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author | Matthew Sloyan <matthew.sloyan@arm.com> | 2021-08-24 16:27:15 +0100 |
---|---|---|
committer | Matthew Sloyan <matthew.sloyan@arm.com> | 2021-08-24 16:27:40 +0100 |
commit | f86be93b7492b381370cae7bf71eca8572a0cbae (patch) | |
tree | 2a16d9b1892db2305851b2d91850f1c1635390b0 /21.08/_tf_lite_benchmark-_armnn_8cpp_source.xhtml | |
parent | ff4682943c0a64acb22643aac7793ad2ec2a1194 (diff) | |
download | armnn-f86be93b7492b381370cae7bf71eca8572a0cbae.tar.gz |
IVGCVSW-5924 Update 21.08 Doxygen Documents
* Also updated latest symlink.
Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: If9b4e0e52464abdf797b9eb858ae19bcc64c2aea
Diffstat (limited to '21.08/_tf_lite_benchmark-_armnn_8cpp_source.xhtml')
-rw-r--r-- | 21.08/_tf_lite_benchmark-_armnn_8cpp_source.xhtml | 148 |
1 files changed, 148 insertions, 0 deletions
diff --git a/21.08/_tf_lite_benchmark-_armnn_8cpp_source.xhtml b/21.08/_tf_lite_benchmark-_armnn_8cpp_source.xhtml new file mode 100644 index 0000000000..31ce83f13b --- /dev/null +++ b/21.08/_tf_lite_benchmark-_armnn_8cpp_source.xhtml @@ -0,0 +1,148 @@ +<!-- 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/TfLiteBenchmark-Armnn/TfLiteBenchmark-Armnn.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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">21.08</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(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('_tf_lite_benchmark-_armnn_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">TfLiteBenchmark-Armnn.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_tf_lite_benchmark-_armnn_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 © 2020 STMicroelectronics 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 <algorithm></span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include <getopt.h></span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <numeric></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <signal.h></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <string></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <sys/time.h></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_backend_id_8hpp.xhtml">armnn/BackendId.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_backend_registry_8hpp.xhtml">armnn/BackendRegistry.hpp</a>></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_i_runtime_8hpp.xhtml">armnn/IRuntime.hpp</a>></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <<a class="code" href="_numeric_cast_8hpp.xhtml">armnn/utility/NumericCast.hpp</a>></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</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="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment">// Application parameters</span></div><div class="line"><a name="l00021"></a><span class="lineno"><a class="line" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#a05e380d8db6803e902ee10ada180bf9c"> 21</a></span> std::vector<armnn::BackendId> <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#a05e380d8db6803e902ee10ada180bf9c">default_preferred_backends_order</a> = {<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a>};</div><div class="line"><a name="l00022"></a><span class="lineno"><a class="line" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aabb2e0ed0630c978f4049b8a532af9d8"> 22</a></span> std::vector<armnn::BackendId> <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aabb2e0ed0630c978f4049b8a532af9d8">preferred_backends_order</a>;</div><div class="line"><a name="l00023"></a><span class="lineno"><a class="line" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ab08a4340366edc1a450635a28a5f3984"> 23</a></span> std::string <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ab08a4340366edc1a450635a28a5f3984">model_file_str</a>;</div><div class="line"><a name="l00024"></a><span class="lineno"><a class="line" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ad0122c5d8e81deb24ddc15559ab88fa4"> 24</a></span> std::string <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ad0122c5d8e81deb24ddc15559ab88fa4">preferred_backend_str</a>;</div><div class="line"><a name="l00025"></a><span class="lineno"><a class="line" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aaa728eb736da07d15a707029028118de"> 25</a></span> <span class="keywordtype">int</span> <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aaa728eb736da07d15a707029028118de">nb_loops</a> = 1;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"><a class="line" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ae3d72fe1ace913f5f5846f55b98a5959"> 27</a></span> <span class="keywordtype">double</span> <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ae3d72fe1ace913f5f5846f55b98a5959">get_us</a>(<span class="keyword">struct</span> timeval t)</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> {</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keywordflow">return</span> (armnn::numeric_cast<double>(t.tv_sec) *</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  armnn::numeric_cast<double>(1000000) +</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  armnn::numeric_cast<double>(t.tv_usec));</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> }</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"><a class="line" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#add162d6cfc9aa5f0d3edc407066154a2"> 34</a></span> <span class="keywordtype">double</span> <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#add162d6cfc9aa5f0d3edc407066154a2">get_ms</a>(<span