter->outputs().size(); ++tfLiteIndex)</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="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a982d4141ecde3eb220a136610d853df2">m_OutputNames</a>[paramIndex] == tfLiteInterpreter->GetOutputName(tfLiteIndex))</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  {</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  paramToTfliteOutputIndex[paramIndex] = tfLiteIndex;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  }</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  }</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  }</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> </div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="comment">// Print out the output</span></div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> paramOutputIndex = 0; paramOutputIndex < params.<a class="code" href="struct_execute_network_params.xhtml#a982d4141ecde3eb220a136610d853df2">m_OutputNames</a>.size(); ++paramOutputIndex)</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="keywordtype">int</span> outputIndex = paramToTfliteOutputIndex[paramOutputIndex];</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keywordflow">if</span> (outputIndex == -1)</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  {</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  std::cout << fmt::format(<span class="stringliteral">"Output name: {} doesn't exist."</span>, params.<a class="code" href="struct_execute_network_params.xhtml#a982d4141ecde3eb220a136610d853df2">m_OutputNames</a>[paramOutputIndex]) <<</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  std::endl;</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keywordflow">continue</span>;</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  }</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keyword">auto</span> tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[outputIndex];</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  TfLiteIntArray* outputDims = tfLiteInterpreter->tensor(tfLiteDelegateOutputId)->dims;</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="comment">// If we've been asked to write to a file then set a file output stream. Otherwise use stdout.</span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  FILE* outputTensorFile = stdout;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.empty())</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  {</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  outputTensorFile = fopen(params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputIndex].c_str(), <span class="stringliteral">"w"</span>);</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <span class="keywordflow">if</span> (outputTensorFile == NULL)</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  {</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Specified output tensor file, \""</span> <<</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputIndex] <<</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="stringliteral">"\", cannot be created. Defaulting to stdout. "</span> <<</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="stringliteral">"Error was: "</span> << std::strerror(errno);</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  outputTensorFile = stdout;</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  }</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  {</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Writing output "</span> << outputIndex << <span class="stringliteral">"' of iteration: "</span> << x+1 << <span class="stringliteral">" to file: '"</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  << params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputIndex] << <span class="stringliteral">"'"</span>;</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  }</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  }</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="keywordtype">long</span> outputSize = 1;</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dim = 0; dim < static_cast<unsigned int>(outputDims->size); ++dim)</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  {</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  outputSize *= outputDims->data[dim];</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  }</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> </div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  std::cout << tfLiteInterpreter->GetOutputName(outputIndex) << <span class="stringliteral">": "</span>;</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex].compare(<span class="stringliteral">"float"</span>) == 0)</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  {</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keyword">auto</span> tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<<span class="keywordtype">float</span>>(tfLiteDelegateOutputId);</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keywordflow">if</span>(tfLiteDelageOutputData == NULL)</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  {</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Output tensor is null, output type: "</span></div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="stringliteral">"\""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex] << <span class="stringliteral">"\" may be incorrect."</span>;</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  }</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>)</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  {</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < outputSize; ++i)</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>  fprintf(outputTensorFile, <span class="stringliteral">"%f "</span>, tfLiteDelageOutputData[i]);</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  }</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  }</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  }</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex].compare(<span class="stringliteral">"int"</span>) == 0)</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  {</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keyword">auto</span> tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<int32_t>(tfLiteDelegateOutputId);</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordflow">if</span>(tfLiteDelageOutputData == NULL)</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  {</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Output tensor is null, output type: "</span></div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="stringliteral">"\""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex] << <span class="stringliteral">"\" may be incorrect."</span>;</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  }</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> </div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>)</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  {</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < outputSize; ++i)</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  {</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  fprintf(outputTensorFile, <span class="stringliteral">"%d "</span>, tfLiteDelageOutputData[i]);</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  }</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  }</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  }</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex].compare(<span class="stringliteral">"qsymms8"</span>) == 0 ||</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex].compare(<span class="stringliteral">"qasymms8"</span>) == 0)</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  {</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keyword">auto</span> tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<int8_t>(tfLiteDelegateOutputId);</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">if</span>(tfLiteDelageOutputData == NULL)</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  {</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Output tensor is null, output type: "</span></div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="stringliteral">"\""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex] << <span class="stringliteral">"\" may be incorrect."</span>;</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  }</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> </div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>)</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  {</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < outputSize; ++i)</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  {</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  fprintf(outputTensorFile, <span class="stringliteral">"%d "</span>, tfLiteDelageOutputData[i]);</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>  }</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="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex].compare(<span class="stringliteral">"qasymm8"</span>) == 0 ||</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex].compare(<span class="stringliteral">"qasymmu8"</span>) == 0)</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>  <span class="keyword">auto</span> tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<uint8_t>(tfLiteDelegateOutputId);</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordflow">if</span>(tfLiteDelageOutputData == NULL)</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  {</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Output tensor is null, output type: "</span></div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="stringliteral">"\""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex] << <span class="stringliteral">"\" may be incorrect."</span>;</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  }</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> </div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>)</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>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < outputSize; ++i)</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  {</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  fprintf(outputTensorFile, <span class="stringliteral">"%u "</span>, tfLiteDelageOutputData[i]);</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  }</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  }</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  }</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  {</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Output tensor is null, output type: "</span></div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="stringliteral">"\""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[paramOutputIndex] <<</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="stringliteral">"\" may be incorrect. Output type can be specified with -z argument"</span>;</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</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>  std::cout << std::endl;</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>  <a class="code" href="_execute_network_8cpp.xhtml#ab9be7e320a1879b362298cb198250dae">CheckInferenceTimeThreshold</a>(duration, params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a>);</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  }</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> </div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordflow">return</span> status;</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> }</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> <span class="keyword">template</span><<span class="keyword">typename</span> TParser, <span class="keyword">typename</span> TDataType></div><div class="line"><a name="l00379"></a><span class="lineno"><a class="line" href="_execute_network_8cpp.xhtml#afc1c3398fd2de1051edf23a171cfa01b"> 379</a></span> <span class="keywordtype">int</span> <a class="code" href="_execute_network_8cpp.xhtml#afc1c3398fd2de1051edf23a171cfa01b">MainImpl</a>(<span class="keyword">const</span> <a class="code" href="struct_execute_network_params.xhtml">ExecuteNetworkParams</a>& params,</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keyword">const</span> std::shared_ptr<armnn::IRuntime>& runtime = <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span> {</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <span class="keyword">using namespace </span><a class="code" href="namespacestd_1_1chrono.xhtml">std::chrono</a>;</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>  std::vector<std::vector<armnnUtils::TContainer>> inputs;</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  std::vector<std::vector<armnnUtils::TContainer>> outputs;</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span> </div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  {</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="comment">// Creates an InferenceModel, which will parse the model and load it into an IRuntime.</span></div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="keyword">typename</span> <a class="code" href="struct_inference_model_internal_1_1_params.xhtml">InferenceModel<TParser, TDataType>::Params</a> inferenceModelParams;</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a4fa312cf0d60fbd3988a7c76ab8e2980">m_ModelPath</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a4fa312cf0d60fbd3988a7c76ab8e2980">m_ModelPath</a>;</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a9ef8ddbeee4b869e4c68eb2ed278b8d9">m_AllowExpandedDims</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a9ef8ddbeee4b869e4c68eb2ed278b8d9">m_AllowExpandedDims</a>;</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a6bf2f586c403977d31c7d32d371918cf">m_IsModelBinary</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a6bf2f586c403977d31c7d32d371918cf">m_IsModelBinary</a>;</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a2d54e6252c1c9a0e29f7706ba03b2b74">m_ComputeDevices</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a2d54e6252c1c9a0e29f7706ba03b2b74">m_ComputeDevices</a>;</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">m_DynamicBackendsPath</a> = params.<a class="code" href="struct_execute_network_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">m_DynamicBackendsPath</a>;</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#acde2af8cbbd224a9f94e509ca538a775">m_PrintIntermediateLayers</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a5acc5b4076604db15ee13ee19fa623c4">m_PrintIntermediate</a>;</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#aaae50a6c0f73e4c210c2e4331c439482">m_VisualizePostOptimizationModel</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a7efc68309e76bfefbfa16fe94501b060">m_EnableLayerDetails</a>;</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a5c7f0c083da98e7b6e9ba79d2fcd985d">m_ParseUnsupported</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a5c7f0c083da98e7b6e9ba79d2fcd985d">m_ParseUnsupported</a>;</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a2a245a63e87f363df491ad8c35be54c5">m_InferOutputShape</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a2a245a63e87f363df491ad8c35be54c5">m_InferOutputShape</a>;</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a66f9597b152215daba3211379dad63d3">m_EnableFastMath</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a66f9597b152215daba3211379dad63d3">m_EnableFastMath</a>;</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a9a04b8c7f19a84f63125edec509b6d53">m_SaveCachedNetwork</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a9a04b8c7f19a84f63125edec509b6d53">m_SaveCachedNetwork</a>;</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a9f8881646a38f828f92d3354930c4165">m_CachedNetworkFilePath</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a9f8881646a38f828f92d3354930c4165">m_CachedNetworkFilePath</a>;</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#adc650e032e7fce99f15e2bf903e7167b">m_NumberOfThreads</a> = params.<a class="code" href="struct_execute_network_params.xhtml#adc650e032e7fce99f15e2bf903e7167b">m_NumberOfThreads</a>;</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#ac609a217f4de4c647422dbb358a5f2ef">m_MLGOTuningFilePath</a> = params.<a class="code" href="struct_execute_network_params.xhtml#ac609a217f4de4c647422dbb358a5f2ef">m_MLGOTuningFilePath</a>;</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#af5e88d9bb91dff85ad5a6f7e190aff4e">m_AsyncEnabled</a> = params.<a class="code" href="struct_execute_network_params.xhtml#abf3cb45be3828b72b4ac08f87ac6c779">m_Concurrent</a>;</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a7adc5dcfe3d76ac489f253c4d5f439c8">m_ThreadPoolSize</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a7adc5dcfe3d76ac489f253c4d5f439c8">m_ThreadPoolSize</a>;</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#ae96fc745917a3a0c0de7a818c9a05012">m_OutputDetailsToStdOut</a> = params.