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diff --git a/20.02/_get_subgraph_inputs_outputs_8cpp_source.xhtml b/20.02/_get_subgraph_inputs_outputs_8cpp_source.xhtml new file mode 100644 index 0000000000..7940ff9122 --- /dev/null +++ b/20.02/_get_subgraph_inputs_outputs_8cpp_source.xhtml @@ -0,0 +1,126 @@ +<!-- 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/GetSubgraphInputsOutputs.cpp Source File</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">20.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(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('_get_subgraph_inputs_outputs_8cpp_source.xhtml','');}); +</script> +<div id="doc-content"> +<!-- window showing the filter options --> +<div id="MSearchSelectWindow" + onmouseover="return searchBox.OnSearchSelectShow()" + onmouseout="return searchBox.OnSearchSelectHide()" + onkeydown="return searchBox.OnSearchSelectKey(event)"> +</div> + +<!-- iframe showing the search results (closed by default) --> +<div id="MSearchResultsWindow"> +<iframe src="javascript:void(0)" frameborder="0" + name="MSearchResults" id="MSearchResults"> +</iframe> +</div> + +<div class="header"> + <div class="headertitle"> +<div class="title">GetSubgraphInputsOutputs.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_get_subgraph_inputs_outputs_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. 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> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "../TfLiteParser.hpp"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="keyword">using</span> <a class="code" href="classarmnn_tf_lite_parser_1_1_tf_lite_parser.xhtml">armnnTfLiteParser::TfLiteParser</a>;</div><div class="line"><a name="l00010"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d"> 10</a></span> <span class="keyword">using</span> <a class="code" href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">ModelPtr</a> = <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d">TfLiteParser::ModelPtr</a>;</div><div class="line"><a name="l00011"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a18208ff9ca4d7b590527411427ac286c"> 11</a></span> <span class="keyword">using</span> <a class="code" href="_parser_flatbuffers_serialize_fixture_8hpp.xhtml#a15c20a0693cd3fc4d85565e2f920d8ef">TensorRawPtr</a> = <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a18208ff9ca4d7b590527411427ac286c">TfLiteParser::TensorRawPtr</a>;</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(TensorflowLiteParser)</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="keyword">struct </span>GetSubgraphInputsOutputsMainFixture : <span class="keyword">public</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> {</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <span class="keyword">explicit</span> GetSubgraphInputsOutputsMainFixture(<span class="keyword">const</span> std::string& inputs, <span class="keyword">const</span> std::string& outputs)</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  {</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  m_JsonString = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="stringliteral"> "version": 3,</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="stringliteral"> "operator_codes": [ { "builtin_code": "AVERAGE_POOL_2D" }, { "builtin_code": "CONV_2D" } ],</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="stringliteral"> "subgraphs": [</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="stringliteral"> "tensors": [</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="stringliteral"> "shape": [ 1, 1, 1, 1 ] ,</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="stringliteral"> "name": "OutputTensor",</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="stringliteral"> "zero_point": [ 0 ]</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="stringliteral"> "shape": [ 1, 2, 2, 1 ] ,</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="stringliteral"> "buffer": 1,</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="stringliteral"> "name": "InputTensor",</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="stringliteral"> "min": [ -1.2 ],</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="stringliteral"> "max": [ 25.5 ],</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="stringliteral"> "scale": [ 0.25 ],</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="stringliteral"> "zero_point": [ 10 ]</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="stringliteral"> "inputs": )"</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="stringliteral"> + inputs</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="stringliteral"> + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="stringliteral"> "outputs": )"</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="stringliteral"> + outputs</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="stringliteral"> + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="stringliteral"> "operators": [ {</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="stringliteral"> "opcode_index": 0,</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="stringliteral"> "inputs": [ 1 ],</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="stringliteral"> "outputs": [ 0 ],</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="stringliteral"> "builtin_options_type": "Pool2DOptions",</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="stringliteral"> "builtin_options":</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="stringliteral"> "padding": "VALID",</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="stringliteral"> "stride_w": 2,</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="stringliteral"> "stride_h": 2,</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="stringliteral"> "filter_width": 2,</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="stringliteral"> "filter_height": 2,</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="stringliteral"> "fused_activation_function": "NONE"</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="stringliteral"> "custom_options_format": "FLEXBUFFERS"</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="stringliteral"> } ]</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="stringliteral"> "tensors": [</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="stringliteral"> "shape": [ 