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| author | Jan Eilers <jan.eilers@arm.com> | 2021-02-25 17:44:00 +0000 |
|---|---|---|
| committer | Jan Eilers <jan.eilers@arm.com> | 2021-02-25 18:27:49 +0000 |
| commit | fd627ffaec8fd8801d980b4c91ee7c0607ab6aaf (patch) | |
| tree | eb4bc8f9b411f30c7655616142b5a4bdd3a1acd0 /21.02/_parser_flatbuffers_fixture_8hpp_source.xhtml | |
| parent | fb14ebbd68e04876809145296af96f6f41857418 (diff) | |
| download | armnn-fd627ffaec8fd8801d980b4c91ee7c0607ab6aaf.tar.gz | |
IVGCVSW-5687 Update Doxygen Docu
* Update Doxygen Documentation for 21.02 release
Signed-off-by: Jan Eilers <jan.eilers@arm.com>
Change-Id: I9ed2f9caab038836ea99d7b378d7899fe431a4e5
Diffstat (limited to '21.02/_parser_flatbuffers_fixture_8hpp_source.xhtml')
| -rw-r--r-- | 21.02/_parser_flatbuffers_fixture_8hpp_source.xhtml | 177 |
1 files changed, 177 insertions, 0 deletions
diff --git a/21.02/_parser_flatbuffers_fixture_8hpp_source.xhtml b/21.02/_parser_flatbuffers_fixture_8hpp_source.xhtml new file mode 100644 index 0000000000..e33d1b2d22 --- /dev/null +++ b/21.02/_parser_flatbuffers_fixture_8hpp_source.xhtml @@ -0,0 +1,177 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/armnnTfLiteParser/test/ParserFlatbuffersFixture.hpp 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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">21.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_parser_flatbuffers_fixture_8hpp_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">ParserFlatbuffersFixture.hpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_parser_flatbuffers_fixture_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_schema_8hpp.xhtml">Schema.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_descriptors_8hpp.xhtml">armnn/Descriptors.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_i_runtime_8hpp.xhtml">armnn/IRuntime.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_types_utils_8hpp.xhtml">armnn/TypesUtils.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_backend_registry_8hpp.xhtml">armnn/BackendRegistry.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_assert_8hpp.xhtml">armnn/utility/Assert.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_i_tf_lite_parser_8hpp.xhtml">armnnTfLiteParser/ITfLiteParser.hpp</a>></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <<a class="code" href="_resolve_type_8hpp.xhtml">ResolveType.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="preprocessor">#include <<a class="code" href="_tensor_helpers_8hpp.xhtml">test/TensorHelpers.hpp</a>></span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> </div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="preprocessor">#include <fmt/format.h></span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> </div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include "flatbuffers/idl.h"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include "flatbuffers/util.h"</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include "flatbuffers/flexbuffers.h"</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include <schema_generated.h></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 <iostream></span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keyword">using</span> <a class="code" href="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser.xhtml">armnnTfLiteParser::ITfLiteParser</a>;</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="keyword">using</span> <a class="code" href="namespacearmnn_tf_lite_parser.xhtml#af69bedce3c37be895f75146016ba8a17">armnnTfLiteParser::ITfLiteParserPtr</a>;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"><a class="line" href="_parser_flatbuffers_fixture_8hpp.xhtml#ac3486e6c1a291aa67efd8b280ffb83cc"> 35</a></span> <span class="keyword">using</span> <a class="code" href="_parser_flatbuffers_serialize_fixture_8hpp.xhtml#a15c20a0693cd3fc4d85565e2f920d8ef">TensorRawPtr</a> = <span class="keyword">const</span> tflite::TensorT *;</div><div class="line"><a name="l00036"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml"> 36</a></span> <span class="keyword">struct </span><a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div><div class="line"><a name="l00038"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#ad748cc696b0f92b478ba4f145e966754"> 38</a></span>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad748cc696b0f92b478ba4f145e966754">ParserFlatbuffersFixture</a>() :</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac">m_Parser</a>(nullptr, &<a class="code" href="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser.xhtml">ITfLiteParser</a>::Destroy),</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#aefd699eb0838261fbe9770d511f63f24">m_Runtime</a>(<a class="code" href="namespacearmnn.xhtml">armnn</a>::IRuntime::Create(<a class="code" href="namespacearmnn.xhtml">armnn</a>::IRuntime::CreationOptions())),</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a0b81fa34e5ca505b9880755f702fafe7">m_NetworkIdentifier</a>(-1)</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>  ITfLiteParser::TfLiteParserOptions options;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  options.m_StandInLayerForUnsupported = <span class="keyword">true</span>;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  options.m_InferAndValidate = <span class="keyword">true</span>;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac">m_Parser</a>.reset(ITfLiteParser::CreateRaw(<a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional<ITfLiteParser::TfLiteParserOptions></a>(options)));</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  }</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a9fbc789fd0aca759cb40737fdeb8ed63"> 50</a></span>  std::vector<uint8_t> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a9fbc789fd0aca759cb40737fdeb8ed63">m_GraphBinary</a>;</div><div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a803c86dca3acef653c1cc481a27be7a9"> 51</a></span>  std::string <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a803c86dca3acef653c1cc481a27be7a9">m_JsonString</a>;</div><div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac"> 52</a></span>  <a class="code" href="namespacearmnn_tf_lite_parser.xhtml#af69bedce3c37be895f75146016ba8a17">ITfLiteParserPtr</a> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac">m_Parser</a>;</div><div class="line"><a name="l00053"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#aefd699eb0838261fbe9770d511f63f24"> 53</a></span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#aefd699eb0838261fbe9770d511f63f24">m_Runtime</a>;</div><div class="line"><a name="l00054"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a0b81fa34e5ca505b9880755f702fafe7"> 54</a></span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a0b81fa34e5ca505b9880755f702fafe7">m_NetworkIdentifier</a>;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="comment"></span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"> /// If the single-input-single-output overload of Setup() is called, these will store the input and output name</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> /// so they don't need to be passed to the single-input-single-output overload of RunTest().