<a class="code" href="struct_execute_network_params.xhtml#ae96fc745917a3a0c0de7a818c9a05012">m_OutputDetailsToStdOut</a>;</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#ab17deb382179697b4702cc4f909e71f8">m_OutputDetailsOnlyToStdOut</a> = params.<a class="code" href="struct_execute_network_params.xhtml#ab17deb382179697b4702cc4f909e71f8">m_OutputDetailsOnlyToStdOut</a>;</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a1697b9751b4ba381f89b8c81cd9dfc3c">m_ImportInputsIfAligned</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a1697b9751b4ba381f89b8c81cd9dfc3c">m_ImportInputsIfAligned</a>;</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span> </div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <span class="keywordflow">for</span>(<span class="keyword">const</span> std::string& inputName: params.<a class="code" href="struct_execute_network_params.xhtml#aaf3c7f286030842a31025309ab6a8329">m_InputNames</a>)</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  {</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#aad2ac35d4cb83ee4da9fad5fbcb907e0">m_InputBindings</a>.push_back(inputName);</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  }</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> </div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>.size(); ++i)</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  {</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#ad69aa6b4967ce55ee4a915c52c71bf2e">m_InputShapes</a>.push_back(*params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>[i]);</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> </div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="keywordflow">for</span>(<span class="keyword">const</span> std::string& outputName: params.<a class="code" href="struct_execute_network_params.xhtml#a982d4141ecde3eb220a136610d853df2">m_OutputNames</a>)</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  {</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>.push_back(outputName);</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  }</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span> </div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a2d4582aa74998c397bd064ae73745b62">m_SubgraphId</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a2d4582aa74998c397bd064ae73745b62">m_SubgraphId</a>;</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a513151623e8d448951a0b94ad1946fbe">m_EnableFp16TurboMode</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a513151623e8d448951a0b94ad1946fbe">m_EnableFp16TurboMode</a>;</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#a0b99050baebe1d169392461b3a9be08d">m_EnableBf16TurboMode</a> = params.<a class="code" href="struct_execute_network_params.xhtml#a0b99050baebe1d169392461b3a9be08d">m_EnableBf16TurboMode</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>  <a class="code" href="class_inference_model.xhtml">InferenceModel<TParser, TDataType></a> model(inferenceModelParams,</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a26d42007440bb01a1a6d0ab3b5a657ee">m_EnableProfiling</a>,</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  params.<a class="code" href="struct_execute_network_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">m_DynamicBackendsPath</a>,</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  runtime);</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span> </div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> numInputs = inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#aad2ac35d4cb83ee4da9fad5fbcb907e0">m_InputBindings</a>.size();</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>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<QuantizationParams></a> qParams = params.<a class="code" href="struct_execute_network_params.xhtml#a077f6963fc555d9d42f98cf9ed3e7e03">m_QuantizeInput</a> ?</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  armnn::MakeOptional<QuantizationParams>(</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  model.<a class="code" href="class_inference_model.xhtml#a066580d185559e2efdcb6cedd1709b9c">GetInputQuantizationParams</a>()) :</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a>();</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span> </div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#ae3c3ae097395afea488cd3e0244269fa">m_InputTensorDataFilePaths</a>.size() > numInputs)</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  {</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Given network has "</span> << numInputs << <span class="stringliteral">" input/s. One input-tensor-data file is required "</span></div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  << <span class="stringliteral">"for each input. The user provided "</span></div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  << params.<a class="code" href="struct_execute_network_params.xhtml#ae3c3ae097395afea488cd3e0244269fa">m_InputTensorDataFilePaths</a>.size()</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  << <span class="stringliteral">" input-tensor-data file/s which will be used to fill the input/s.\n"</span>;</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  }</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span> </div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> numOutputs = inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>.size();</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> </div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="comment">// The user is allowed to specify the data type of each output tensor. It is used here to construct the</span></div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="comment">// result tensors for each iteration. It is possible for the user to specify a type that does not match</span></div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <span class="comment">// the data type of the corresponding model output. It may not make sense, but it is historically allowed.</span></div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <span class="comment">// The potential problem here is a buffer overrun when a larger data type is written into the space for a</span></div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="comment">// smaller one. Issue a warning to highlight the potential problem.</span></div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIdx = 0; outputIdx < model.<a class="code" href="class_inference_model.xhtml#ac0b73049e00e7013f5cc6ae7fcaedcd4">GetOutputBindingInfos</a>().size(); ++outputIdx)</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  {</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> type = model.<a class="code" href="class_inference_model.xhtml#a325f1c17b5ff2153cae944e3c62820a2">GetOutputBindingInfo</a>(outputIdx).second.GetDataType();</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <span class="keywordflow">switch</span> (type)</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  {</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <span class="comment">// --output-type only supports float, int, qasymms8 or qasymmu8.</span></div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>:</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[outputIdx].compare(<span class="stringliteral">"float"</span>) != 0)</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  {</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(warning) << <span class="stringliteral">"Model output index: "</span> << outputIdx << <span class="stringliteral">" has data type Float32. The "</span></div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  << <span class="stringliteral">"corresponding --output-type is "</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[outputIdx] <<</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  <span class="stringliteral">". This may cause unexpected problems or random failures."</span>;</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  }</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>:</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[outputIdx].compare(<span class="stringliteral">"qasymmu8"</span>) != 0)</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>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(warning) << <span class="stringliteral">"Model output index: "</span> << outputIdx << <span class="stringliteral">" has data type QAsymmU8. The "</span></div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  << <span class="stringliteral">"corresponding --output-type is "</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[outputIdx] <<</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  <span class="stringliteral">". This may cause unexpected problems or random failures."</span>;</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="keywordflow">break</span>;</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>:</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[outputIdx].compare(<span class="stringliteral">"int"</span>) != 0)</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  {</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(warning) << <span class="stringliteral">"Model output index: "</span> << outputIdx << <span class="stringliteral">" has data type Signed32. The "</span></div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  << <span class="stringliteral">"corresponding --output-type is "</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[outputIdx] <<</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="stringliteral">". This may cause unexpected problems or random failures."</span>;</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  }</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>:</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[outputIdx].compare(<span class="stringliteral">"qasymms8"</span>) != 0)</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  {</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(warning) << <span class="stringliteral">"Model output index: "</span> << outputIdx << <span class="stringliteral">" has data type QAsymmS8. The "</span></div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  << <span class="stringliteral">"corresponding --output-type is "</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[outputIdx] <<</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <span class="stringliteral">". This may cause unexpected problems or random failures."</span>;</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  }</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keywordflow">break</span>;</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>  }</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span> </div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#acb9376adc0f7174b7d4295e00315a084">m_ReuseBuffers</a>)</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = 0; j < params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>; ++j)</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>  std::vector<armnnUtils::TContainer> inputDataContainers;</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputs; ++i)</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  {</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <span class="comment">// If there are fewer input files given than required for the execution of</span></div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="comment">// params.m_Iterations we simply start with the first input file again</span></div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <span class="keywordtype">size_t</span> inputFileIndex = j * numInputs + i;</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#ae3c3ae097395afea488cd3e0244269fa">m_InputTensorDataFilePaths</a>.empty())</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>  inputFileIndex = inputFileIndex % params.<a class="code" href="struct_execute_network_params.xhtml#ae3c3ae097395afea488cd3e0244269fa">m_InputTensorDataFilePaths</a>.size();</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  }</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span> </div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<std::string></a> dataFile = params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a> ?</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a>() :</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  armnn::MakeOptional<std::string>(</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  params.<a class="code" href="struct_execute_network_params.xhtml#ae3c3ae097395afea488cd3e0244269fa">m_InputTensorDataFilePaths</a>.at(</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  inputFileIndex));</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span> </div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numElements = model.<a class="code" href="class_inference_model.xhtml#a679e4b22a845c8d7f58f6ca6a5df625f">GetInputSize</a>(i);</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>.size() > i && params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>[i])</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  {</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  <span class="comment">// If the user has provided a tensor shape for the current input,</span></div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  <span class="comment">// override numElements</span></div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  numElements = params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>[i]->GetNumElements();</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  }</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span> </div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <a class="code" href="namespacearmnn_utils.xhtml#ac7bd4ea667375c07718086368507ed44">armnnUtils::TContainer</a> tensorData;</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <a class="code" href="_network_execution_utils_8cpp.xhtml#afcaa1d8d70f62d28c2cb7779b6155afb">PopulateTensorWithData</a>(tensorData,</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  numElements,</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[i],</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  qParams,</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  dataFile);</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span> </div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  inputDataContainers.push_back(tensorData);</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  }</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  inputs.push_back(inputDataContainers);</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  }</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span> </div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = 0; j < params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>; ++j)</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  {</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  std::vector<armnnUtils::TContainer> outputDataContainers;</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numOutputs; ++i)</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  {</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i].compare(<span class="stringliteral">"float"</span>) == 0)</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  {</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  outputDataContainers.push_back(std::vector<float>(model.<a class="code" href="class_inference_model.xhtml#a8282dddf88e0deb3c414235e20a6cb2c">GetOutputSize</a>(i)));</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  }</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i].compare(<span class="stringliteral">"int"</span>) == 0)</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  {</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  outputDataContainers.push_back(std::vector<int>(model.<a class="code" href="class_inference_model.xhtml#a8282dddf88e0deb3c414235e20a6cb2c">GetOutputSize</a>(i)));</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  }</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i].compare(<span class="stringliteral">"qasymm8"</span>) == 0 ||</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i].compare(<span class="stringliteral">"qasymmu8"</span>) == 0)</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  {</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  outputDataContainers.push_back(std::vector<uint8_t>(model.<a class="code" href="class_inference_model.xhtml#a8282dddf88e0deb3c414235e20a6cb2c">GetOutputSize</a>(i)));</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  }</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i].compare(<span class="stringliteral">"qasymms8"</span>) == 0)</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  {</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  outputDataContainers.push_back(std::vector<int8_t>(model.