class="keyword">struct</span> timeval t)</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> {</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keywordflow">return</span> (armnn::numeric_cast<double>(t.tv_sec) *</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  armnn::numeric_cast<double>(1000) +</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  armnn::numeric_cast<double>(t.tv_usec) / 1000);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> }</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="keyword">static</span> <span class="keywordtype">void</span> print_help(<span class="keywordtype">char</span>** argv)</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> {</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  std::cout <<</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="stringliteral">"Usage: "</span> << argv[0] << <span class="stringliteral">" -m <model .tflite>\n"</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="stringliteral">"\n"</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="stringliteral">"-m --model_file <.tflite file path>: .tflite model to be executed\n"</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="stringliteral">"-b --backend <device>: preferred backend device to run layers on by default. Possible choices: "</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  << <a class="code" href="namespacearmnn.xhtml#ac2807505b850738bc8a1991ce669dd47">armnn::BackendRegistryInstance</a>().<a class="code" href="classarmnn_1_1_backend_registry.xhtml#ae1de2f7ca1db17f45f97155e239b8b45">GetBackendIdsAsString</a>() << <span class="stringliteral">"\n"</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="stringliteral">" (by default CpuAcc, CpuRef)\n"</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="stringliteral">"-l --loops <int>: provide the number of times the inference will be executed\n"</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="stringliteral">" (by default nb_loops=1)\n"</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="stringliteral">"--help: show this help\n"</span>;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  exit(1);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> }</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"><a class="line" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aefcb3f70374ff9b6256aac6e12870399"> 56</a></span> <span class="keywordtype">void</span> <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aefcb3f70374ff9b6256aac6e12870399">process_args</a>(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>** argv)</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> {</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* <span class="keyword">const</span> short_opts = <span class="stringliteral">"m:b:l:h"</span>;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">const</span> option long_opts[] = {</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  {<span class="stringliteral">"model_file"</span>, required_argument, <span class="keyword">nullptr</span>, <span class="charliteral">'m'</span>},</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  {<span class="stringliteral">"backend"</span>, required_argument, <span class="keyword">nullptr</span>, <span class="charliteral">'b'</span>},</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  {<span class="stringliteral">"loops"</span>, required_argument, <span class="keyword">nullptr</span>, <span class="charliteral">'l'</span>},</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  {<span class="stringliteral">"help"</span>, no_argument, <span class="keyword">nullptr</span>, <span class="charliteral">'h'</span>},</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  {<span class="keyword">nullptr</span>, no_argument, <span class="keyword">nullptr</span>, 0}</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  };</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">while</span> (<span class="keyword">true</span>)</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">const</span> <span class="keyword">auto</span> opt = getopt_long(argc, argv, short_opts, long_opts, <span class="keyword">nullptr</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="keywordflow">if</span> (-1 == opt)</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  }</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keywordflow">switch</span> (opt)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">case</span> <span class="charliteral">'m'</span>:</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ab08a4340366edc1a450635a28a5f3984">model_file_str</a> = std::string(optarg);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  std::cout << <span class="stringliteral">"model file set to: "</span> << <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ab08a4340366edc1a450635a28a5f3984">model_file_str</a> << std::endl;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordflow">case</span> <span class="charliteral">'b'</span>:</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ad0122c5d8e81deb24ddc15559ab88fa4">preferred_backend_str</a> = std::string(optarg);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="comment">// Overwrite the backend</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aabb2e0ed0630c978f4049b8a532af9d8">preferred_backends_order</a>.push_back(<a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ad0122c5d8e81deb24ddc15559ab88fa4">preferred_backend_str</a>);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  std::cout << <span