</span></div><div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a2f8365158b7c75e43897fbe804b7fc4f"> 58</a></span> <span class="comment"></span> std::string <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a2f8365158b7c75e43897fbe804b7fc4f">m_SingleInputName</a>;</div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#add32b4d209a5b5d6ea6db94b9894ad75"> 59</a></span>  std::string <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#add32b4d209a5b5d6ea6db94b9894ad75">m_SingleOutputName</a>;</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a769404f2985a027a0d626fedfd4de1e9"> 61</a></span>  <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a769404f2985a027a0d626fedfd4de1e9">Setup</a>()</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>  <span class="keywordtype">bool</span> ok = <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a69fc8e7f42386fa67732cb8c98d8b024">ReadStringToBinary</a>();</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordflow">if</span> (!ok) {</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>(<span class="stringliteral">"LoadNetwork failed while reading binary input"</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>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network =</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  m_Parser->CreateNetworkFromBinary(m_GraphBinary);</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> (!network) {</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>(<span class="stringliteral">"The parser failed to create an ArmNN network"</span>);</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> </div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keyword">auto</span> optimized = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*network, { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a> },</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  m_Runtime->GetDeviceSpec());</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  std::string errorMessage;</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>  <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a> ret = m_Runtime->LoadNetwork(m_NetworkIdentifier, move(optimized), errorMessage);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordflow">if</span> (ret != <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">armnn::Status::Success</a>)</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>(</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  fmt::format(<span class="stringliteral">"The runtime failed to load the network. "</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="stringliteral">"Error was: {}. in {} [{}:{}]"</span>,</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  errorMessage,</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  __func__,</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  __FILE__,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  __LINE__));</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>  }</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div><div class="line"><a name="l00093"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a2bb4ea256fbbf6d53068ca93bb4bc95c"> 93</a></span>  <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a2bb4ea256fbbf6d53068ca93bb4bc95c">SetupSingleInputSingleOutput</a>(<span class="keyword">const</span> std::string& inputName, <span class="keyword">const</span> std::string& outputName)</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  {</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="comment">// Store the input and output name so they don't need to be passed to the single-input-single-output RunTest().</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  m_SingleInputName = inputName;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  m_SingleOutputName = outputName;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a769404f2985a027a0d626fedfd4de1e9">Setup</a>();</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  }</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div><div class="line"><a name="l00101"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a69fc8e7f42386fa67732cb8c98d8b024"> 101</a></span>  <span class="keywordtype">bool</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a69fc8e7f42386fa67732cb8c98d8b024">ReadStringToBinary</a>()</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>  std::string schemafile(<a class="code" href="_schema_8hpp.xhtml#a6747d3548926a8130c42fb3398027acf">g_TfLiteSchemaText</a>, <a class="code" href="_schema_8hpp.xhtml#a6747d3548926a8130c42fb3398027acf">g_TfLiteSchemaText</a> + <a class="code" href="_schema_8hpp.xhtml#abe07dadc9cf942cbf847470102a8980e">g_TfLiteSchemaText_len</a>);</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>  <span class="comment">// parse schema first, so we can use it to parse the data after</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  flatbuffers::Parser parser;</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="keywordtype">bool</span> ok = parser.Parse(schemafile.c_str());</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(ok, <span class="stringliteral">"Failed to parse schema file"</span>);</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>  ok &= parser.Parse(m_JsonString.c_str());</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(ok, <span class="stringliteral">"Failed to parse json input"</span>);</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="keywordflow">if</span> (!ok)</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  {</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  }</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </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="keyword">const</span> uint8_t * bufferPtr = parser.builder_.GetBufferPointer();</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordtype">size_t</span> size = <span class="keyword">static_cast<</span><span class="keywordtype">size_t</span><span class="keyword">></span>(parser.builder_.GetSize());</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  m_GraphBinary.assign(bufferPtr, bufferPtr+size);</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  }</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keywordflow">return</span> ok;</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="comment"></span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="comment"> /// Executes the network with the given input tensor and checks the result against the given output tensor.</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="comment"> /// This assumes the network has a single input and a single output.</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="comment"></span> <span class="keyword">template</span> <std::size_t NumOutputDimensions,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">RunTest</a>(<span class="keywordtype">size_t</span> subgraphId,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keyword">const</span> std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType></a>>& inputData,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keyword">const</span> std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType></a>>& expectedOutputData);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="comment"></span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="comment"> /// Executes the network with the given input tensors and checks the results against the given output tensors.</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="comment"> /// This overload supports multiple inputs and multiple outputs, identified by name.</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="comment"></span> <span class="keyword">template</span> <std::size_t NumOutputDimensions,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">RunTest</a>(<span class="keywordtype">size_t</span> subgraphId,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType></a>>>& inputData,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType></a>>>& expectedOutputData);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment"></span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment"> /// Multiple Inputs, Multiple Outputs w/ Variable Datatypes and different dimension sizes.</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="comment"> /// Executes the network with the given input tensors and checks the results against the given output tensors.</span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="comment"> /// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="comment"> /// the input datatype to be different to the output</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="comment"></span> <span class="keyword">template</span> <std::size_t NumOutputDimensions,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType1,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType2></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">RunTest</a>(<span class="keywordtype">size_t</span> subgraphId,</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType1></a>>>& inputData,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType2></a>>>& expectedOutputData,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keywordtype">bool</span> isDynamic = <span class="keyword">false</span>);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="comment"></span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="comment"> /// Multiple Inputs with different DataTypes, Multiple Outputs w/ Variable DataTypes</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="comment"> /// Executes the network with the given input tensors and checks the results against the given output tensors.