1, 3, 3, 1 ],</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="stringliteral"> "name": "ConvInputTensor",</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="stringliteral"> "zero_point": [ 0 ],</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="stringliteral"> "shape": [ 1, 1, 1, 1 ],</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="stringliteral"> "buffer": 1,</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="stringliteral"> "name": "ConvOutputTensor",</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="stringliteral"> "max": [ 511.0 ],</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="stringliteral"> "scale": [ 2.0 ],</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="stringliteral"> "zero_point": [ 0 ],</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="stringliteral"> "shape": [ 1, 3, 3, 1 ],</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="stringliteral"> "type": "UINT8",</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="stringliteral"> "buffer": 2,</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="stringliteral"> "name": "filterTensor",</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="stringliteral"> "scale": [ 1.0 ],</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="stringliteral"> "zero_point": [ 0 ],</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="stringliteral"> "inputs": [ 0 ],</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="stringliteral"> "outputs": [ 1 ],</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="stringliteral"> "operators": [</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="stringliteral"> "opcode_index": 0,</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="stringliteral"> "inputs": [ 0, 2 ],</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="stringliteral"> "outputs": [ 1 ],</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="stringliteral"> "builtin_options_type": "Conv2DOptions",</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="stringliteral"> "builtin_options": {</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="stringliteral"> "padding": "VALID",</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="stringliteral"> "stride_w": 1,</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="stringliteral"> "stride_h": 1,</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="stringliteral"> "fused_activation_function": "NONE"</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> <span class="stringliteral"> },</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="stringliteral"> "custom_options_format": "FLEXBUFFERS"</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="stringliteral"> "description": "Test Subgraph Inputs Outputs",</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="stringliteral"> "buffers" : [</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="stringliteral"> { },</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="stringliteral"> { },</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="stringliteral"> { "data": [ 2,1,0, 6,2,1, 4,1,2 ], },</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="stringliteral"> { },</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="stringliteral"> ]</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="stringliteral"> })";</span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="stringliteral"></span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="stringliteral"> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml#a69fc8e7f42386fa67732cb8c98d8b024">ReadStringToBinary</a>();</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="stringliteral"></span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="stringliteral">};</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="stringliteral"></span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="stringliteral"></span><span class="keyword">struct </span>GetEmptySubgraphInputsOutputsFixture : GetSubgraphInputsOutputsMainFixture</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  GetEmptySubgraphInputsOutputsFixture() : GetSubgraphInputsOutputsMainFixture(<span class="stringliteral">"[ ]"</span>, <span class="stringliteral">"[ ]"</span>) {}</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> };</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="keyword">struct </span>GetSubgraphInputsOutputsFixture : GetSubgraphInputsOutputsMainFixture</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> {</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  GetSubgraphInputsOutputsFixture() : GetSubgraphInputsOutputsMainFixture(<span class="stringliteral">"[ 1 ]"</span>, <span class="stringliteral">"[ 0 ]"</span>) {}</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> };</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a742e7359d9eaa6561681a2c6cbc594d9"> 154</a></span> <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a742e7359d9eaa6561681a2c6cbc594d9">BOOST_FIXTURE_TEST_CASE</a>(GetEmptySubgraphInputs, GetEmptySubgraphInputsOutputsFixture)</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> {</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  TfLiteParser::TensorIdRawPtrVector subgraphTensors = TfLiteParser::GetSubgraphInputs(model, 0);</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  BOOST_CHECK_EQUAL(0, subgraphTensors.size());</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> }</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a9680b254ccdab1cce2304c7b07afee43"> 161</a></span> <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a742e7359d9eaa6561681a2c6cbc594d9">BOOST_FIXTURE_TEST_CASE</a>(GetEmptySubgraphOutputs, GetEmptySubgraphInputsOutputsFixture)</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> {</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  TfLiteParser::TensorIdRawPtrVector subgraphTensors = TfLiteParser::GetSubgraphOutputs(model, 0);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  BOOST_CHECK_EQUAL(0, subgraphTensors.size());</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> }</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div><div class="line"><a name="l00168"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a98b43cc876cba9c65264d86e76b1a87c"> 