<a class="code" href="class_inference_model.xhtml#a8282dddf88e0deb3c414235e20a6cb2c">GetOutputSize</a>(i)));</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  }</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  {</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Unsupported tensor data type \""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i] << <span class="stringliteral">"\". "</span>;</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  }</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  }</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  outputs.push_back(outputDataContainers);</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  }</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  }</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a> > 1)</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  {</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  std::stringstream msg;</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  msg << <span class="stringliteral">"Network will be executed "</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>;</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#abf3cb45be3828b72b4ac08f87ac6c779">m_Concurrent</a>)</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  {</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  msg << <span class="stringliteral">" times in an asynchronous manner. "</span>;</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  }</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  {</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  msg << <span class="stringliteral">" times successively. "</span>;</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  }</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  msg << <span class="stringliteral">"The input-tensor-data files will be reused recursively if the user didn't provide enough to "</span></div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  <span class="stringliteral">"cover each execution."</span>;</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << msg.str();</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  }</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span> </div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <span class="comment">// Synchronous execution</span></div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#abf3cb45be3828b72b4ac08f87ac6c779">m_Concurrent</a> && !params.<a class="code" href="struct_execute_network_params.xhtml#acb9376adc0f7174b7d4295e00315a084">m_ReuseBuffers</a>)</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  {</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> x = 0; x < params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>; x++)</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  {</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <span class="comment">// model.Run returns the inference time elapsed in EnqueueWorkload (in milliseconds)</span></div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="keyword">auto</span> inference_duration = model.<a class="code" href="class_inference_model.xhtml#a25651303cbe4a971cdada990eb71bf21">Run</a>(inputs[x], outputs[x]);</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span> </div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a>)</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  {</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(warning) << <span class="stringliteral">"The input data was generated, note that the output will not be useful"</span>;</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  }</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>)</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  {</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Printing outputs to console is disabled."</span>;</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  }</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span> </div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="comment">// Print output tensors</span></div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& infosOut = model.<a class="code" href="class_inference_model.xhtml#ac0b73049e00e7013f5cc6ae7fcaedcd4">GetOutputBindingInfos</a>();</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < numOutputs; i++)</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  {</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& infoOut = infosOut[i].second;</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span> </div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="comment">// We've made sure before that the number of output files either equals numOutputs, in which</span></div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <span class="comment">// case we override those files when processing the results of each iteration (only the result</span></div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  <span class="comment">// of the last iteration will be stored), or there are enough</span></div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  <span class="comment">// output files for each output of each iteration.</span></div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <span class="keywordtype">size_t</span> outputFileIndex = x * numOutputs + i;</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.empty())</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  {</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  outputFileIndex = outputFileIndex % params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.size();</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Writing output "</span> << i << <span class="stringliteral">" named: '"</span></div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  << inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>[i]</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  << <span class="stringliteral">"' of iteration: "</span> << x+1 << <span class="stringliteral">" to file: '"</span></div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  << params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputFileIndex] << <span class="stringliteral">"'"</span>;</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  }</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  <span class="keyword">auto</span> outputTensorFile = params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.empty()</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  ? <span class="stringliteral">""</span></div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  : params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputFileIndex];</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span> </div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  <a class="code" href="struct_tensor_printer.xhtml">TensorPrinter</a> printer(inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>[i],</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  infoOut,</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  outputTensorFile,</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a85929a48c5e7b16af8f5bc637e45a37f">m_DequantizeOutput</a>,</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  !params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>);</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  mapbox::util::apply_visitor(printer, outputs[x][i]);</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  }</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span> </div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"\nInference time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  << std::fixed << inference_duration.count() << <span class="stringliteral">" ms\n"</span>;</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span> </div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  <span class="comment">// If thresholdTime == 0.0 (default), then it hasn't been supplied at command line</span></div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a> != 0.0)</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  {</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Threshold time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  << std::fixed << params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a> << <span class="stringliteral">" ms"</span>;</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  <span class="keyword">auto</span> thresholdMinusInference = params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a> - inference_duration.count();</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Threshold time - Inference time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  << std::fixed << thresholdMinusInference << <span class="stringliteral">" ms"</span> << <span class="stringliteral">"\n"</span>;</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span> </div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  <span class="keywordflow">if</span> (thresholdMinusInference < 0)</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  {</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  std::string errorMessage = <span class="stringliteral">"Elapsed inference time is greater than provided threshold time."</span>;</div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << errorMessage;</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  }</div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  }</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  }</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  }</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <span class="comment">// Synchronous Execution using a single buffer for input and output data</span></div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(!params.<a class="code" href="struct_execute_network_params.xhtml#abf3cb45be3828b72b4ac08f87ac6c779">m_Concurrent</a>)</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  {</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  std::vector<armnnUtils::TContainer> input;</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  std::vector<armnnUtils::TContainer> output;</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span> </div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputs; ++i)</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  {</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  <span class="comment">// If there are fewer input files given than required for the execution of</span></div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  <span class="comment">// params.m_Iterations we simply start with the first input file again</span></div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  <span class="keywordtype">size_t</span> inputFileIndex = numInputs + i;</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#ae3c3ae097395afea488cd3e0244269fa">m_InputTensorDataFilePaths</a>.empty())</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  {</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  inputFileIndex = inputFileIndex % params.<a class="code" href="struct_execute_network_params.xhtml#ae3c3ae097395afea488cd3e0244269fa">m_InputTensorDataFilePaths</a>.size();</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  }</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span> </div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<std::string></a> dataFile = params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a> ?</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  <a class="code" href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a>() :</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  armnn::MakeOptional<std::string>(</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  params.<a class="code" href="struct_execute_network_params.xhtml#ae3c3ae097395afea488cd3e0244269fa">m_InputTensorDataFilePaths</a>.at(</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  inputFileIndex));</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span> </div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numElements = model.<a class="code" href="class_inference_model.xhtml#a679e4b22a845c8d7f58f6ca6a5df625f">GetInputSize</a>(i);</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>.size() > i && params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>[i])</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  {</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  <span class="comment">// If the user has provided a tensor shape for the current input,</span></div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  <span class="comment">// override numElements</span></div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  numElements = params.<a class="code" href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">m_InputTensorShapes</a>[i]->GetNumElements();</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  }</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span> </div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  <a class="code" href="namespacearmnn_utils.xhtml#ac7bd4ea667375c07718086368507ed44">armnnUtils::TContainer</a> tensorData;</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  <a class="code" href="_network_execution_utils_8cpp.xhtml#afcaa1d8d70f62d28c2cb7779b6155afb">PopulateTensorWithData</a>(tensorData,</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  numElements,</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  params.<a class="code" href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">m_InputTypes</a>[i],</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  qParams,</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  dataFile);</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span> </div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  input.push_back(tensorData);</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  }</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span> </div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numOutputs; ++i)</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  {</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i].compare(<span class="stringliteral">"float"</span>) == 0)</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  {</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  output.push_back(std::vector<float>(model.<a class="code" href="class_inference_model.xhtml#a8282dddf88e0deb3c414235e20a6cb2c">GetOutputSize</a>(i)));</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i].compare(<span class="stringliteral">"int"</span>) == 0) {</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  output.push_back(std::vector<int>(model.<a class="code" href="class_inference_model.xhtml#a8282dddf88e0deb3c414235e20a6cb2c">GetOutputSize</a>(i)));</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i].compare(<span class="stringliteral">"qasymm8"</span>) == 0 ||</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i].compare(<span class="stringliteral">"qasymmu8"</span>) == 0)</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  {</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  output.push_back(std::vector<uint8_t>(model.<a class="code" href="class_inference_model.xhtml#a8282dddf88e0deb3c414235e20a6cb2c">GetOutputSize</a>(i)));</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i].compare(<span class="stringliteral">"qasymms8"</span>) == 0)</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  {</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  output.push_back(std::vector<int8_t>(model.<a class="code" href="class_inference_model.xhtml#a8282dddf88e0deb3c414235e20a6cb2c">GetOutputSize</a>(i)));</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  } <span class="keywordflow">else</span> {</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Unsupported tensor data type \""</span> << params.<a class="code" href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">m_OutputTypes</a>[i] << <span class="stringliteral">"\". "</span>;</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  }</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  }</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span> </div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  std::vector<std::chrono::duration<double, std::milli>> timings;</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  timings.reserve(params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>);</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> x = 0; x < params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>; x++)</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  {</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  <span class="comment">// model.Run returns the inference time elapsed in EnqueueWorkload (in milliseconds)</span></div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <span class="keyword">auto</span> inference_duration = model.<a class="code" href="class_inference_model.xhtml#a25651303cbe4a971cdada990eb71bf21">Run</a>(input, output);</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  timings.push_back(inference_duration);</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  }</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span> </div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a>)</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  {</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(warning) << <span class="stringliteral">"The input data was generated, note that the output will not be useful"</span>;</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  }</div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>)</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  {</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Printing outputs to console is disabled."