</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="comment"> /// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="comment"> /// the input datatype to be different to the output</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="comment"></span> <span class="keyword">template</span> <std::size_t NumOutputDimensions,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> inputType1,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> inputType2,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> outputType></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">RunTest</a>(<span class="keywordtype">size_t</span> subgraphId,</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<inputType1></a>>>& input1Data,</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<inputType2></a>>>& input2Data,</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<outputType></a>>>& expectedOutputData);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> <span class="comment"></span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="comment"> /// Multiple Inputs, Multiple Outputs w/ Variable Datatypes and different dimension sizes.</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> <span class="comment"> /// Executes the network with the given input tensors and checks the results against the given output tensors.</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> <span class="comment"> /// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> <span class="comment"> /// the input datatype to be different to the output</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> <span class="comment"></span> <span class="keyword">template</span><<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType1,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> ArmnnType2></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">RunTest</a>(std::size_t subgraphId,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType1></a>>>& inputData,</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<ArmnnType2></a>>>& expectedOutputData);</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> </div><div class="line"><a name="l00178"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#ab77021b45ae36342092fac96ec3534b7"> 178</a></span>  <span class="keyword">static</span> <span class="keyword">inline</span> std::string <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ab77021b45ae36342092fac96ec3534b7">GenerateDetectionPostProcessJsonString</a>(</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a>& descriptor)</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  {</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  flexbuffers::Builder detectPostProcess;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  detectPostProcess.Map([&]() {</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  detectPostProcess.Bool(<span class="stringliteral">"use_regular_nms"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">m_UseRegularNms</a>);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  detectPostProcess.Int(<span class="stringliteral">"max_detections"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">m_MaxDetections</a>);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  detectPostProcess.Int(<span class="stringliteral">"max_classes_per_detection"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a9ae2c9796692ebeafe19a4d3f09c8ea8">m_MaxClassesPerDetection</a>);</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  detectPostProcess.Int(<span class="stringliteral">"detections_per_class"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7e2f87544b8bc7e497e1dec8d3ca4055">m_DetectionsPerClass</a>);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  detectPostProcess.Int(<span class="stringliteral">"num_classes"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a3a04b0ccee4bb2f21721ee5045e83df4">m_NumClasses</a>);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  detectPostProcess.Float(<span class="stringliteral">"nms_score_threshold"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a4392dd6b4862cc9cf95ae8f1001ba592">m_NmsScoreThreshold</a>);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  detectPostProcess.Float(<span class="stringliteral">"nms_iou_threshold"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a53c8a7f33a40e1e240256bcfcf41b101">m_NmsIouThreshold</a>);</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  detectPostProcess.Float(<span class="stringliteral">"h_scale"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#aa61510cbd529870182e918ac6e8b9d72">m_ScaleH</a>);</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  detectPostProcess.Float(<span class="stringliteral">"w_scale"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ab509802c659de19929f18bad14a35c58">m_ScaleW</a>);</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  detectPostProcess.Float(<span class="stringliteral">"x_scale"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae64523937ea910030ad66fee6fddd51f">m_ScaleX</a>);</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  detectPostProcess.Float(<span class="stringliteral">"y_scale"</span>, descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7a2156ec7d9c012ce00bbcc6afcb9028">m_ScaleY</a>);</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  });</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  detectPostProcess.Finish();</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// Create JSON string</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  std::stringstream strStream;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  std::vector<uint8_t> buffer = detectPostProcess.GetBuffer();</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  std::copy(buffer.begin(), buffer.end(),std::ostream_iterator<int>(strStream,<span class="stringliteral">","</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="keywordflow">return</span> strStream.str();</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  }</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00205"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a131f9fe1b625ce21cfe4285136ecfa20"> 205</a></span>  <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a131f9fe1b625ce21cfe4285136ecfa20">CheckTensors</a>(<span class="keyword">const</span> <a class="code" href="_parser_flatbuffers_serialize_fixture_8hpp.xhtml#a15c20a0693cd3fc4d85565e2f920d8ef">TensorRawPtr</a>& tensors, <span class="keywordtype">size_t</span> shapeSize, <span class="keyword">const</span> std::vector<int32_t>& shape,</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  tflite::TensorType tensorType, uint32_t buffer, <span class="keyword">const</span> std::string& name,</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keyword">const</span> std::vector<float>& min, <span class="keyword">const</span> std::vector<float>& max,</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keyword">const</span> std::vector<float>& scale, <span class="keyword">const</span> std::vector<int64_t>& zeroPoint)</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  {</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  BOOST_CHECK(tensors);</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  BOOST_CHECK_EQUAL(shapeSize, tensors->shape.size());</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  BOOST_CHECK_EQUAL_COLLECTIONS(shape.begin(), shape.end(), tensors->shape.begin(), tensors->shape.end());</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  BOOST_CHECK_EQUAL(tensorType, tensors->type);</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  BOOST_CHECK_EQUAL(buffer, tensors->buffer);</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  