class="stringliteral">"backend device set to:"</span> << <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ad0122c5d8e81deb24ddc15559ab88fa4">preferred_backend_str</a> << std::endl;;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordflow">case</span> <span class="charliteral">'l'</span>:</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aaa728eb736da07d15a707029028118de">nb_loops</a> = std::stoi(optarg);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  std::cout << <span class="stringliteral">"benchmark will execute "</span> << <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aaa728eb736da07d15a707029028118de">nb_loops</a> << <span class="stringliteral">" inference(s)"</span> << std::endl;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordflow">case</span> <span class="charliteral">'h'</span>: <span class="comment">// -h or --help</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keywordflow">case</span> <span class="charliteral">'?'</span>: <span class="comment">// Unrecognized option</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  print_help(argv);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  }</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  }</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">if</span> (<a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ab08a4340366edc1a450635a28a5f3984">model_file_str</a>.empty())</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  {</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  print_help(argv);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  }</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> }</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00107"></a><span class="lineno"><a class="line" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#a0ddf1224851353fc92bfbff6f499fa97"> 107</a></span> <span class="keywordtype">int</span> <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#a0ddf1224851353fc92bfbff6f499fa97">main</a>(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>* argv[])</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> {</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  std::vector<double> inferenceTimes;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="comment">// Get options</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aefcb3f70374ff9b6256aac6e12870399">process_args</a>(argc, argv);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="comment">// Create the runtime</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</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="comment">// Create Parser</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <a class="code" href="namespacearmnn_tf_lite_parser.xhtml#af69bedce3c37be895f75146016ba8a17">armnnTfLiteParser::ITfLiteParserPtr</a> armnnparser(<a class="code" href="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser.xhtml#a9932449a89a62cfcfd72a4fedbee1ab7">armnnTfLiteParser::ITfLiteParser::Create</a>());</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="comment">// Create a network</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = armnnparser->CreateNetworkFromBinaryFile(<a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ab08a4340366edc1a450635a28a5f3984">model_file_str</a>.c_str());</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">if</span> (!network)</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  {</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>(<span class="stringliteral">"Failed to create an ArmNN network"</span>);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  }</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="comment">// Optimize the network</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">if</span> (<a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aabb2e0ed0630c978f4049b8a532af9d8">preferred_backends_order</a>.size() == 0)</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>  <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aabb2e0ed0630c978f4049b8a532af9d8">preferred_backends_order</a> = <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#a05e380d8db6803e902ee10ada180bf9c">default_preferred_backends_order</a>;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  }</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optimizedNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(*network,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aabb2e0ed0630c978f4049b8a532af9d8">preferred_backends_order</a>,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  runtime->GetDeviceSpec());</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <a class="code" href="namespacearmnn.xhtml#a0d8160388a127c1a23b37bc88dc6e2ec">armnn::NetworkId</a> networkId;</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>  <span class="comment">// Load the network in to the runtime</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  runtime->LoadNetwork(networkId, std::move(optimizedNet));</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="comment">// Check the number of subgraph</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keywordflow">if</span> (armnnparser->GetSubgraphCount() != 1)</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  {</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  std::cout << <span class="stringliteral">"Model with more than 1 subgraph is not supported by this benchmark application.