</span>;</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  }</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span> </div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  <span class="comment">// Print output. This only needs to happen once as input is the same for each iteration.</span></div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  <span class="keyword">const</span> <span class="keyword">auto</span> &infosOut = model.<a class="code" href="class_inference_model.xhtml#ac0b73049e00e7013f5cc6ae7fcaedcd4">GetOutputBindingInfos</a>();</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < numOutputs; i++)</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  {</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> &infoOut = infosOut[i].second;</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span> </div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  <span class="comment">// We've made sure before that the number of output files either equals numOutputs, in which</span></div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  <span class="comment">// case we override those files when processing the results of each iteration (only the result</span></div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  <span class="comment">// of the last iteration will be stored), or there are enough</span></div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  <span class="comment">// output files for each output of each iteration.</span></div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  <span class="keywordtype">size_t</span> outputFileIndex = numOutputs + i;</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.empty())</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  {</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  outputFileIndex = outputFileIndex % params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.size();</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Writing output "</span> << i << <span class="stringliteral">" named: '"</span></div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  << inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>[i] <<<span class="stringliteral">" to file: '"</span></div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  << params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputFileIndex] << <span class="stringliteral">"'"</span>;</div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  }</div><div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  <span class="keyword">auto</span> outputTensorFile = params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.empty()</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  ? <span class="stringliteral">""</span></div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  : params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputFileIndex];</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span> </div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  <a class="code" href="struct_tensor_printer.xhtml">TensorPrinter</a> printer(inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>[i],</div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  infoOut,</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  outputTensorFile,</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a85929a48c5e7b16af8f5bc637e45a37f">m_DequantizeOutput</a>,</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  !params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>);</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  mapbox::util::apply_visitor(printer, output[i]);</div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  }</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span> </div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  <span class="keywordflow">for</span>(<span class="keyword">auto</span> inference: timings)</div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  {</div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span> </div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"\nInference time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  << std::fixed << inference.count() << <span class="stringliteral">" ms\n"</span>;</div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span> </div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  <span class="comment">// If thresholdTime == 0.0 (default), then it hasn't been supplied at command line</span></div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a> != 0.0)</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  {</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Threshold time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  << std::fixed << params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a> << <span class="stringliteral">" ms"</span>;</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  <span class="keyword">auto</span> thresholdMinusInference = params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a> - inference.count();</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Threshold time - Inference time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  << std::fixed << thresholdMinusInference << <span class="stringliteral">" ms"</span> << <span class="stringliteral">"\n"</span>;</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span> </div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  <span class="keywordflow">if</span> (thresholdMinusInference < 0)</div><div class="line"><a name="l00781"></a><span class="lineno"> 781</span>  {</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  std::string errorMessage = <span class="stringliteral">"Elapsed inference time is greater than provided threshold time."</span>;</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << errorMessage;</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  }</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  }</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  }</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  }</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span> </div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  <span class="comment">// Asynchronous execution using the Arm NN thread pool</span></div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a7adc5dcfe3d76ac489f253c4d5f439c8">m_ThreadPoolSize</a> >= 1)</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  {</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  {</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Asynchronous execution with Arm NN thread pool... \n"</span>;</div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <a class="code" href="classarmnn_1_1experimental_1_1_async_callback_manager.xhtml">armnn::AsyncCallbackManager</a> callbackManager;</div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  std::unordered_map<armnn::InferenceId, std::vector<armnnUtils::TContainer>&> inferenceOutputMap;</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span> </div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  <span class="comment">// Declare the latest and earliest inference times here to be used when calculating overall time</span></div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  std::chrono::high_resolution_clock::time_point earliestStartTime;</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  std::chrono::high_resolution_clock::time_point latestEndTime =</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  std::chrono::high_resolution_clock::now();</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span> </div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <span class="comment">// For the asynchronous execution, we are adding a pool of working memory handles (1 per thread) in the</span></div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  <span class="comment">// LoadedNetwork with each scheduled inference having a specific priority</span></div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>; ++i)</div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  {</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  std::shared_ptr<armnn::AsyncExecutionCallback> cb = callbackManager.<a class="code" href="classarmnn_1_1experimental_1_1_async_callback_manager.xhtml#a27aff9e4e5d9bce49988a2de6a1ebc59">GetNewCallback</a>();</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  inferenceOutputMap.insert({cb->GetInferenceId(), outputs[i]});</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  model.<a class="code" href="class_inference_model.xhtml#ab510347c552e6ff7fd6b702b688525b1">RunAsync</a>(inputs[i], outputs[i], cb);</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  }</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span> </div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  <span class="comment">// Check the results</span></div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = 0;</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> iteration = 0; iteration < params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>; ++iteration)</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  {</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  <span class="keyword">auto</span> cb = callbackManager.<a class="code" href="classarmnn_1_1experimental_1_1_async_callback_manager.xhtml#a9ee5b1dd7d3a6f619d2ed3d97d75d9b1">GetNotifiedCallback</a>();</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span> </div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  <span class="comment">// Get the results</span></div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  <span class="keyword">auto</span> endTime = time_point_cast<std::chrono::milliseconds>(cb->GetEndTime());</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  <span class="keyword">auto</span> startTime = time_point_cast<std::chrono::milliseconds>(cb->GetStartTime());</div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  <span class="keyword">auto</span> inferenceDuration = endTime - startTime;</div><div class="line"><a name="l00822"></a><span class="lineno"> 822</span> </div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  <span class="keywordflow">if</span> (latestEndTime < cb->GetEndTime())</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  {</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  latestEndTime = cb->GetEndTime();</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  }</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span> </div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  <span class="keywordflow">if</span> (earliestStartTime.time_since_epoch().count() == 0)</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  {</div><div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  earliestStartTime = cb->GetStartTime();</div><div class="line"><a name="l00831"></a><span class="lineno"> 831</span>  }</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (earliestStartTime > cb->GetStartTime())</div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span>  {</div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  earliestStartTime = cb->GetStartTime();</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  }</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span> </div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a>)</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  {</div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(warning) << <span class="stringliteral">"The input data was generated, note that the output will not be useful"</span>;</div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  }</div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>)</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  {</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Printing outputs to console is disabled."</span>;</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  }</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span> </div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  <span class="comment">// Print output tensors</span></div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& infosOut = model.<a class="code" href="class_inference_model.xhtml#ac0b73049e00e7013f5cc6ae7fcaedcd4">GetOutputBindingInfos</a>();</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < numOutputs; i++)</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  {</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  <span class="comment">// We've made sure before that the number of output files either equals numOutputs, in which</span></div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <span class="comment">// case we override those files when processing the results of each iteration (only the</span></div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  <span class="comment">// result of the last iteration will be stored), or there are enough</span></div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  <span class="comment">// output files for each output of each iteration.</span></div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  <span class="keywordtype">size_t</span> outputFileIndex = iteration * numOutputs + i;</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.empty())</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  {</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  outputFileIndex = outputFileIndex % params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.size();</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Writing output "</span> << i << <span class="stringliteral">" named: '"</span></div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  << inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>[i]</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  << <span class="stringliteral">"' of iteration: "</span> << iteration+1 << <span class="stringliteral">" to file: '"</span></div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  << params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputFileIndex] << <span class="stringliteral">"'"</span>;</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  }</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span> </div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& infoOut = infosOut[i].second;</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  <span class="keyword">auto</span> outputTensorFile = params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.empty()</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  ? <span class="stringliteral">""</span></div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  : params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputFileIndex];</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span> </div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  <a class="code" href="struct_tensor_printer.xhtml">TensorPrinter</a> printer(inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>[i],</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  infoOut,</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  outputTensorFile,</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a85929a48c5e7b16af8f5bc637e45a37f">m_DequantizeOutput</a>,</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  !params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>);</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  mapbox::util::apply_visitor(printer, inferenceOutputMap.at(cb->GetInferenceId())[i]);</div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  }</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span> </div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  <a class="code" href="_execute_network_8cpp.xhtml#ab9be7e320a1879b362298cb198250dae">CheckInferenceTimeThreshold</a>(inferenceDuration, params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a>);</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  ++j;</div><div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  }</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  <span class="comment">//print duration difference between overallStartTime and overallEndTime</span></div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  <span class="keyword">auto</span> overallEndTime = time_point_cast<std::chrono::milliseconds>(latestEndTime);</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  <span class="keyword">auto</span> overallStartTime = time_point_cast<std::chrono::milliseconds>(earliestStartTime);</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  <span class="keyword">auto</span> totalInferenceDuration = overallEndTime - overallStartTime;</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"\nOverall Inference time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  << std::fixed << totalInferenceDuration.count() << <span class="stringliteral">" ms\n"</span>;</div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  }</div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>& e)</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  {</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Armnn Error: "</span> << e.