BOOST_CHECK_EQUAL(name, tensors->name);</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  BOOST_CHECK(tensors->quantization);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  BOOST_CHECK_EQUAL_COLLECTIONS(min.begin(), min.end(), tensors->quantization.get()->min.begin(),</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  tensors->quantization.get()->min.end());</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  BOOST_CHECK_EQUAL_COLLECTIONS(max.begin(), max.end(), tensors->quantization.get()->max.begin(),</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  tensors->quantization.get()->max.end());</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  BOOST_CHECK_EQUAL_COLLECTIONS(scale.begin(), scale.end(), tensors->quantization.get()->scale.begin(),</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  tensors->quantization.get()->scale.end());</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  BOOST_CHECK_EQUAL_COLLECTIONS(zeroPoint.begin(), zeroPoint.end(),</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  tensors->quantization.get()->zero_point.begin(),</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  tensors->quantization.get()->zero_point.end());</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="keyword">private</span>:<span class="comment"></span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="comment"> /// Fills the InputTensors with given input data</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <span class="comment"></span> <span class="keyword">template</span> <armnn::DataType dataType></div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="keywordtype">void</span> FillInputTensors(<a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a>& inputTensors,</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<dataType></a>>>& inputData,</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="keywordtype">size_t</span> subgraphId);</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> };</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> <span class="comment"></span></div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> <span class="comment">/// Fills the InputTensors with given input data</span></div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> <span class="comment"></span><span class="keyword">template</span> <armnn::DataType dataType></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="keywordtype">void</span> ParserFlatbuffersFixture::FillInputTensors(</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a>& inputTensors,</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<dataType></a>>>& inputData,</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keywordtype">size_t</span> subgraphId)</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> {</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : inputData)</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  {</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <a class="code" href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">armnn::BindingPointInfo</a> bindingInfo = <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac">m_Parser</a>->GetNetworkInputBindingInfo(subgraphId, it.first);</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <a class="code" href="namespacearmnn.xhtml#a9667bea652e3a5ef81fea59b71513ced">armnn::VerifyTensorInfoDataType</a>(bindingInfo.second, dataType);</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  inputTensors.push_back({ bindingInfo.first, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(bindingInfo.second, it.second.data()) });</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> <span class="comment"></span></div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <span class="comment">/// Single Input, Single Output</span></div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> <span class="comment">/// Executes the network with the given input tensor and checks the result against the given output tensor.</span></div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> <span class="comment">/// This overload assumes the network has a single input and a single output.</span></div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> <span class="comment"></span><span class="keyword">template</span> <std::size_t NumOutputDimensions,</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> armnnType></div><div class="line"><a name="l00256"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a"> 256</a></span> <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">ParserFlatbuffersFixture::RunTest</a>(<span class="keywordtype">size_t</span> subgraphId,</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keyword">const</span> std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<armnnType></a>>& inputData,</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keyword">const</span> std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<armnnType></a>>& expectedOutputData)</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> {</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  RunTest<NumOutputDimensions, armnnType>(subgraphId,</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  { { <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a2f8365158b7c75e43897fbe804b7fc4f">m_SingleInputName</a>, inputData } },</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  { { <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#add32b4d209a5b5d6ea6db94b9894ad75">m_SingleOutputName</a>, expectedOutputData } });</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> }</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> <span class="comment"></span></div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> <span class="comment">/// Multiple Inputs, Multiple Outputs</span></div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> <span class="comment">/// Executes the network with the given input tensors and checks the results against the given output tensors.</span></div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> <span class="comment">/// This overload supports multiple inputs and multiple outputs, identified by name.</span></div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> <span class="comment"></span><span class="keyword">template</span> <std::size_t NumOutputDimensions,</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> armnnType></div><div class="line"><a name="l00270"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a515ada4931d7b8d8f9c9b84d1090ada1"> 270</a></span> <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">ParserFlatbuffersFixture::RunTest</a>(<span class="keywordtype">size_t</span> subgraphId,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<armnnType></a>>>& inputData,</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<armnnType></a>>>& expectedOutputData)</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> {</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  RunTest<NumOutputDimensions, armnnType, armnnType>(subgraphId, inputData, expectedOutputData);</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="comment"></span></div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> <span class="comment">/// Multiple Inputs, Multiple Outputs w/ Variable Datatypes</span></div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> <span class="comment">/// Executes the network with the given input tensors and checks the results against the given output tensors.