\n"</span>;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  exit(0);</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  }</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keywordtype">size_t</span> subgraphId = 0;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="comment">// Set up the input network</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  std::cout << <span class="stringliteral">"\nModel information:"</span> << std::endl;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  std::vector<armnnTfLiteParser::BindingPointInfo> inputBindings;</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  std::vector<armnn::TensorInfo> inputTensorInfos;</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  std::vector<std::string> inputTensorNames = armnnparser->GetSubgraphInputTensorNames(subgraphId);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < inputTensorNames.size() ; i++)</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  {</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  std::cout << <span class="stringliteral">"inputTensorNames["</span> << i << <span class="stringliteral">"] = "</span> << inputTensorNames[i] << std::endl;</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <a class="code" href="namespacearmnn_tf_lite_parser.xhtml#a9084adbf804022c874039ad40d1939e9">armnnTfLiteParser::BindingPointInfo</a> inputBinding = armnnparser->GetNetworkInputBindingInfo(</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  subgraphId,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  inputTensorNames[i]);</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo = runtime->GetInputTensorInfo(networkId, inputBinding.first);</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  inputBindings.push_back(inputBinding);</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  inputTensorInfos.push_back(inputTensorInfo);</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> </div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="comment">// Set up the output network</span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  std::vector<armnnTfLiteParser::BindingPointInfo> outputBindings;</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  std::vector<armnn::TensorInfo> outputTensorInfos;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  std::vector<std::string> outputTensorNames = armnnparser->GetSubgraphOutputTensorNames(subgraphId);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < outputTensorNames.size() ; i++)</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::cout << <span class="stringliteral">"outputTensorNames["</span> << i << <span class="stringliteral">"] = "</span> << outputTensorNames[i] << std::endl;</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <a class="code" href="namespacearmnn_tf_lite_parser.xhtml#a9084adbf804022c874039ad40d1939e9">armnnTfLiteParser::BindingPointInfo</a> outputBinding = armnnparser->GetNetworkOutputBindingInfo(</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  subgraphId,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  outputTensorNames[i]);</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = runtime->GetOutputTensorInfo(networkId, outputBinding.first);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  outputBindings.push_back(outputBinding);</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  outputTensorInfos.push_back(outputTensorInfo);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  }</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="comment">// Allocate input tensors</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> nb_inputs = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(inputTensorInfos.size());</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a> inputTensors;</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  std::vector<std::vector<float>> in;</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0 ; i < nb_inputs ; i++)</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>  std::vector<float> in_data(inputTensorInfos.at(i).GetNumElements());</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  in.push_back(in_data);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  inputTensors.push_back({ inputBindings[i].first, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(inputBindings[i].second, in[i].data()) });</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>  <span class="comment">// Allocate output tensors</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> nb_ouputs = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(outputTensorInfos.size());</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a> outputTensors;</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  std::vector<std::vector<float>> out;</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < nb_ouputs ; i++)</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  {</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  std::vector<float> out_data(outputTensorInfos.at(i).GetNumElements());</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  out.push_back(out_data);</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  outputTensors.push_back({ outputBindings[i].first, <a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(outputBindings[i].second, out[i].data()) });</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  }</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="comment">// Run the inferences</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  std::cout << <span class="stringliteral">"\ninferences are running: "</span> << std::flush;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0 ; i < <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aaa728eb736da07d15a707029028118de">nb_loops</a> ; i++)</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  {</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keyword">struct </span>timeval start_time, stop_time;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  gettimeofday(&start_time, <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> </div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  runtime->EnqueueWorkload(networkId, inputTensors, outputTensors);</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>  gettimeofday(&stop_time, <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  inferenceTimes.push_back((<a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ae3d72fe1ace913f5f5846f55b98a5959">get_us</a>(stop_time) - <a class="code" href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ae3d72fe1ace913f5f5846f55b98a5959">get_us</a>(start_time)));</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  std::cout << <span class="stringliteral">"# "</span> << std::flush;</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  }</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keyword">auto</span> maxInfTime = *std::max_element(inferenceTimes.begin(), inferenceTimes.end());</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="keyword">auto</span> minInfTime = *std::min_element(inferenceTimes.begin(), inferenceTimes.end());</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keyword">auto</span> avgInfTime = accumulate(inferenceTimes.begin(), inferenceTimes.end(), 0.0) /</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">double</span>>(inferenceTimes.size());</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  std::cout << <span class="stringliteral">"\n\ninference time: "</span>;</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  std::cout << <span class="stringliteral">"min="</span> << minInfTime << <span class="stringliteral">"us "</span>;</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  std::cout << <span class="stringliteral">"max="</span> << maxInfTime << <span class="stringliteral">"us "</span>;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  std::cout << <span class="stringliteral">"avg="</span> << avgInfTime << <span class="stringliteral">"us"</span> << std::endl;</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> </div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> }</div><div class="ttc" id="classarmnn_1_1_i_runtime_xhtml_ad44ecd3700748dc30dc4bbe34ba5bde7"><div class="ttname"><a href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a></div><div class="ttdeci">static IRuntimePtr Create(const CreationOptions &options)</div><div class="ttdef"><b>Definition:</b> <a href="_runtime_8cpp_source.xhtml#l00039">Runtime.cpp:39</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a></div><div class="ttdoc">CPU Execution: Reference C++ kernels. </div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr< IRuntime, void(*)(IRuntime *runtime)> IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00030">IRuntime.hpp:30</a></div></div> +<div class="ttc" id="_i_runtime_8hpp_xhtml"><div class="ttname"><a href="_i_runtime_8hpp.xhtml">IRuntime.hpp</a></div></div> +<div class="ttc" id="_tf_lite_benchmark-_armnn_8cpp_xhtml_aaa728eb736da07d15a707029028118de"><div class="ttname"><a href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aaa728eb736da07d15a707029028118de">nb_loops</a></div><div class="ttdeci">int nb_loops</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_benchmark-_armnn_8cpp_source.xhtml#l00025">TfLiteBenchmark-Armnn.cpp:25</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ac2807505b850738bc8a1991ce669dd47"><div class="ttname"><a href="namespacearmnn.xhtml#ac2807505b850738bc8a1991ce669dd47">armnn::BackendRegistryInstance</a></div><div class="ttdeci">BackendRegistry & BackendRegistryInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.xhtml#l00013">BackendRegistry.cpp:13</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00360">Tensor.hpp:360</a></div></div> +<div class="ttc" id="namespacearmnn_tf_lite_parser_xhtml_af69bedce3c37be895f75146016ba8a17"><div class="ttname"><a href="namespacearmnn_tf_lite_parser.xhtml#af69bedce3c37be895f75146016ba8a17">armnnTfLiteParser::ITfLiteParserPtr</a></div><div class="ttdeci">std::unique_ptr< ITfLiteParser, void(*)(ITfLiteParser *parser)> ITfLiteParserPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_tf_lite_parser_8hpp_source.xhtml#l00024">ITfLiteParser.hpp:24</a></div></div> +<div class="ttc" id="classarmnn_1_1_backend_registry_xhtml_ae1de2f7ca1db17f45f97155e239b8b45"><div class="ttname"><a href="classarmnn_1_1_backend_registry.xhtml#ae1de2f7ca1db17f45f97155e239b8b45">armnn::BackendRegistry::GetBackendIdsAsString</a></div><div class="ttdeci">std::string GetBackendIdsAsString() const</div><div class="ttdef"><b>Definition:</b> <a href="_backend_registry_8cpp_source.xhtml#l00083">BackendRegistry.cpp:83</a></div></div> +<div class="ttc" id="_backend_registry_8hpp_xhtml"><div class="ttname"><a href="_backend_registry_8hpp.xhtml">BackendRegistry.hpp</a></div></div> +<div class="ttc" id="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser_xhtml_a9932449a89a62cfcfd72a4fedbee1ab7"><div class="ttname"><a href="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser.xhtml#a9932449a89a62cfcfd72a4fedbee1ab7">armnnTfLiteParser::ITfLiteParser::Create</a></div><div class="ttdeci">static ITfLiteParserPtr Create(const armnn::Optional< TfLiteParserOptions > &options=armnn::EmptyOptional())</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_parser_8cpp_source.xhtml#l00064">TfLiteParser.cpp:64</a></div></div> +<div class="ttc" id="_numeric_cast_8hpp_xhtml"><div class="ttname"><a href="_numeric_cast_8hpp.xhtml">NumericCast.