<a class="code" href="classarmnn_1_1_exception.xhtml#abf843cbb29dec939d0731e491bab6f70">what</a>();</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  }</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  }</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  <span class="comment">// Asynchronous execution using std::launch::async</span></div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  {</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  <span class="keywordflow">try</span></div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  {</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Asynchronous Execution with std::launch:async... \n"</span>;</div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span>  std::vector<std::future<std::tuple<<span class="keywordtype">unsigned</span> int,</div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  std::chrono::duration<double, std::milli>>>> inferenceResults;</div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  inferenceResults.reserve(params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>);</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span> </div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <span class="comment">// Create WorkingMemHandles for each inference</span></div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  std::vector<std::unique_ptr<armnn::experimental::IWorkingMemHandle>> workingMemHandles;</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  workingMemHandles.reserve(params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>);</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>; ++i)</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  {</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  workingMemHandles.push_back(model.<a class="code" href="class_inference_model.xhtml#a6d789a57513b4b26e31eaed316e45b7f">CreateWorkingMemHandle</a>());</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  }</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span> </div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  <span class="comment">// Run each inference in its own thread</span></div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  <span class="comment">// start a timer</span></div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  <span class="keyword">const</span> <span class="keyword">auto</span> start_time = <a class="code" href="namespacearmnn.xhtml#ac895f6f6897ce335b7b433201bae0b48">armnn::GetTimeNow</a>();</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < params.<a class="code" href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">m_Iterations</a>; ++i)</div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  {</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  <a class="code" href="classarmnn_1_1experimental_1_1_i_working_mem_handle.xhtml">armnn::experimental::IWorkingMemHandle</a>& workingMemHandleRef = *workingMemHandles[i].get();</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span> </div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  inferenceResults.push_back(std::async(</div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  std::launch::async, [&model, &workingMemHandleRef, &inputs, &outputs, i]() {</div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  <span class="keywordflow">return</span> model.<a class="code" href="class_inference_model.xhtml#ab510347c552e6ff7fd6b702b688525b1">RunAsync</a>(workingMemHandleRef, inputs[i], outputs[i], i);</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  }</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  ));</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  }</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span> </div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  <span class="comment">// Check the results</span></div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = 0; j < inferenceResults.size(); ++j)</div><div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  {</div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  <span class="comment">// Get the results</span></div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  <span class="keyword">auto</span> inferenceResult = inferenceResults[j].get();</div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  <span class="keyword">auto</span> inferenceDuration = std::get<1>(inferenceResult);</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  <span class="keyword">auto</span> inferenceID = std::get<0>(inferenceResult);</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span> </div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">m_GenerateTensorData</a>)</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  {</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(warning) << <span class="stringliteral">"The input data was generated, note that the output will not be useful"</span>;</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  }</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  <span class="keywordflow">if</span> (params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>)</div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  {</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Printing outputs to console is disabled."</span>;</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  }</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span> </div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  <span class="comment">// Print output tensors</span></div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& infosOut = model.<a class="code" href="class_inference_model.xhtml#ac0b73049e00e7013f5cc6ae7fcaedcd4">GetOutputBindingInfos</a>();</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < numOutputs; i++)</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  {</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  <span class="comment">// We've made sure before that the number of output files either equals numOutputs, in which</span></div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  <span class="comment">// case we override those files when processing the results of each iteration (only the</span></div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  <span class="comment">// result of the last iteration will be stored), or there are enough</span></div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  <span class="comment">// output files for each output of each iteration.</span></div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  <span class="keywordtype">size_t</span> outputFileIndex = j * numOutputs + i;</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  <span class="keywordflow">if</span> (!params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.empty())</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  {</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  outputFileIndex = outputFileIndex % params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.size();</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Writing output "</span> << i << <span class="stringliteral">" named: '"</span></div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  << inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>[i]</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  << <span class="stringliteral">"' of iteration: "</span> << j+1 << <span class="stringliteral">" to file: '"</span></div><div class="line"><a name="l00957"></a><span class="lineno"> 957</span>  << params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputFileIndex] << <span class="stringliteral">"'"</span>;</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  }</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& infoOut = infosOut[i].second;</div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  <span class="keyword">auto</span> outputTensorFile = params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>.empty()</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  ? <span class="stringliteral">""</span></div><div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  : params.<a class="code" href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">m_OutputTensorFiles</a>[outputFileIndex];</div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span> </div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  <a class="code" href="struct_tensor_printer.xhtml">TensorPrinter</a> printer(inferenceModelParams.<a class="code" href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">m_OutputBindings</a>[i],</div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  infoOut,</div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  outputTensorFile,</div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  params.<a class="code" href="struct_execute_network_params.xhtml#a85929a48c5e7b16af8f5bc637e45a37f">m_DequantizeOutput</a>,</div><div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  !params.<a class="code" href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">m_DontPrintOutputs</a>);</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  mapbox::util::apply_visitor(printer, outputs[j][i]);</div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  }</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  <a class="code" href="_execute_network_8cpp.xhtml#ab9be7e320a1879b362298cb198250dae">CheckInferenceTimeThreshold</a>(inferenceDuration, params.<a class="code" href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">m_ThresholdTime</a>);</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"Asynchronous Execution is finished for Inference ID: "</span> << inferenceID << <span class="stringliteral">" \n"</span>;</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  }</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  <span class="comment">// finish timer</span></div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  <span class="keyword">const</span> <span class="keyword">auto</span> duration = <a class="code" href="namespacearmnn.xhtml#a441621f00fd5665898c81a5ae3473c6b">armnn::GetTimeDuration</a>(start_time);</div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(info) << <span class="stringliteral">"\nOverall Inference time: "</span> << std::setprecision(2)</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  << std::fixed << duration.count() << <span class="stringliteral">" ms\n"</span>;</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  }</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>& e)</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  {</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Armnn Error: "</span> << e.<a class="code" href="classarmnn_1_1_exception.xhtml#abf843cbb29dec939d0731e491bab6f70">what</a>();</div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  }</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  }</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  }</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  <span class="keywordflow">catch</span> (<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>& e)</div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  {</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Armnn Error: "</span> << e.<a class="code" href="classarmnn_1_1_exception.xhtml#abf843cbb29dec939d0731e491bab6f70">what</a>();</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  }</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span> </div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  <span class="keywordflow">return</span> EXIT_SUCCESS;</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span> }</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span> </div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span> <span class="comment">// MAIN</span></div><div class="line"><a name="l00996"></a><span class="lineno"><a class="line" href="_execute_network_8cpp.xhtml#ac0f2228420376f4db7e1274f2b41667c"> 996</a></span> <span class="keywordtype">int</span> <a class="code" href="_execute_network_8cpp.xhtml#ac0f2228420376f4db7e1274f2b41667c">main</a>(<span class="keywordtype">int</span> argc, <span class="keyword">const</span> <span class="keywordtype">char</span>* argv[])</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span> {</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  <span class="comment">// Configures logging for both the ARMNN library and this test program.</span></div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span> <span class="preprocessor"> #ifdef NDEBUG</span></div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  <a class="code" href="namespacearmnn.xhtml#a93a3ba385cad27c4774e5fe64c025d3d">armnn::LogSeverity</a> level = <a class="code" href="namespacearmnn.xhtml#a93a3ba385cad27c4774e5fe64c025d3da4059b0251f66a18cb56f544728796875">armnn::LogSeverity::Info</a>;</div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span> <span class="preprocessor"> #else</span></div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  <a class="code" href="namespacearmnn.xhtml#a93a3ba385cad27c4774e5fe64c025d3d">armnn::LogSeverity</a> level = <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aa603905470e2a5b8c13e96b579ef0dba">armnn::LogSeverity::Debug</a>;</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span> <span class="preprocessor"> #endif</span></div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>  <a class="code" href="namespacearmnn.xhtml#aa59f7a819c3e29d10ffc41e5c0616872">armnn::ConfigureLogging</a>(<span class="keyword">true</span>, <span class="keyword">true</span>, level);</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span> </div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span> </div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  <span class="comment">// Get ExecuteNetwork parameters and runtime options from command line</span></div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  <span class="comment">// This might throw an InvalidArgumentException if the user provided invalid inputs</span></div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  <a class="code" href="struct_program_options.xhtml">ProgramOptions</a> <a class="code" href="struct_program_options.xhtml">ProgramOptions</a>;</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>  <span class="keywordflow">try</span> {</div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>  ProgramOptions.<a class="code" href="struct_program_options.xhtml#a59cc301c978c454abd5ce1851a63e59e">ParseOptions</a>(argc, argv);</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  } <span class="keywordflow">catch</span> (<span class="keyword">const</span> std::exception &e){</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << e.what();</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  }</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span> </div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  <span class="keywordflow">if</span> ((ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>.<a class="code" href="struct_execute_network_params.xhtml#ae96fc745917a3a0c0de7a818c9a05012">m_OutputDetailsToStdOut</a> ||</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>.<a class="code" href="struct_execute_network_params.xhtml#ab17deb382179697b4702cc4f909e71f8">m_OutputDetailsOnlyToStdOut</a>)</div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  && !ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>.<a class="code" href="struct_execute_network_params.xhtml#a26d42007440bb01a1a6d0ab3b5a657ee">m_EnableProfiling</a>)</div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>  {</div><div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"You must enable profiling if you would like to output layer details"</span>;</div><div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>  }</div><div class="line"><a name="l01024"></a><span class="lineno"> 1024</span> </div><div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>  std::string modelFormat = ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>.<a class="code" href="struct_execute_network_params.xhtml#a86800ee44cdb3d1bfd169ec4200212d2">m_ModelFormat</a>;</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span> </div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  <span class="comment">// Forward to implementation based on the parser type</span></div><div class="line"><a name="l01028"></a><span class="lineno"> 1028</span>  <span class="keywordflow">if</span> (modelFormat.find(<span class="stringliteral">"armnn"</span>) != std::string::npos)</div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>  {</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span> <span class="preprocessor"> #if defined(ARMNN_SERIALIZER)</span></div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  std::shared_ptr<armnn::IRuntime> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(ProgramOptions.