</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> <span class="comment">/// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for</span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> <span class="comment">/// the input datatype to be different to the output</span></div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="comment"></span><span class="keyword">template</span> <std::size_t NumOutputDimensions,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> armnnType1,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> armnnType2></div><div class="line"><a name="l00284"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a4bd9d97856a0c52dc07afdea7e7831c9"> 284</a></span> <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">ParserFlatbuffersFixture::RunTest</a>(<span class="keywordtype">size_t</span> subgraphId,</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<armnnType1></a>>>& inputData,</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<armnnType2></a>>>& expectedOutputData,</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keywordtype">bool</span> isDynamic)</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> {</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keyword">using</span> DataType2 = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<armnnType2></a>;</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="comment">// Setup the armnn input tensors from the given vectors.</span></div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a> inputTensors;</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  FillInputTensors<armnnType1>(inputTensors, inputData, subgraphId);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="comment">// Allocate storage for the output tensors to be written to and setup the armnn output tensors.</span></div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  std::map<std::string, boost::multi_array<DataType2, NumOutputDimensions>> outputStorage;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a> outputTensors;</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : expectedOutputData)</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  {</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> outputBindingId = <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac">m_Parser</a>->GetNetworkOutputBindingInfo(subgraphId, it.first).first;</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#aefd699eb0838261fbe9770d511f63f24">m_Runtime</a>->GetOutputTensorInfo(<a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a0b81fa34e5ca505b9880755f702fafe7">m_NetworkIdentifier</a>, outputBindingId);</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> </div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="comment">// Check that output tensors have correct number of dimensions (NumOutputDimensions specified in test)</span></div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keyword">auto</span> outputNumDimensions = outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  BOOST_CHECK_MESSAGE((outputNumDimensions == NumOutputDimensions),</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  fmt::format(<span class="stringliteral">"Number of dimensions expected {}, but got {} for output layer {}"</span>,</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  NumOutputDimensions,</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  outputNumDimensions,</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  it.first));</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> </div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <a class="code" href="namespacearmnn.xhtml#a9667bea652e3a5ef81fea59b71513ced">armnn::VerifyTensorInfoDataType</a>(outputTensorInfo, armnnType2);</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  outputStorage.emplace(it.first, MakeTensor<DataType2, NumOutputDimensions>(outputTensorInfo));</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  outputTensors.push_back(</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  { outputBindingId, <a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(outputTensorInfo, outputStorage.at(it.first).data()) });</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>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#aefd699eb0838261fbe9770d511f63f24">m_Runtime</a>->EnqueueWorkload(<a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a0b81fa34e5ca505b9880755f702fafe7">m_NetworkIdentifier</a>, inputTensors, outputTensors);</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="comment">// Compare each output tensor to the expected values</span></div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : expectedOutputData)</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  {</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">armnn::BindingPointInfo</a> bindingInfo = <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac">m_Parser</a>->GetNetworkOutputBindingInfo(subgraphId, it.first);</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keyword">auto</span> outputExpected = MakeTensor<DataType2, NumOutputDimensions>(bindingInfo.second, it.second, isDynamic);</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  BOOST_TEST(<a class="code" href="_tensor_helpers_8hpp.xhtml#aa5a4b75c5fa1d312b4f3615b2315ff58">CompareTensors</a>(outputExpected, outputStorage[it.first], <span class="keyword">false</span>, isDynamic));</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  }</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> }</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> <span class="comment"></span></div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> <span class="comment">/// Multiple Inputs, Multiple Outputs w/ Variable Datatypes and different dimension sizes.</span></div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> <span class="comment">/// Executes the network with the given input tensors and checks the results against the given output tensors.</span></div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span> <span class="comment">/// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> <span class="comment">/// the input datatype to be different to the output.</span></div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> <span class="comment"></span><span class="keyword">template</span> <<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> armnnType1,</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> armnnType2></div><div class="line"><a name="l00334"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a603fc6ee4530690774de844a399dbc06"> 334</a></span> <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">ParserFlatbuffersFixture::RunTest</a>(std::size_t subgraphId,</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<armnnType1></a>>>& inputData,</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<armnnType2></a>>>& expectedOutputData)</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="keyword">using</span> DataType2 = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<armnnType2></a>;</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>  <span class="comment">// Setup the armnn input tensors from the given vectors.</span></div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a> inputTensors;</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  FillInputTensors<armnnType1>(inputTensors, inputData, subgraphId);</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>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a> outputTensors;</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  outputTensors.reserve(expectedOutputData.size());</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  std::map<std::string, std::vector<DataType2>> outputStorage;</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : expectedOutputData)</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  {</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <a class="code" href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">armnn::BindingPointInfo</a> bindingInfo = <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac">m_Parser</a>->GetNetworkOutputBindingInfo(subgraphId, it.first);</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <a class="code" href="namespacearmnn.xhtml#a9667bea652e3a5ef81fea59b71513ced">armnn::VerifyTensorInfoDataType</a>(bindingInfo.second, armnnType2);</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> </div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  std::vector<DataType2> out(it.second.size());</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  outputStorage.emplace(it.first, out);</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  outputTensors.push_back({ bindingInfo.first,</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(bindingInfo.second,</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  outputStorage.at(it.first).data()) });</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  }</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> </div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#aefd699eb0838261fbe9770d511f63f24">m_Runtime</a>->EnqueueWorkload(<a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a0b81fa34e5ca505b9880755f702fafe7">m_NetworkIdentifier</a>, inputTensors, outputTensors);</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>  <span class="comment">// Checks the results.