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00319">Tensor.hpp:319</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="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01613">Network.cpp:1613</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a0d8160388a127c1a23b37bc88dc6e2ec"><div class="ttname"><a href="namespacearmnn.xhtml#a0d8160388a127c1a23b37bc88dc6e2ec">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00024">IRuntime.hpp:24</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00327">Tensor.hpp:327</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00361">Tensor.hpp:361</a></div></div> +<div class="ttc" id="_tf_lite_benchmark-_armnn_8cpp_xhtml_ae3d72fe1ace913f5f5846f55b98a5959"><div class="ttname"><a href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ae3d72fe1ace913f5f5846f55b98a5959">get_us</a></div><div class="ttdeci">double get_us(struct timeval t)</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_benchmark-_armnn_8cpp_source.xhtml#l00027">TfLiteBenchmark-Armnn.cpp:27</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div> +<div class="ttc" id="_tf_lite_benchmark-_armnn_8cpp_xhtml_aefcb3f70374ff9b6256aac6e12870399"><div class="ttname"><a href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aefcb3f70374ff9b6256aac6e12870399">process_args</a></div><div class="ttdeci">void process_args(int argc, char **argv)</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_benchmark-_armnn_8cpp_source.xhtml#l00056">TfLiteBenchmark-Armnn.cpp:56</a></div></div> +<div class="ttc" id="_tf_lite_benchmark-_armnn_8cpp_xhtml_ab08a4340366edc1a450635a28a5f3984"><div class="ttname"><a href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ab08a4340366edc1a450635a28a5f3984">model_file_str</a></div><div class="ttdeci">std::string model_file_str</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_benchmark-_armnn_8cpp_source.xhtml#l00023">TfLiteBenchmark-Armnn.cpp:23</a></div></div> +<div class="ttc" id="_backend_id_8hpp_xhtml"><div class="ttname"><a href="_backend_id_8hpp.xhtml">BackendId.hpp</a></div></div> +<div class="ttc" id="_tf_lite_benchmark-_armnn_8cpp_xhtml_a0ddf1224851353fc92bfbff6f499fa97"><div class="ttname"><a href="_tf_lite_benchmark-_armnn_8cpp.xhtml#a0ddf1224851353fc92bfbff6f499fa97">main</a></div><div class="ttdeci">int main(int argc, char *argv[])</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_benchmark-_armnn_8cpp_source.xhtml#l00107">TfLiteBenchmark-Armnn.cpp:107</a></div></div> +<div class="ttc" id="_tf_lite_benchmark-_armnn_8cpp_xhtml_a05e380d8db6803e902ee10ada180bf9c"><div class="ttname"><a href="_tf_lite_benchmark-_armnn_8cpp.xhtml#a05e380d8db6803e902ee10ada180bf9c">default_preferred_backends_order</a></div><div class="ttdeci">std::vector< armnn::BackendId > default_preferred_backends_order</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_benchmark-_armnn_8cpp_source.xhtml#l00021">TfLiteBenchmark-Armnn.cpp:21</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#l00101">IRuntime.hpp:101</a></div></div> +<div class="ttc" id="_tf_lite_benchmark-_armnn_8cpp_xhtml_add162d6cfc9aa5f0d3edc407066154a2"><div class="ttname"><a href="_tf_lite_benchmark-_armnn_8cpp.xhtml#add162d6cfc9aa5f0d3edc407066154a2">get_ms</a></div><div class="ttdeci">double get_ms(struct timeval t)</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_benchmark-_armnn_8cpp_source.xhtml#l00034">TfLiteBenchmark-Armnn.cpp:34</a></div></div> +<div class="ttc" id="_tf_lite_benchmark-_armnn_8cpp_xhtml_ad0122c5d8e81deb24ddc15559ab88fa4"><div class="ttname"><a href="_tf_lite_benchmark-_armnn_8cpp.xhtml#ad0122c5d8e81deb24ddc15559ab88fa4">preferred_backend_str</a></div><div class="ttdeci">std::string preferred_backend_str</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_benchmark-_armnn_8cpp_source.xhtml#l00024">TfLiteBenchmark-Armnn.cpp:24</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="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a></div><div class="ttdoc">CPU Execution: NEON: ArmCompute. </div></div> +<div class="ttc" id="_tf_lite_benchmark-_armnn_8cpp_xhtml_aabb2e0ed0630c978f4049b8a532af9d8"><div class="ttname"><a href="_tf_lite_benchmark-_armnn_8cpp.xhtml#aabb2e0ed0630c978f4049b8a532af9d8">preferred_backends_order</a></div><div class="ttdeci">std::vector< armnn::BackendId > preferred_backends_order</div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_benchmark-_armnn_8cpp_source.xhtml#l00022">TfLiteBenchmark-Armnn.cpp:22</a></div></div> +<div class="ttc" id="namespacearmnn_tf_lite_parser_xhtml_a9084adbf804022c874039ad40d1939e9"><div class="ttname"><a href="namespacearmnn_tf_lite_parser.xhtml#a9084adbf804022c874039ad40d1939e9">armnnTfLiteParser::BindingPointInfo</a></div><div class="ttdeci">armnn::BindingPointInfo BindingPointInfo</div><div class="ttdef"><b>Definition:</b> <a href="_i_tf_lite_parser_8hpp_source.xhtml#l00020">ITfLiteParser.hpp:20</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="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00172">INetwork.hpp:172</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_a7a49a416e46eae238f261ac197dd364.xhtml">TfLiteBenchmark-Armnn</a></li><li class="navelem"><a class="el" href="_tf_lite_benchmark-_armnn_8cpp.xhtml">TfLiteBenchmark-Armnn.cpp</a></li> + <li class="footer">Generated on Tue Aug 24 2021 16:18:45 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> |