<a class="code" href="struct_program_options.xhtml#a521b82f1467d6ede7a11db36f4d0823d">m_RuntimeOptions</a>));</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  <span class="keywordflow">return</span> MainImpl<armnnDeserializer::IDeserializer, float>(ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>, runtime);</div><div class="line"><a name="l01033"></a><span class="lineno"> 1033</span> <span class="preprocessor"> #else</span></div><div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Not built with serialization support."</span>;</div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l01036"></a><span class="lineno"> 1036</span> <span class="preprocessor"> #endif</span></div><div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>  }</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (modelFormat.find(<span class="stringliteral">"onnx"</span>) != std::string::npos)</div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  {</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span> <span class="preprocessor"> #if defined(ARMNN_ONNX_PARSER)</span></div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>  std::shared_ptr<armnn::IRuntime> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(ProgramOptions.<a class="code" href="struct_program_options.xhtml#a521b82f1467d6ede7a11db36f4d0823d">m_RuntimeOptions</a>));</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  <span class="keywordflow">return</span> MainImpl<armnnOnnxParser::IOnnxParser, float>(ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>, runtime);</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span> <span class="preprocessor"> #else</span></div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Not built with Onnx parser support."</span>;</div><div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l01046"></a><span class="lineno"> 1046</span> <span class="preprocessor"> #endif</span></div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  }</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(modelFormat.find(<span class="stringliteral">"tflite"</span>) != std::string::npos)</div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  {</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>  <span class="keywordflow">if</span> (ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>.<a class="code" href="struct_execute_network_params.xhtml#a876462c8d3a74b51c890820df24f42f9">m_TfLiteExecutor</a> == <a class="code" href="struct_execute_network_params.xhtml#a721fa5f104533ca06589330accc2857daf36e3b2e1fe4ec94cab683d237883fee">ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteParser</a>)</div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>  {</div><div class="line"><a name="l01052"></a><span class="lineno"> 1052</span> <span class="preprocessor"> #if defined(ARMNN_TF_LITE_PARSER)</span></div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  std::shared_ptr<armnn::IRuntime> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(ProgramOptions.<a class="code" href="struct_program_options.xhtml#a521b82f1467d6ede7a11db36f4d0823d">m_RuntimeOptions</a>));</div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>  <span class="keywordflow">return</span> MainImpl<armnnTfLiteParser::ITfLiteParser, float>(ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>, runtime);</div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span> <span class="preprocessor"> #else</span></div><div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Not built with Tensorflow-Lite parser support."</span>;</div><div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l01058"></a><span class="lineno"> 1058</span> <span class="preprocessor"> #endif</span></div><div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  }</div><div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>.<a class="code" href="struct_execute_network_params.xhtml#a876462c8d3a74b51c890820df24f42f9">m_TfLiteExecutor</a> ==</div><div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  <a class="code" href="struct_execute_network_params.xhtml#a721fa5f104533ca06589330accc2857da34feb52e49daeff4cae20f668187ec5c">ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteDelegate</a> ||</div><div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>  ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>.<a class="code" href="struct_execute_network_params.xhtml#a876462c8d3a74b51c890820df24f42f9">m_TfLiteExecutor</a> ==</div><div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>  <a class="code" href="struct_execute_network_params.xhtml#a721fa5f104533ca06589330accc2857da979cb18d483aeb3c0c636e340ba011df">ExecuteNetworkParams::TfLiteExecutor::TfliteInterpreter</a>)</div><div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>  {</div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span> <span class="preprocessor"> #if defined(ARMNN_TF_LITE_DELEGATE)</span></div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>  <span class="keywordflow">return</span> TfLiteDelegateMainImpl(ProgramOptions.<a class="code" href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">m_ExNetParams</a>, ProgramOptions.<a class="code" href="struct_program_options.xhtml#a521b82f1467d6ede7a11db36f4d0823d">m_RuntimeOptions</a>);</div><div class="line"><a name="l01067"></a><span class="lineno"> 1067</span> <span class="preprocessor"> #else</span></div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Not built with Arm NN Tensorflow-Lite delegate support."</span>;</div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span> <span class="preprocessor"> #endif</span></div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  }</div><div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>  }</div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  {</div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>  <a class="code" href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a>(fatal) << <span class="stringliteral">"Unknown model format: '"</span> << modelFormat</div><div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>  << <span class="stringliteral">"'. Please include 'tflite' or 'onnx'"</span>;</div><div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>  <span class="keywordflow">return</span> EXIT_FAILURE;</div><div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>  }</div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</span> }</div><div class="ttc" id="namespacetflite_xhtml"><div class="ttname"><a href="namespacetflite.xhtml">tflite</a></div><div class="ttdef"><b>Definition:</b> <a href="armnn__external__delegate_8cpp_source.xhtml#l00012">armnn_external_delegate.cpp:12</a></div></div> +<div class="ttc" id="struct_program_options_xhtml_a85f77fe8adc087571402b9e204ad77dd"><div class="ttname"><a href="struct_program_options.xhtml#a85f77fe8adc087571402b9e204ad77dd">ProgramOptions::m_ExNetParams</a></div><div class="ttdeci">ExecuteNetworkParams m_ExNetParams</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_program_options_8hpp_source.xhtml#l00044">ExecuteNetworkProgramOptions.hpp:44</a></div></div> +<div class="ttc" id="class_inference_model_xhtml_a25651303cbe4a971cdada990eb71bf21"><div class="ttname"><a href="class_inference_model.xhtml#a25651303cbe4a971cdada990eb71bf21">InferenceModel::Run</a></div><div class="ttdeci">std::chrono::duration< double, std::milli > Run(const std::vector< armnnUtils::TContainer > &inputContainers, std::vector< armnnUtils::TContainer > &outputContainers)</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00594">InferenceModel.hpp:594</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_acc7592cbdfe2e70cbc3794fb1e7eaeb9"><div class="ttname"><a href="struct_execute_network_params.xhtml#acc7592cbdfe2e70cbc3794fb1e7eaeb9">ExecuteNetworkParams::m_InputTypes</a></div><div class="ttdeci">std::vector< std::string > m_InputTypes</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00045">ExecuteNetworkParams.hpp:45</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a4fa312cf0d60fbd3988a7c76ab8e2980"><div class="ttname"><a href="struct_execute_network_params.xhtml#a4fa312cf0d60fbd3988a7c76ab8e2980">ExecuteNetworkParams::m_ModelPath</a></div><div class="ttdeci">std::string m_ModelPath</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00049">ExecuteNetworkParams.hpp:49</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a85929a48c5e7b16af8f5bc637e45a37f"><div class="ttname"><a href="struct_execute_network_params.xhtml#a85929a48c5e7b16af8f5bc637e45a37f">ExecuteNetworkParams::m_DequantizeOutput</a></div><div class="ttdeci">bool m_DequantizeOutput</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00032">ExecuteNetworkParams.hpp:32</a></div></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#l00049">Runtime.cpp:49</a></div></div> +<div class="ttc" id="_i_async_execution_callback_8hpp_xhtml"><div class="ttname"><a href="_i_async_execution_callback_8hpp.xhtml">IAsyncExecutionCallback.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a441621f00fd5665898c81a5ae3473c6b"><div class="ttname"><a href="namespacearmnn.xhtml#a441621f00fd5665898c81a5ae3473c6b">armnn::GetTimeDuration</a></div><div class="ttdeci">std::chrono::duration< double, std::milli > GetTimeDuration(std::chrono::high_resolution_clock::time_point start_time)</div><div class="ttdef"><b>Definition:</b> <a href="_timer_8hpp_source.xhtml#l00019">Timer.hpp:19</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_ac609a217f4de4c647422dbb358a5f2ef"><div class="ttname"><a href="struct_execute_network_params.xhtml#ac609a217f4de4c647422dbb358a5f2ef">ExecuteNetworkParams::m_MLGOTuningFilePath</a></div><div class="ttdeci">std::string m_MLGOTuningFilePath</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00066">ExecuteNetworkParams.hpp:66</a></div></div> +<div class="ttc" id="classarmnn_1_1experimental_1_1_async_callback_manager_xhtml_a27aff9e4e5d9bce49988a2de6a1ebc59"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_async_callback_manager.xhtml#a27aff9e4e5d9bce49988a2de6a1ebc59">armnn::experimental::AsyncCallbackManager::GetNewCallback</a></div><div class="ttdeci">std::shared_ptr< AsyncExecutionCallback > GetNewCallback()</div><div class="ttdef"><b>Definition:</b> <a href="_async_execution_callback_8cpp_source.xhtml#l00046">AsyncExecutionCallback.cpp:46</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a9ef8ddbeee4b869e4c68eb2ed278b8d9"><div class="ttname"><a href="struct_execute_network_params.xhtml#a9ef8ddbeee4b869e4c68eb2ed278b8d9">ExecuteNetworkParams::m_AllowExpandedDims</a></div><div class="ttdeci">bool m_AllowExpandedDims</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00028">ExecuteNetworkParams.hpp:28</a></div></div> +<div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional< std::string ></a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a721fa5f104533ca06589330accc2857da34feb52e49daeff4cae20f668187ec5c"><div class="ttname"><a href="struct_execute_network_params.xhtml#a721fa5f104533ca06589330accc2857da34feb52e49daeff4cae20f668187ec5c">ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteDelegate</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_ac828647e0c753c3727c8c1f81939f7e4"><div class="ttname"><a href="struct_execute_network_params.xhtml#ac828647e0c753c3727c8c1f81939f7e4">ExecuteNetworkParams::m_DontPrintOutputs</a></div><div class="ttdeci">bool m_DontPrintOutputs</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00058">ExecuteNetworkParams.hpp:58</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a091cda9098c6f03f91f477a22327892d"><div class="ttname"><a href="struct_execute_network_params.xhtml#a091cda9098c6f03f91f477a22327892d">ExecuteNetworkParams::m_InputTensorShapes</a></div><div class="ttdeci">std::vector< TensorShapePtr > m_InputTensorShapes</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00044">ExecuteNetworkParams.hpp:44</a></div></div> +<div class="ttc" id="class_inference_model_xhtml_a066580d185559e2efdcb6cedd1709b9c"><div class="ttname"><a href="class_inference_model.xhtml#a066580d185559e2efdcb6cedd1709b9c">InferenceModel::GetInputQuantizationParams</a></div><div class="ttdeci">QuantizationParams GetInputQuantizationParams(unsigned int inputIndex=0u) const</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00779">InferenceModel.hpp:779</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="class_inference_model_xhtml_ac0b73049e00e7013f5cc6ae7fcaedcd4"><div class="ttname"><a href="class_inference_model.xhtml#ac0b73049e00e7013f5cc6ae7fcaedcd4">InferenceModel::GetOutputBindingInfos</a></div><div class="ttdeci">const std::vector< armnn::BindingPointInfo > & GetOutputBindingInfos() const</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00767">InferenceModel.hpp:767</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_ab17deb382179697b4702cc4f909e71f8"><div class="ttname"><a href="struct_execute_network_params.xhtml#ab17deb382179697b4702cc4f909e71f8">ExecuteNetworkParams::m_OutputDetailsOnlyToStdOut</a></div><div class="ttdeci">bool m_OutputDetailsOnlyToStdOut</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00052">ExecuteNetworkParams.hpp:52</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa59f7a819c3e29d10ffc41e5c0616872"><div class="ttname"><a href="namespacearmnn.xhtml#aa59f7a819c3e29d10ffc41e5c0616872">armnn::ConfigureLogging</a></div><div class="ttdeci">void ConfigureLogging(bool printToStandardOutput, bool printToDebugOutput, LogSeverity severity)</div><div class="ttdoc">Configures the logging behaviour of the ARMNN library. </div><div class="ttdef"><b>Definition:</b> <a href="_utils_8cpp_source.xhtml#l00018">Utils.cpp:18</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a513151623e8d448951a0b94ad1946fbe"><div class="ttname"><a href="struct_execute_network_params.xhtml#a513151623e8d448951a0b94ad1946fbe">ExecuteNetworkParams::m_EnableFp16TurboMode</a></div><div class="ttdeci">bool m_EnableFp16TurboMode</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00036">ExecuteNetworkParams.hpp:36</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_ae43cf4b5df0068ee6a9151c98947248b"><div class="ttname"><a href="struct_execute_network_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">ExecuteNetworkParams::m_DynamicBackendsPath</a></div><div class="ttdeci">std::string m_DynamicBackendsPath</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00033">ExecuteNetworkParams.hpp:33</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_ae43cf4b5df0068ee6a9151c98947248b"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#ae43cf4b5df0068ee6a9151c98947248b">InferenceModelInternal::Params::m_DynamicBackendsPath</a></div><div class="ttdeci">std::string m_DynamicBackendsPath</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00096">InferenceModel.hpp:96</a></div></div> +<div class="ttc" id="class_inference_model_xhtml_a325f1c17b5ff2153cae944e3c62820a2"><div class="ttname"><a href="class_inference_model.xhtml#a325f1c17b5ff2153cae944e3c62820a2">InferenceModel::GetOutputBindingInfo</a></div><div class="ttdeci">const armnn::BindingPointInfo & GetOutputBindingInfo(unsigned int outputIndex=0u) const</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00761">InferenceModel.hpp:761</a></div></div> +<div class="ttc" id="class_inference_model_xhtml"><div class="ttname"><a href="class_inference_model.xhtml">InferenceModel</a></div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00377">InferenceModel.hpp:377</a></div></div> +<div class="ttc" id="classarmnn_1_1_exception_xhtml_abf843cbb29dec939d0731e491bab6f70"><div class="ttname"><a href="classarmnn_1_1_exception.xhtml#abf843cbb29dec939d0731e491bab6f70">armnn::Exception::what</a></div><div class="ttdeci">virtual const char * what() const noexcept override</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8cpp_source.xhtml#l00032">Exceptions.cpp:32</a></div></div> +<div class="ttc" id="struct_program_options_xhtml_a521b82f1467d6ede7a11db36f4d0823d"><div class="ttname"><a href="struct_program_options.xhtml#a521b82f1467d6ede7a11db36f4d0823d">ProgramOptions::m_RuntimeOptions</a></div><div class="ttdeci">armnn::IRuntime::CreationOptions m_RuntimeOptions</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_program_options_8hpp_source.xhtml#l00045">ExecuteNetworkProgramOptions.hpp:45</a></div></div> +<div class="ttc" id="_logging_8hpp_xhtml_a7b6ad073975f437ec38ca7d20154727f"><div class="ttname"><a href="_logging_8hpp.xhtml#a7b6ad073975f437ec38ca7d20154727f">ARMNN_LOG</a></div><div class="ttdeci">#define ARMNN_LOG(severity)</div><div class="ttdef"><b>Definition:</b> <a href="_logging_8hpp_source.xhtml#l00205">Logging.hpp:205</a></div></div> +<div class="ttc" id="class_inference_model_xhtml_ab510347c552e6ff7fd6b702b688525b1"><div class="ttname"><a href="class_inference_model.xhtml#ab510347c552e6ff7fd6b702b688525b1">InferenceModel::RunAsync</a></div><div class="ttdeci">std::tuple< unsigned int, std::chrono::duration< double, std::milli > > RunAsync(armnn::experimental::IWorkingMemHandle &workingMemHandleRef, const std::vector< armnnUtils::TContainer > &inputContainers, std::vector< armnnUtils::TContainer > &outputContainers, unsigned int inferenceID)</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00660">InferenceModel.hpp:660</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div> +<div class="ttc" id="_execute_network_8cpp_xhtml_ab9be7e320a1879b362298cb198250dae"><div class="ttname"><a href="_execute_network_8cpp.xhtml#ab9be7e320a1879b362298cb198250dae">CheckInferenceTimeThreshold</a></div><div class="ttdeci">bool CheckInferenceTimeThreshold(const std::chrono::duration< double, std::milli > &duration, const double &thresholdTime)</div><div class="ttdoc">Given a measured duration and a threshold time tell the user whether we succeeded or not...