</span></div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : expectedOutputData)</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  {</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  std::vector<armnn::ResolveType<armnnType2>> out = outputStorage.at(it.first);</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  {</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < out.size(); ++i)</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  {</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  BOOST_TEST(it.second[i] == out[i], boost::test_tools::tolerance(0.000001f));</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>  }</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  }</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> }</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> <span class="comment"></span></div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> <span class="comment">/// Multiple Inputs with different DataTypes, Multiple Outputs w/ Variable DataTypes</span></div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> <span class="comment">/// Executes the network with the given input tensors and checks the results against the given output tensors.</span></div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> <span class="comment">/// This overload supports multiple inputs and multiple outputs, identified by name along with the allowance for</span></div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> <span class="comment">/// the input datatype to be different to the output</span></div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> <span class="comment"></span><span class="keyword">template</span> <std::size_t NumOutputDimensions,</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> inputType1,</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> inputType2,</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> outputType></div><div class="line"><a name="l00382"></a><span class="lineno"><a class="line" href="struct_parser_flatbuffers_fixture.xhtml#a7c5b6cc5f5d14210b60323913d2b8841"> 382</a></span> <span class="keywordtype">void</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">ParserFlatbuffersFixture::RunTest</a>(<span class="keywordtype">size_t</span> subgraphId,</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<inputType1></a>>>& input1Data,</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<inputType2></a>>>& input2Data,</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keyword">const</span> std::map<std::string, std::vector<<a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<outputType></a>>>& expectedOutputData)</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="keyword">using</span> DataType2 = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType<outputType></a>;</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">// Setup the armnn input tensors from the given vectors.</span></div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a> inputTensors;</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  FillInputTensors<inputType1>(inputTensors, input1Data, subgraphId);</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  FillInputTensors<inputType2>(inputTensors, input2Data, subgraphId);</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> </div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="comment">// Allocate storage for the output tensors to be written to and setup the armnn output tensors.</span></div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  std::map<std::string, boost::multi_array<DataType2, NumOutputDimensions>> outputStorage;</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a> outputTensors;</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : expectedOutputData)</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  {</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> outputBindingId = <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac">m_Parser</a>->GetNetworkOutputBindingInfo(subgraphId, it.first).first;</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#aefd699eb0838261fbe9770d511f63f24">m_Runtime</a>->GetOutputTensorInfo(<a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a0b81fa34e5ca505b9880755f702fafe7">m_NetworkIdentifier</a>, outputBindingId);</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> </div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="comment">// Check that output tensors have correct number of dimensions (NumOutputDimensions specified in test)</span></div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <span class="keyword">auto</span> outputNumDimensions = outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  BOOST_CHECK_MESSAGE((outputNumDimensions == NumOutputDimensions),</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  fmt::format(<span class="stringliteral">"Number of dimensions expected {}, but got {} for output layer {}"</span>,</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  NumOutputDimensions,</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  outputNumDimensions,</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  it.first));</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> </div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <a class="code" href="namespacearmnn.xhtml#a9667bea652e3a5ef81fea59b71513ced">armnn::VerifyTensorInfoDataType</a>(outputTensorInfo, outputType);</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  outputStorage.emplace(it.first, MakeTensor<DataType2, NumOutputDimensions>(outputTensorInfo));</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  outputTensors.push_back(</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  { outputBindingId, <a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(outputTensorInfo, outputStorage.at(it.first).data()) });</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>  <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#aefd699eb0838261fbe9770d511f63f24">m_Runtime</a>->EnqueueWorkload(<a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a0b81fa34e5ca505b9880755f702fafe7">m_NetworkIdentifier</a>, inputTensors, outputTensors);</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>  <span class="comment">// Compare each output tensor to the expected values</span></div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : expectedOutputData)</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>  <a class="code" href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">armnn::BindingPointInfo</a> bindingInfo = <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac">m_Parser</a>->GetNetworkOutputBindingInfo(subgraphId, it.first);</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keyword">auto</span> outputExpected = MakeTensor<DataType2, NumOutputDimensions>(bindingInfo.second, it.second);</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  BOOST_TEST(<a class="code" href="_tensor_helpers_8hpp.xhtml#aa5a4b75c5fa1d312b4f3615b2315ff58">CompareTensors</a>(outputExpected, outputStorage[it.first], <span class="keyword">false</span>));</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  }</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span> }</div><div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a0b81fa34e5ca505b9880755f702fafe7"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a0b81fa34e5ca505b9880755f702fafe7">ParserFlatbuffersFixture::m_NetworkIdentifier</a></div><div class="ttdeci">armnn::NetworkId m_NetworkIdentifier</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00054">ParserFlatbuffersFixture.hpp:54</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a803c86dca3acef653c1cc481a27be7a9"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a803c86dca3acef653c1cc481a27be7a9">ParserFlatbuffersFixture::m_JsonString</a></div><div class="ttdeci">std::string m_JsonString</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00051">ParserFlatbuffersFixture.hpp:51</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ab509802c659de19929f18bad14a35c58"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ab509802c659de19929f18bad14a35c58">armnn::DetectionPostProcessDescriptor::m_ScaleW</a></div><div class="ttdeci">float m_ScaleW</div><div class="ttdoc">Center size encoding scale weight. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00561">Descriptors.hpp:561</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_ab77021b45ae36342092fac96ec3534b7"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#ab77021b45ae36342092fac96ec3534b7">ParserFlatbuffersFixture::GenerateDetectionPostProcessJsonString</a></div><div class="ttdeci">static std::string GenerateDetectionPostProcessJsonString(const armnn::DetectionPostProcessDescriptor &descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00178">ParserFlatbuffersFixture.hpp:178</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_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00270">Optional.hpp:270</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="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae64523937ea910030ad66fee6fddd51f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae64523937ea910030ad66fee6fddd51f">armnn::DetectionPostProcessDescriptor::m_ScaleX</a></div><div class="ttdeci">float m_ScaleX</div><div class="ttdoc">Center size encoding scale x. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00557">Descriptors.hpp:557</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_ad748cc696b0f92b478ba4f145e966754"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#ad748cc696b0f92b478ba4f145e966754">ParserFlatbuffersFixture::ParserFlatbuffersFixture</a></div><div class="ttdeci">ParserFlatbuffersFixture()</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00038">ParserFlatbuffersFixture.hpp:38</a></div></div> +<div class="ttc" id="_tensor_helpers_8hpp_xhtml_aa5a4b75c5fa1d312b4f3615b2315ff58"><div class="ttname"><a href="_tensor_helpers_8hpp.xhtml#aa5a4b75c5fa1d312b4f3615b2315ff58">CompareTensors</a></div><div class="ttdeci">boost::test_tools::predicate_result CompareTensors(const boost::multi_array< T, n > &a, const boost::multi_array< T, n > &b, bool compareBoolean=false, bool isDynamic=false)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_helpers_8hpp_source.xhtml#l00073">TensorHelpers.hpp:73</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a131f9fe1b625ce21cfe4285136ecfa20"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a131f9fe1b625ce21cfe4285136ecfa20">ParserFlatbuffersFixture::CheckTensors</a></div><div class="ttdeci">void CheckTensors(const TensorRawPtr &tensors, size_t shapeSize, const std::vector< int32_t > &shape, tflite::TensorType tensorType, uint32_t buffer, const std::string &name, const std::vector< float > &min, const std::vector< float > &max, const std::vector< float > &scale, const std::vector< int64_t > &zeroPoint)</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00205">ParserFlatbuffersFixture.hpp:205</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr< IRuntime, void(*)(IRuntime *runtime)> IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00026">IRuntime.hpp:26</a></div></div> +<div class="ttc" id="_i_runtime_8hpp_xhtml"><div class="ttname"><a href="_i_runtime_8hpp.xhtml">IRuntime.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7e2f87544b8bc7e497e1dec8d3ca4055"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7e2f87544b8bc7e497e1dec8d3ca4055">armnn::DetectionPostProcessDescriptor::m_DetectionsPerClass</a></div><div class="ttdeci">uint32_t m_DetectionsPerClass</div><div class="ttdoc">Detections per classes, used in Regular NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00547">Descriptors.hpp:547</a></div></div> +<div class="ttc" id="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser_xhtml"><div class="ttname"><a href="classarmnn_tf_lite_parser_1_1_i_tf_lite_parser.xhtml">armnnTfLiteParser::ITfLiteParser</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_tf_lite_parser_8hpp_source.xhtml#l00026">ITfLiteParser.hpp:26</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a0743ed5e860c316a20b68ca96301b411"><div class="ttname"><a href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a></div><div class="ttdeci">typename ResolveTypeImpl< DT >::Type ResolveType</div><div class="ttdef"><b>Definition:</b> <a href="_resolve_type_8hpp_source.xhtml#l00073">ResolveType.hpp:73</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a69fc8e7f42386fa67732cb8c98d8b024"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a69fc8e7f42386fa67732cb8c98d8b024">ParserFlatbuffersFixture::ReadStringToBinary</a></div><div class="ttdeci">bool ReadStringToBinary()</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00101">ParserFlatbuffersFixture.hpp:101</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00340">Tensor.hpp:340</a></div></div> +<div class="ttc" id="_resolve_type_8hpp_xhtml"><div class="ttname"><a href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00020">IRuntime.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_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="struct_parser_flatbuffers_fixture_xhtml_a769404f2985a027a0d626fedfd4de1e9"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a769404f2985a027a0d626fedfd4de1e9">ParserFlatbuffersFixture::Setup</a></div><div class="ttdeci">void Setup()</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00061">ParserFlatbuffersFixture.hpp:61</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00036">ParserFlatbuffersFixture.hpp:36</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_ad7406d5673bc2a8bc1efbdd4f4da140a"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#ad7406d5673bc2a8bc1efbdd4f4da140a">ParserFlatbuffersFixture::RunTest</a></div><div class="ttdeci">void RunTest(size_t subgraphId, const std::vector< armnn::ResolveType< ArmnnType >> &inputData, const std::vector< armnn::ResolveType< ArmnnType >> &expectedOutputData)</div><div class="ttdoc">Executes the network with the given input tensor and checks the result against the given output tenso...</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00256">ParserFlatbuffersFixture.hpp:256</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="namespacearmnn_xhtml_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a></div><div class="ttdeci">int LayerBindingId</div><div class="ttdoc">Type of identifiers for bindable layers (inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00210">Types.hpp:210</a></div></div> +<div class="ttc" id="_schema_8hpp_xhtml"><div class="ttname"><a href="_schema_8hpp.xhtml">Schema.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a9ae2c9796692ebeafe19a4d3f09c8ea8"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a9ae2c9796692ebeafe19a4d3f09c8ea8">armnn::DetectionPostProcessDescriptor::m_MaxClassesPerDetection</a></div><div class="ttdeci">uint32_t m_MaxClassesPerDetection</div><div class="ttdoc">Maximum numbers of classes per detection, used in Fast NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00545">Descriptors.hpp:545</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00306">Tensor.hpp:306</a></div></div> +<div class="ttc" id="_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="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae72089bcab60ac175557f4241b16a014"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">armnn::DetectionPostProcessDescriptor::m_MaxDetections</a></div><div class="ttdeci">uint32_t m_MaxDetections</div><div class="ttdoc">Maximum numbers of detections. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00543">Descriptors.hpp:543</a></div></div> +<div class="ttc" id="_tensor_helpers_8hpp_xhtml"><div class="ttname"><a href="_tensor_helpers_8hpp.xhtml">TensorHelpers.hpp</a></div></div> +<div class="ttc" id="_types_utils_8hpp_xhtml"><div class="ttname"><a href="_types_utils_8hpp.xhtml">TypesUtils.