</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_8cpp_source.xhtml#l00048">ExecuteNetwork.cpp:48</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a721fa5f104533ca06589330accc2857daf36e3b2e1fe4ec94cab683d237883fee"><div class="ttname"><a href="struct_execute_network_params.xhtml#a721fa5f104533ca06589330accc2857daf36e3b2e1fe4ec94cab683d237883fee">ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteParser</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a513151623e8d448951a0b94ad1946fbe"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a513151623e8d448951a0b94ad1946fbe">InferenceModelInternal::Params::m_EnableFp16TurboMode</a></div><div class="ttdeci">bool m_EnableFp16TurboMode</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00101">InferenceModel.hpp:101</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a5acc5b4076604db15ee13ee19fa623c4"><div class="ttname"><a href="struct_execute_network_params.xhtml#a5acc5b4076604db15ee13ee19fa623c4">ExecuteNetworkParams::m_PrintIntermediate</a></div><div class="ttdeci">bool m_PrintIntermediate</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00057">ExecuteNetworkParams.hpp:57</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ac895f6f6897ce335b7b433201bae0b48"><div class="ttname"><a href="namespacearmnn.xhtml#ac895f6f6897ce335b7b433201bae0b48">armnn::GetTimeNow</a></div><div class="ttdeci">std::chrono::high_resolution_clock::time_point GetTimeNow()</div><div class="ttdef"><b>Definition:</b> <a href="_timer_8hpp_source.xhtml#l00014">Timer.hpp:14</a></div></div> +<div class="ttc" id="_profiling_options_converter_8hpp_xhtml"><div class="ttname"><a href="_profiling_options_converter_8hpp.xhtml">ProfilingOptionsConverter.hpp</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_abf3cb45be3828b72b4ac08f87ac6c779"><div class="ttname"><a href="struct_execute_network_params.xhtml#abf3cb45be3828b72b4ac08f87ac6c779">ExecuteNetworkParams::m_Concurrent</a></div><div class="ttdeci">bool m_Concurrent</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00031">ExecuteNetworkParams.hpp:31</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a982d4141ecde3eb220a136610d853df2"><div class="ttname"><a href="struct_execute_network_params.xhtml#a982d4141ecde3eb220a136610d853df2">ExecuteNetworkParams::m_OutputNames</a></div><div class="ttdeci">std::vector< std::string > m_OutputNames</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00053">ExecuteNetworkParams.hpp:53</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a876462c8d3a74b51c890820df24f42f9"><div class="ttname"><a href="struct_execute_network_params.xhtml#a876462c8d3a74b51c890820df24f42f9">ExecuteNetworkParams::m_TfLiteExecutor</a></div><div class="ttdeci">TfLiteExecutor m_TfLiteExecutor</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00067">ExecuteNetworkParams.hpp:67</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a5c7f0c083da98e7b6e9ba79d2fcd985d"><div class="ttname"><a href="struct_execute_network_params.xhtml#a5c7f0c083da98e7b6e9ba79d2fcd985d">ExecuteNetworkParams::m_ParseUnsupported</a></div><div class="ttdeci">bool m_ParseUnsupported</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00056">ExecuteNetworkParams.hpp:56</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a74d346297c55b516908c541030adc88d"><div class="ttname"><a href="struct_execute_network_params.xhtml#a74d346297c55b516908c541030adc88d">ExecuteNetworkParams::m_OutputTensorFiles</a></div><div class="ttdeci">std::vector< std::string > m_OutputTensorFiles</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00054">ExecuteNetworkParams.hpp:54</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a9a04b8c7f19a84f63125edec509b6d53"><div class="ttname"><a href="struct_execute_network_params.xhtml#a9a04b8c7f19a84f63125edec509b6d53">ExecuteNetworkParams::m_SaveCachedNetwork</a></div><div class="ttdeci">bool m_SaveCachedNetwork</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00060">ExecuteNetworkParams.hpp:60</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_aaae50a6c0f73e4c210c2e4331c439482"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#aaae50a6c0f73e4c210c2e4331c439482">InferenceModelInternal::Params::m_VisualizePostOptimizationModel</a></div><div class="ttdeci">bool m_VisualizePostOptimizationModel</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00100">InferenceModel.hpp:100</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a7adc5dcfe3d76ac489f253c4d5f439c8"><div class="ttname"><a href="struct_execute_network_params.xhtml#a7adc5dcfe3d76ac489f253c4d5f439c8">ExecuteNetworkParams::m_ThreadPoolSize</a></div><div class="ttdeci">size_t m_ThreadPoolSize</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00068">ExecuteNetworkParams.hpp:68</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a66f9597b152215daba3211379dad63d3"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a66f9597b152215daba3211379dad63d3">InferenceModelInternal::Params::m_EnableFastMath</a></div><div class="ttdeci">bool m_EnableFastMath</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00106">InferenceModel.hpp:106</a></div></div> +<div class="ttc" id="_filesystem_8hpp_xhtml"><div class="ttname"><a href="_filesystem_8hpp.xhtml">Filesystem.hpp</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_ae96fc745917a3a0c0de7a818c9a05012"><div class="ttname"><a href="struct_execute_network_params.xhtml#ae96fc745917a3a0c0de7a818c9a05012">ExecuteNetworkParams::m_OutputDetailsToStdOut</a></div><div class="ttdeci">bool m_OutputDetailsToStdOut</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00051">ExecuteNetworkParams.hpp:51</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a9f8881646a38f828f92d3354930c4165"><div class="ttname"><a href="struct_execute_network_params.xhtml#a9f8881646a38f828f92d3354930c4165">ExecuteNetworkParams::m_CachedNetworkFilePath</a></div><div class="ttdeci">std::string m_CachedNetworkFilePath</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00029">ExecuteNetworkParams.hpp:29</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a2d4582aa74998c397bd064ae73745b62"><div class="ttname"><a href="struct_execute_network_params.xhtml#a2d4582aa74998c397bd064ae73745b62">ExecuteNetworkParams::m_SubgraphId</a></div><div class="ttdeci">size_t m_SubgraphId</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00062">ExecuteNetworkParams.hpp:62</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a0b99050baebe1d169392461b3a9be08d"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a0b99050baebe1d169392461b3a9be08d">InferenceModelInternal::Params::m_EnableBf16TurboMode</a></div><div class="ttdeci">bool m_EnableBf16TurboMode</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00102">InferenceModel.hpp:102</a></div></div> +<div class="ttc" id="class_inference_model_xhtml_a8282dddf88e0deb3c414235e20a6cb2c"><div class="ttname"><a href="class_inference_model.xhtml#a8282dddf88e0deb3c414235e20a6cb2c">InferenceModel::GetOutputSize</a></div><div class="ttdeci">unsigned int GetOutputSize(unsigned int outputIndex=0u) const</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00588">InferenceModel.hpp:588</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a93a3ba385cad27c4774e5fe64c025d3da4059b0251f66a18cb56f544728796875"><div class="ttname"><a href="namespacearmnn.xhtml#a93a3ba385cad27c4774e5fe64c025d3da4059b0251f66a18cb56f544728796875">armnn::LogSeverity::Info</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_aad2ac35d4cb83ee4da9fad5fbcb907e0"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#aad2ac35d4cb83ee4da9fad5fbcb907e0">InferenceModelInternal::Params::m_InputBindings</a></div><div class="ttdeci">std::vector< std::string > m_InputBindings</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00092">InferenceModel.hpp:92</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a2d54e6252c1c9a0e29f7706ba03b2b74"><div class="ttname"><a href="struct_execute_network_params.xhtml#a2d54e6252c1c9a0e29f7706ba03b2b74">ExecuteNetworkParams::m_ComputeDevices</a></div><div class="ttdeci">std::vector< armnn::BackendId > m_ComputeDevices</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00030">ExecuteNetworkParams.hpp:30</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a810addfa426b5ac1476035dedee7cda5"><div class="ttname"><a href="struct_execute_network_params.xhtml#a810addfa426b5ac1476035dedee7cda5">ExecuteNetworkParams::m_OutputTypes</a></div><div class="ttdeci">std::vector< std::string > m_OutputTypes</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00055">ExecuteNetworkParams.hpp:55</a></div></div> +<div class="ttc" id="_i_tf_lite_parser_8hpp_xhtml"><div class="ttname"><a href="_i_tf_lite_parser_8hpp.xhtml">ITfLiteParser.hpp</a></div></div> +<div class="ttc" id="classarmnn_delegate_1_1_delegate_options_xhtml_abfd26a0521c63aaf8857067e4b6b6e3e"><div class="ttname"><a href="classarmnn_delegate_1_1_delegate_options.xhtml#abfd26a0521c63aaf8857067e4b6b6e3e">armnnDelegate::DelegateOptions::SetExternalProfilingParams</a></div><div class="ttdeci">void SetExternalProfilingParams(const arm::pipe::ProfilingOptions &externalProfilingParams)</div><div class="ttdef"><b>Definition:</b> <a href="_delegate_options_8hpp_source.xhtml#l00244">DelegateOptions.hpp:244</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a6bf2f586c403977d31c7d32d371918cf"><div class="ttname"><a href="struct_execute_network_params.xhtml#a6bf2f586c403977d31c7d32d371918cf">ExecuteNetworkParams::m_IsModelBinary</a></div><div class="ttdeci">bool m_IsModelBinary</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00046">ExecuteNetworkParams.hpp:46</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_ad69aa6b4967ce55ee4a915c52c71bf2e"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#ad69aa6b4967ce55ee4a915c52c71bf2e">InferenceModelInternal::Params::m_InputShapes</a></div><div class="ttdeci">std::vector< armnn::TensorShape > m_InputShapes</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00093">InferenceModel.hpp:93</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a1697b9751b4ba381f89b8c81cd9dfc3c"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a1697b9751b4ba381f89b8c81cd9dfc3c">InferenceModelInternal::Params::m_ImportInputsIfAligned</a></div><div class="ttdeci">bool m_ImportInputsIfAligned</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00115">InferenceModel.hpp:115</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a9a04b8c7f19a84f63125edec509b6d53"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a9a04b8c7f19a84f63125edec509b6d53">InferenceModelInternal::Params::m_SaveCachedNetwork</a></div><div class="ttdeci">bool m_SaveCachedNetwork</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00107">InferenceModel.hpp:107</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a7adc5dcfe3d76ac489f253c4d5f439c8"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a7adc5dcfe3d76ac489f253c4d5f439c8">InferenceModelInternal::Params::m_ThreadPoolSize</a></div><div class="ttdeci">size_t m_ThreadPoolSize</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00114">InferenceModel.hpp:114</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_af5e88d9bb91dff85ad5a6f7e190aff4e"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#af5e88d9bb91dff85ad5a6f7e190aff4e">InferenceModelInternal::Params::m_AsyncEnabled</a></div><div class="ttdeci">bool m_AsyncEnabled</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00113">InferenceModel.hpp:113</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a6e4eff6a5f40cb026ea76d3c13c96341"><div class="ttname"><a href="struct_execute_network_params.xhtml#a6e4eff6a5f40cb026ea76d3c13c96341">ExecuteNetworkParams::m_Iterations</a></div><div class="ttdeci">size_t m_Iterations</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00047">ExecuteNetworkParams.hpp:47</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00048">Types.hpp:48</a></div></div> +<div class="ttc" id="_execute_network_program_options_8hpp_xhtml"><div class="ttname"><a href="_execute_network_program_options_8hpp.xhtml">ExecuteNetworkProgramOptions.hpp</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a99c7360a4d4b248b3f10607bc5d2fe7b"><div class="ttname"><a href="struct_execute_network_params.xhtml#a99c7360a4d4b248b3f10607bc5d2fe7b">ExecuteNetworkParams::m_GenerateTensorData</a></div><div class="ttdeci">bool m_GenerateTensorData</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00039">ExecuteNetworkParams.hpp:39</a></div></div> +<div class="ttc" id="_network_execution_utils_8cpp_xhtml_afcaa1d8d70f62d28c2cb7779b6155afb"><div class="ttname"><a href="_network_execution_utils_8cpp.xhtml#afcaa1d8d70f62d28c2cb7779b6155afb">PopulateTensorWithData</a></div><div class="ttdeci">void PopulateTensorWithData(armnnUtils::TContainer &tensorData, unsigned int numElements, const std::string &dataTypeStr, const armnn::Optional< QuantizationParams > &qParams, const armnn::Optional< std::string > &dataFile)</div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8cpp_source.xhtml#l00231">NetworkExecutionUtils.cpp:231</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml"><div class="ttname"><a href="struct_execute_network_params.xhtml">ExecuteNetworkParams</a></div><div class="ttdoc">Holds all parameters necessary to execute a network Check ExecuteNetworkProgramOptions.cpp for a description of each parameter. </div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00017">ExecuteNetworkParams.hpp:17</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_abeacb4ed1ca9256ee0e8aea73185a0cc"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#abeacb4ed1ca9256ee0e8aea73185a0cc">InferenceModelInternal::Params::m_OutputBindings</a></div><div class="ttdeci">std::vector< std::string > m_OutputBindings</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00094">InferenceModel.hpp:94</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a2d54e6252c1c9a0e29f7706ba03b2b74"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a2d54e6252c1c9a0e29f7706ba03b2b74">InferenceModelInternal::Params::m_ComputeDevices</a></div><div class="ttdeci">std::vector< armnn::BackendId > m_ComputeDevices</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00095">InferenceModel.hpp:95</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_adc650e032e7fce99f15e2bf903e7167b"><div class="ttname"><a href="struct_execute_network_params.xhtml#adc650e032e7fce99f15e2bf903e7167b">ExecuteNetworkParams::m_NumberOfThreads</a></div><div class="ttdeci">unsigned int m_NumberOfThreads</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00050">ExecuteNetworkParams.hpp:50</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a318999172ae5197f56326b12d29104b7"><div class="ttname"><a href="struct_execute_network_params.xhtml#a318999172ae5197f56326b12d29104b7">ExecuteNetworkParams::m_ThresholdTime</a></div><div class="ttdeci">double m_ThresholdTime</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00063">ExecuteNetworkParams.hpp:63</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_aaf3c7f286030842a31025309ab6a8329"><div class="ttname"><a href="struct_execute_network_params.xhtml#aaf3c7f286030842a31025309ab6a8329">ExecuteNetworkParams::m_InputNames</a></div><div class="ttdeci">std::vector< std::string > m_InputNames</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00042">ExecuteNetworkParams.hpp:42</a></div></div> +<div class="ttc" id="_inference_test_8hpp_xhtml"><div class="ttname"><a href="_inference_test_8hpp.xhtml">InferenceTest.hpp</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a9ef8ddbeee4b869e4c68eb2ed278b8d9"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a9ef8ddbeee4b869e4c68eb2ed278b8d9">InferenceModelInternal::Params::m_AllowExpandedDims</a></div><div class="ttdeci">bool m_AllowExpandedDims</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00098">InferenceModel.hpp:98</a></div></div> +<div class="ttc" id="classarmnn_1_1experimental_1_1_i_working_mem_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_i_working_mem_handle.xhtml">armnn::experimental::IWorkingMemHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_working_mem_handle_8hpp_source.xhtml#l00018">IWorkingMemHandle.hpp:18</a></div></div> +<div class="ttc" id="namespacearm_1_1pipe_xhtml_aedd5bf7f3d6df99a1b42e7826c5b380b"><div class="ttname"><a href="namespacearm_1_1pipe.xhtml#aedd5bf7f3d6df99a1b42e7826c5b380b">arm::pipe::ConvertExternalProfilingOptions</a></div><div class="ttdeci">ProfilingOptions ConvertExternalProfilingOptions(const armnn::IRuntime::CreationOptions::ExternalProfilingOptions &options)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_options_converter_8cpp_source.xhtml#l00017">ProfilingOptionsConverter.cpp:17</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a5c7f0c083da98e7b6e9ba79d2fcd985d"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a5c7f0c083da98e7b6e9ba79d2fcd985d">InferenceModelInternal::Params::m_ParseUnsupported</a></div><div class="ttdeci">bool m_ParseUnsupported</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00104">InferenceModel.hpp:104</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a66f9597b152215daba3211379dad63d3"><div class="ttname"><a href="struct_execute_network_params.xhtml#a66f9597b152215daba3211379dad63d3">ExecuteNetworkParams::m_EnableFastMath</a></div><div class="ttdeci">bool m_EnableFastMath</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00035">ExecuteNetworkParams.hpp:35</a></div></div> +<div class="ttc" id="_i_onnx_parser_8hpp_xhtml"><div class="ttname"><a href="_i_onnx_parser_8hpp.xhtml">IOnnxParser.hpp</a></div></div> +<div class="ttc" id="namespacestd_1_1chrono_xhtml"><div class="ttname"><a href="namespacestd_1_1chrono.xhtml">chrono</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a0b99050baebe1d169392461b3a9be08d"><div class="ttname"><a href="struct_execute_network_params.xhtml#a0b99050baebe1d169392461b3a9be08d">ExecuteNetworkParams::m_EnableBf16TurboMode</a></div><div class="ttdeci">bool m_EnableBf16TurboMode</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00034">ExecuteNetworkParams.hpp:34</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_ae3c3ae097395afea488cd3e0244269fa"><div class="ttname"><a href="struct_execute_network_params.xhtml#ae3c3ae097395afea488cd3e0244269fa">ExecuteNetworkParams::m_InputTensorDataFilePaths</a></div><div class="ttdeci">std::vector< std::string > m_InputTensorDataFilePaths</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00043">ExecuteNetworkParams.hpp:43</a></div></div> +<div class="ttc" id="_logging_8hpp_xhtml"><div class="ttname"><a href="_logging_8hpp.xhtml">Logging.hpp</a></div></div> +<div class="ttc" id="struct_program_options_xhtml_a59cc301c978c454abd5ce1851a63e59e"><div class="ttname"><a href="struct_program_options.xhtml#a59cc301c978c454abd5ce1851a63e59e">ProgramOptions::ParseOptions</a></div><div class="ttdeci">void ParseOptions(int ac, const char *av[])</div><div class="ttdoc">Parses program options from the command line or another source and stores the values in member variab...