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">armnn::Status::Success</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#l00032">Types.hpp:32</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a53c8a7f33a40e1e240256bcfcf41b101"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a53c8a7f33a40e1e240256bcfcf41b101">armnn::DetectionPostProcessDescriptor::m_NmsIouThreshold</a></div><div class="ttdeci">float m_NmsIouThreshold</div><div class="ttdoc">Intersection over union threshold. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00551">Descriptors.hpp:551</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.xhtml#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00015">Assert.hpp:15</a></div></div> +<div class="ttc" id="_parser_flatbuffers_serialize_fixture_8hpp_xhtml_a15c20a0693cd3fc4d85565e2f920d8ef"><div class="ttname"><a href="_parser_flatbuffers_serialize_fixture_8hpp.xhtml#a15c20a0693cd3fc4d85565e2f920d8ef">TensorRawPtr</a></div><div class="ttdeci">armnnSerializer::TensorInfo * TensorRawPtr</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_serialize_fixture_8hpp_source.xhtml#l00025">ParserFlatbuffersSerializeFixture.hpp:25</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70b"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a></div><div class="ttdeci">Status</div><div class="ttdoc">enumeration </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00026">Types.hpp:26</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a3a04b0ccee4bb2f21721ee5045e83df4"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a3a04b0ccee4bb2f21721ee5045e83df4">armnn::DetectionPostProcessDescriptor::m_NumClasses</a></div><div class="ttdeci">uint32_t m_NumClasses</div><div class="ttdoc">Number of classes. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00553">Descriptors.hpp:553</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7ed9bc7c26df67d274d5dd4cd83adf0f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">armnn::DetectionPostProcessDescriptor::m_UseRegularNms</a></div><div class="ttdeci">bool m_UseRegularNms</div><div class="ttdoc">Use Regular NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00555">Descriptors.hpp:555</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_add32b4d209a5b5d6ea6db94b9894ad75"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#add32b4d209a5b5d6ea6db94b9894ad75">ParserFlatbuffersFixture::m_SingleOutputName</a></div><div class="ttdeci">std::string m_SingleOutputName</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00059">ParserFlatbuffersFixture.hpp:59</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a9fbc789fd0aca759cb40737fdeb8ed63"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a9fbc789fd0aca759cb40737fdeb8ed63">ParserFlatbuffersFixture::m_GraphBinary</a></div><div class="ttdeci">std::vector< uint8_t > m_GraphBinary</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00050">ParserFlatbuffersFixture.hpp:50</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_aefd699eb0838261fbe9770d511f63f24"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#aefd699eb0838261fbe9770d511f63f24">ParserFlatbuffersFixture::m_Runtime</a></div><div class="ttdeci">armnn::IRuntimePtr m_Runtime</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00053">ParserFlatbuffersFixture.hpp:53</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_aa61510cbd529870182e918ac6e8b9d72"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#aa61510cbd529870182e918ac6e8b9d72">armnn::DetectionPostProcessDescriptor::m_ScaleH</a></div><div class="ttdeci">float m_ScaleH</div><div class="ttdoc">Center size encoding scale height. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00563">Descriptors.hpp:563</a></div></div> +<div class="ttc" id="_assert_8hpp_xhtml"><div class="ttname"><a href="_assert_8hpp.xhtml">Assert.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a280670a263dc4fd40491f6d0a2737f44"><div class="ttname"><a href="namespacearmnn.xhtml#a280670a263dc4fd40491f6d0a2737f44">armnn::BindingPointInfo</a></div><div class="ttdeci">std::pair< armnn::LayerBindingId, armnn::TensorInfo > BindingPointInfo</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00261">Tensor.hpp:261</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a2bb4ea256fbbf6d53068ca93bb4bc95c"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a2bb4ea256fbbf6d53068ca93bb4bc95c">ParserFlatbuffersFixture::SetupSingleInputSingleOutput</a></div><div class="ttdeci">void SetupSingleInputSingleOutput(const std::string &inputName, const std::string &outputName)</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00093">ParserFlatbuffersFixture.hpp:93</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="_descriptors_8hpp_xhtml"><div class="ttname"><a href="_descriptors_8hpp.xhtml">Descriptors.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a9667bea652e3a5ef81fea59b71513ced"><div class="ttname"><a href="namespacearmnn.xhtml#a9667bea652e3a5ef81fea59b71513ced">armnn::VerifyTensorInfoDataType</a></div><div class="ttdeci">void VerifyTensorInfoDataType(const armnn::TensorInfo &info, armnn::DataType dataType)</div><div class="ttdef"><b>Definition:</b> <a href="_types_utils_8hpp_source.xhtml#l00309">TypesUtils.hpp:309</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7a2156ec7d9c012ce00bbcc6afcb9028"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7a2156ec7d9c012ce00bbcc6afcb9028">armnn::DetectionPostProcessDescriptor::m_ScaleY</a></div><div class="ttdeci">float m_ScaleY</div><div class="ttdoc">Center size encoding scale y. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00559">Descriptors.hpp:559</a></div></div> +<div class="ttc" id="_schema_8hpp_xhtml_a6747d3548926a8130c42fb3398027acf"><div class="ttname"><a href="_schema_8hpp.xhtml#a6747d3548926a8130c42fb3398027acf">g_TfLiteSchemaText</a></div><div class="ttdeci">unsigned char g_TfLiteSchemaText[]</div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a4392dd6b4862cc9cf95ae8f1001ba592"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a4392dd6b4862cc9cf95ae8f1001ba592">armnn::DetectionPostProcessDescriptor::m_NmsScoreThreshold</a></div><div class="ttdeci">float m_NmsScoreThreshold</div><div class="ttdoc">NMS score threshold. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00549">Descriptors.hpp:549</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#l00173">INetwork.hpp:173</a></div></div> +<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00511">Descriptors.hpp:511</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_a2f8365158b7c75e43897fbe804b7fc4f"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#a2f8365158b7c75e43897fbe804b7fc4f">ParserFlatbuffersFixture::m_SingleInputName</a></div><div class="ttdeci">std::string m_SingleInputName</div><div class="ttdoc">If the single-input-single-output overload of Setup() is called, these will store the input and outpu...</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00058">ParserFlatbuffersFixture.hpp:58</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00191">Tensor.hpp:191</a></div></div> +<div class="ttc" id="struct_parser_flatbuffers_fixture_xhtml_ad30eda63c4e66a0e2e3f538a2181f4ac"><div class="ttname"><a href="struct_parser_flatbuffers_fixture.xhtml#ad30eda63c4e66a0e2e3f538a2181f4ac">ParserFlatbuffersFixture::m_Parser</a></div><div class="ttdeci">ITfLiteParserPtr m_Parser</div><div class="ttdef"><b>Definition:</b> <a href="_parser_flatbuffers_fixture_8hpp_source.xhtml#l00052">ParserFlatbuffersFixture.hpp:52</a></div></div> +<div class="ttc" id="_schema_8hpp_xhtml_abe07dadc9cf942cbf847470102a8980e"><div class="ttname"><a href="_schema_8hpp.xhtml#abe07dadc9cf942cbf847470102a8980e">g_TfLiteSchemaText_len</a></div><div class="ttdeci">unsigned int g_TfLiteSchemaText_len</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_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_510324e450b9df55f9aac2d01fae83d8.xhtml">armnnTfLiteParser</a></li><li class="navelem"><a class="el" href="dir_6d8d07609c57029a35488d2120e28fbd.xhtml">test</a></li><li class="navelem"><a class="el" href="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a></li> + <li class="footer">Generated on Thu Feb 25 2021 17:27:50 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> |