</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_program_options_8cpp_source.xhtml#l00457">ExecuteNetworkProgramOptions.cpp:457</a></div></div> +<div class="ttc" id="_t_container_8hpp_xhtml"><div class="ttname"><a href="_t_container_8hpp.xhtml">TContainer.hpp</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#l00077">IRuntime.hpp:77</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a2a245a63e87f363df491ad8c35be54c5"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a2a245a63e87f363df491ad8c35be54c5">InferenceModelInternal::Params::m_InferOutputShape</a></div><div class="ttdeci">bool m_InferOutputShape</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00105">InferenceModel.hpp:105</a></div></div> +<div class="ttc" id="struct_program_options_xhtml"><div class="ttname"><a href="struct_program_options.xhtml">ProgramOptions</a></div><div class="ttdoc">Holds and parses program options for the ExecuteNetwork application. </div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_program_options_8hpp_source.xhtml#l00021">ExecuteNetworkProgramOptions.hpp:21</a></div></div> +<div class="ttc" id="namespacearmnn_delegate_xhtml_aaab840e387d9a4e7de223fbc8c969eb3"><div class="ttname"><a href="namespacearmnn_delegate.xhtml#aaab840e387d9a4e7de223fbc8c969eb3">armnnDelegate::TfLiteArmnnDelegateCreate</a></div><div class="ttdeci">TfLiteDelegate * TfLiteArmnnDelegateCreate(armnnDelegate::DelegateOptions options)</div></div> +<div class="ttc" id="structarmnn_1_1_empty_optional_xhtml"><div class="ttname"><a href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a></div><div class="ttdoc">EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00032">Optional.hpp:32</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_acde2af8cbbd224a9f94e509ca538a775"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#acde2af8cbbd224a9f94e509ca538a775">InferenceModelInternal::Params::m_PrintIntermediateLayers</a></div><div class="ttdeci">bool m_PrintIntermediateLayers</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00103">InferenceModel.hpp:103</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a9f8881646a38f828f92d3354930c4165"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a9f8881646a38f828f92d3354930c4165">InferenceModelInternal::Params::m_CachedNetworkFilePath</a></div><div class="ttdeci">std::string m_CachedNetworkFilePath</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00110">InferenceModel.hpp:110</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a1697b9751b4ba381f89b8c81cd9dfc3c"><div class="ttname"><a href="struct_execute_network_params.xhtml#a1697b9751b4ba381f89b8c81cd9dfc3c">ExecuteNetworkParams::m_ImportInputsIfAligned</a></div><div class="ttdeci">bool m_ImportInputsIfAligned</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00069">ExecuteNetworkParams.hpp:69</a></div></div> +<div class="ttc" id="class_inference_model_xhtml_a6d789a57513b4b26e31eaed316e45b7f"><div class="ttname"><a href="class_inference_model.xhtml#a6d789a57513b4b26e31eaed316e45b7f">InferenceModel::CreateWorkingMemHandle</a></div><div class="ttdeci">std::unique_ptr< armnn::experimental::IWorkingMemHandle > CreateWorkingMemHandle()</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00796">InferenceModel.hpp:796</a></div></div> +<div class="ttc" id="_i_deserializer_8hpp_xhtml"><div class="ttname"><a href="_i_deserializer_8hpp.xhtml">IDeserializer.hpp</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a7efc68309e76bfefbfa16fe94501b060"><div class="ttname"><a href="struct_execute_network_params.xhtml#a7efc68309e76bfefbfa16fe94501b060">ExecuteNetworkParams::m_EnableLayerDetails</a></div><div class="ttdeci">bool m_EnableLayerDetails</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00037">ExecuteNetworkParams.hpp:37</a></div></div> +<div class="ttc" id="_execute_network_8cpp_xhtml_ac0f2228420376f4db7e1274f2b41667c"><div class="ttname"><a href="_execute_network_8cpp.xhtml#ac0f2228420376f4db7e1274f2b41667c">main</a></div><div class="ttdeci">int main(int argc, const char *argv[])</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_8cpp_source.xhtml#l00996">ExecuteNetwork.cpp:996</a></div></div> +<div class="ttc" id="classarmnn_1_1_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_exception.xhtml">armnn::Exception</a></div><div class="ttdoc">Base class for all ArmNN exceptions so that users can filter to just those. </div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00046">Exceptions.hpp:46</a></div></div> +<div class="ttc" id="_async_execution_callback_8hpp_xhtml"><div class="ttname"><a href="_async_execution_callback_8hpp.xhtml">AsyncExecutionCallback.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_utils_xhtml_ac7bd4ea667375c07718086368507ed44"><div class="ttname"><a href="namespacearmnn_utils.xhtml#ac7bd4ea667375c07718086368507ed44">armnnUtils::TContainer</a></div><div class="ttdeci">mapbox::util::variant< std::vector< float >, std::vector< int >, std::vector< unsigned char >, std::vector< int8_t > > TContainer</div><div class="ttdef"><b>Definition:</b> <a href="_t_container_8hpp_source.xhtml#l00018">TContainer.hpp:18</a></div></div> +<div class="ttc" id="class_inference_model_xhtml_a679e4b22a845c8d7f58f6ca6a5df625f"><div class="ttname"><a href="class_inference_model.xhtml#a679e4b22a845c8d7f58f6ca6a5df625f">InferenceModel::GetInputSize</a></div><div class="ttdeci">unsigned int GetInputSize(unsigned int inputIndex=0u) const</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00582">InferenceModel.hpp:582</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_ae96fc745917a3a0c0de7a818c9a05012"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#ae96fc745917a3a0c0de7a818c9a05012">InferenceModelInternal::Params::m_OutputDetailsToStdOut</a></div><div class="ttdeci">bool m_OutputDetailsToStdOut</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00108">InferenceModel.hpp:108</a></div></div> +<div class="ttc" id="_delegate_options_8hpp_xhtml"><div class="ttname"><a href="_delegate_options_8hpp.xhtml">DelegateOptions.hpp</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_ac609a217f4de4c647422dbb358a5f2ef"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#ac609a217f4de4c647422dbb358a5f2ef">InferenceModelInternal::Params::m_MLGOTuningFilePath</a></div><div class="ttdeci">std::string m_MLGOTuningFilePath</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00112">InferenceModel.hpp:112</a></div></div> +<div class="ttc" id="namespacearmnn_delegate_xhtml_a29bbb05765039d65532d61301b56749e"><div class="ttname"><a href="namespacearmnn_delegate.xhtml#a29bbb05765039d65532d61301b56749e">armnnDelegate::TfLiteArmnnDelegateDelete</a></div><div class="ttdeci">void TfLiteArmnnDelegateDelete(TfLiteDelegate *tfLiteDelegate)</div></div> +<div class="ttc" id="classarmnn_delegate_1_1_delegate_options_xhtml"><div class="ttname"><a href="classarmnn_delegate_1_1_delegate_options.xhtml">armnnDelegate::DelegateOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_delegate_options_8hpp_source.xhtml#l00021">DelegateOptions.hpp:21</a></div></div> +<div class="ttc" id="_execute_network_8cpp_xhtml_afc1c3398fd2de1051edf23a171cfa01b"><div class="ttname"><a href="_execute_network_8cpp.xhtml#afc1c3398fd2de1051edf23a171cfa01b">MainImpl</a></div><div class="ttdeci">int MainImpl(const ExecuteNetworkParams &params, const std::shared_ptr< armnn::IRuntime > &runtime=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_8cpp_source.xhtml#l00379">ExecuteNetwork.cpp:379</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_adc650e032e7fce99f15e2bf903e7167b"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#adc650e032e7fce99f15e2bf903e7167b">InferenceModelInternal::Params::m_NumberOfThreads</a></div><div class="ttdeci">unsigned int m_NumberOfThreads</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00111">InferenceModel.hpp:111</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_ab17deb382179697b4702cc4f909e71f8"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#ab17deb382179697b4702cc4f909e71f8">InferenceModelInternal::Params::m_OutputDetailsOnlyToStdOut</a></div><div class="ttdeci">bool m_OutputDetailsOnlyToStdOut</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00109">InferenceModel.hpp:109</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a4fa312cf0d60fbd3988a7c76ab8e2980"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a4fa312cf0d60fbd3988a7c76ab8e2980">InferenceModelInternal::Params::m_ModelPath</a></div><div class="ttdeci">std::string m_ModelPath</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00091">InferenceModel.hpp:91</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a375ca3cff9f1b005d1412dc5f3cf5b6e"><div class="ttname"><a href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00035">NumericCast.hpp:35</a></div></div> +<div class="ttc" id="classarmnn_1_1experimental_1_1_async_callback_manager_xhtml"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_async_callback_manager.xhtml">armnn::experimental::AsyncCallbackManager</a></div><div class="ttdef"><b>Definition:</b> <a href="_async_execution_callback_8hpp_source.xhtml#l00076">AsyncExecutionCallback.hpp:76</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a6bf2f586c403977d31c7d32d371918cf"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a6bf2f586c403977d31c7d32d371918cf">InferenceModelInternal::Params::m_IsModelBinary</a></div><div class="ttdeci">bool m_IsModelBinary</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00099">InferenceModel.hpp:99</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml_a2d4582aa74998c397bd064ae73745b62"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml#a2d4582aa74998c397bd064ae73745b62">InferenceModelInternal::Params::m_SubgraphId</a></div><div class="ttdeci">size_t m_SubgraphId</div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00097">InferenceModel.hpp:97</a></div></div> +<div class="ttc" id="armnn__delegate_8hpp_xhtml"><div class="ttname"><a href="armnn__delegate_8hpp.xhtml">armnn_delegate.hpp</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_acb9376adc0f7174b7d4295e00315a084"><div class="ttname"><a href="struct_execute_network_params.xhtml#acb9376adc0f7174b7d4295e00315a084">ExecuteNetworkParams::m_ReuseBuffers</a></div><div class="ttdeci">bool m_ReuseBuffers</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00070">ExecuteNetworkParams.hpp:70</a></div></div> +<div class="ttc" id="struct_tensor_printer_xhtml"><div class="ttname"><a href="struct_tensor_printer.xhtml">TensorPrinter</a></div><div class="ttdef"><b>Definition:</b> <a href="_network_execution_utils_8hpp_source.xhtml#l00023">NetworkExecutionUtils.hpp:23</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a077f6963fc555d9d42f98cf9ed3e7e03"><div class="ttname"><a href="struct_execute_network_params.xhtml#a077f6963fc555d9d42f98cf9ed3e7e03">ExecuteNetworkParams::m_QuantizeInput</a></div><div class="ttdeci">bool m_QuantizeInput</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00059">ExecuteNetworkParams.hpp:59</a></div></div> +<div class="ttc" id="_network_execution_utils_8hpp_xhtml"><div class="ttname"><a href="_network_execution_utils_8hpp.xhtml">NetworkExecutionUtils.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_xhtml_a30412a91cadff138686eaeb12f5357cc"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml#a30412a91cadff138686eaeb12f5357cc">armnn::IRuntime::CreationOptions::m_ProfilingOptions</a></div><div class="ttdeci">ExternalProfilingOptions m_ProfilingOptions</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00153">IRuntime.hpp:153</a></div></div> +<div class="ttc" id="struct_inference_model_internal_1_1_params_xhtml"><div class="ttname"><a href="struct_inference_model_internal_1_1_params.xhtml">InferenceModelInternal::Params</a></div><div class="ttdef"><b>Definition:</b> <a href="_inference_model_8hpp_source.xhtml#l00089">InferenceModel.hpp:89</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a93a3ba385cad27c4774e5fe64c025d3d"><div class="ttname"><a href="namespacearmnn.xhtml#a93a3ba385cad27c4774e5fe64c025d3d">armnn::LogSeverity</a></div><div class="ttdeci">LogSeverity</div><div class="ttdef"><b>Definition:</b> <a href="_utils_8hpp_source.xhtml#l00014">Utils.hpp:14</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a2a245a63e87f363df491ad8c35be54c5"><div class="ttname"><a href="struct_execute_network_params.xhtml#a2a245a63e87f363df491ad8c35be54c5">ExecuteNetworkParams::m_InferOutputShape</a></div><div class="ttdeci">bool m_InferOutputShape</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00040">ExecuteNetworkParams.hpp:40</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a86800ee44cdb3d1bfd169ec4200212d2"><div class="ttname"><a href="struct_execute_network_params.xhtml#a86800ee44cdb3d1bfd169ec4200212d2">ExecuteNetworkParams::m_ModelFormat</a></div><div class="ttdeci">std::string m_ModelFormat</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00048">ExecuteNetworkParams.hpp:48</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4aa603905470e2a5b8c13e96b579ef0dba"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4aa603905470e2a5b8c13e96b579ef0dba">armnn::LayerType::Debug</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a26d42007440bb01a1a6d0ab3b5a657ee"><div class="ttname"><a href="struct_execute_network_params.xhtml#a26d42007440bb01a1a6d0ab3b5a657ee">ExecuteNetworkParams::m_EnableProfiling</a></div><div class="ttdeci">bool m_EnableProfiling</div><div class="ttdef"><b>Definition:</b> <a href="_execute_network_params_8hpp_source.xhtml#l00038">ExecuteNetworkParams.hpp:38</a></div></div> +<div class="ttc" id="classarmnn_1_1experimental_1_1_async_callback_manager_xhtml_a9ee5b1dd7d3a6f619d2ed3d97d75d9b1"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_async_callback_manager.xhtml#a9ee5b1dd7d3a6f619d2ed3d97d75d9b1">armnn::experimental::AsyncCallbackManager::GetNotifiedCallback</a></div><div class="ttdeci">std::shared_ptr< AsyncExecutionCallback > GetNotifiedCallback()</div><div class="ttdef"><b>Definition:</b> <a href="_async_execution_callback_8cpp_source.xhtml#l00060">AsyncExecutionCallback.cpp:60</a></div></div> +<div class="ttc" id="struct_execute_network_params_xhtml_a721fa5f104533ca06589330accc2857da979cb18d483aeb3c0c636e340ba011df"><div class="ttname"><a href="struct_execute_network_params.xhtml#a721fa5f104533ca06589330accc2857da979cb18d483aeb3c0c636e340ba011df">ExecuteNetworkParams::TfLiteExecutor::TfliteInterpreter</a></div></div> +</div><!-- fragment --></div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_59425e443f801f1f2fd8bbe4959a3ccf.xhtml">tests</a></li><li class="navelem"><a class="el" href="dir_3502d64799b714c597b8fa7662494b65.xhtml">ExecuteNetwork</a></li><li class="navelem"><a class="el" href="_execute_network_8cpp.xhtml">ExecuteNetwork.cpp</a></li> + <li class="footer">Generated on Tue May 24 2022 11:27:15 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> |