168</a></span> <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a742e7359d9eaa6561681a2c6cbc594d9">BOOST_FIXTURE_TEST_CASE</a>(GetSubgraphInputs, GetSubgraphInputsOutputsFixture)</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> {</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  TfLiteParser::TensorIdRawPtrVector subgraphTensors = TfLiteParser::GetSubgraphInputs(model, 0);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  BOOST_CHECK_EQUAL(1, subgraphTensors.size());</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  BOOST_CHECK_EQUAL(1, subgraphTensors[0].first);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  CheckTensors(subgraphTensors[0].second, 4, { 1, 2, 2, 1 }, tflite::TensorType::TensorType_UINT8, 1,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="stringliteral">"InputTensor"</span>, { -1.2f }, { 25.5f }, { 0.25f }, { 10 });</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> }</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="_get_subgraph_inputs_outputs_8cpp.xhtml#a5f0942d33c99e4d5c6f84b329be6202e"> 178</a></span> <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a742e7359d9eaa6561681a2c6cbc594d9">BOOST_FIXTURE_TEST_CASE</a>(GetSubgraphOutputsSimpleQuantized, GetSubgraphInputsOutputsFixture)</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> {</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  TfLiteParser::TensorIdRawPtrVector subgraphTensors = TfLiteParser::GetSubgraphOutputs(model, 0);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  BOOST_CHECK_EQUAL(1, subgraphTensors.size());</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  BOOST_CHECK_EQUAL(0, subgraphTensors[0].first);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  CheckTensors(subgraphTensors[0].second, 4, { 1, 1, 1, 1 }, tflite::TensorType::TensorType_UINT8, 0,</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="stringliteral">"OutputTensor"</span>, { 0.0f }, { 255.0f }, { 1.0f }, { 0 });</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> }</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#aba904879236956771f65d36ccb81bf19"> 188</a></span> <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a742e7359d9eaa6561681a2c6cbc594d9">BOOST_FIXTURE_TEST_CASE</a>(GetSubgraphInputsEmptyMinMax, GetSubgraphInputsOutputsFixture)</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> {</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  TfLiteParser::TensorIdRawPtrVector subgraphTensors = TfLiteParser::GetSubgraphInputs(model, 1);</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  BOOST_CHECK_EQUAL(1, subgraphTensors.size());</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  BOOST_CHECK_EQUAL(0, subgraphTensors[0].first);</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  CheckTensors(subgraphTensors[0].second, 4, { 1, 3, 3, 1 }, tflite::TensorType::TensorType_UINT8, 0,</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="stringliteral">"ConvInputTensor"</span>, { }, { }, { 1.0f }, { 0 });</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> </div><div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a8158f38ef701f1b632b12271a9c1b894"> 198</a></span> <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a742e7359d9eaa6561681a2c6cbc594d9">BOOST_FIXTURE_TEST_CASE</a>(GetSubgraphOutputs, GetSubgraphInputsOutputsFixture)</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> {</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  TfLiteParser::TensorIdRawPtrVector subgraphTensors = TfLiteParser::GetSubgraphOutputs(model, 1);</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  BOOST_CHECK_EQUAL(1, subgraphTensors.size());</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  BOOST_CHECK_EQUAL(1, subgraphTensors[0].first);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  CheckTensors(subgraphTensors[0].second, 4, { 1, 1, 1, 1 }, tflite::TensorType::TensorType_UINT8, 1,</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="stringliteral">"ConvOutputTensor"</span>, { 0.0f }, { 511.0f }, { 2.0f }, { 0 });</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> }</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> </div><div class="line"><a name="l00208"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#af38468442423eba2b603a187582e697f"> 208</a></span> <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#af38468442423eba2b603a187582e697f">BOOST_AUTO_TEST_CASE</a>(GetSubgraphInputsNullModel)</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_THROW(TfLiteParser::GetSubgraphInputs(<span class="keyword">nullptr</span>, 0), <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>);</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> }</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a7304f335c203cc928c03f611da283078"> 213</a></span> <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#af38468442423eba2b603a187582e697f">BOOST_AUTO_TEST_CASE</a>(GetSubgraphOutputsNullModel)</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> {</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  BOOST_CHECK_THROW(TfLiteParser::GetSubgraphOutputs(<span class="keyword">nullptr</span>, 0), <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>);</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> }</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> </div><div class="line"><a name="l00218"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a968b347d4378e434bcca58995aff34dc"> 218</a></span> <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a742e7359d9eaa6561681a2c6cbc594d9">BOOST_FIXTURE_TEST_CASE</a>(GetSubgraphInputsInvalidSubgraph, GetSubgraphInputsOutputsFixture)</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span> {</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  BOOST_CHECK_THROW(TfLiteParser::GetSubgraphInputs(model, 2), <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>);</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> }</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> </div><div class="line"><a name="l00224"></a><span class="lineno"><a class="line" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a7559b33088411e599572b68daca7a93e"> 224</a></span> <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#a742e7359d9eaa6561681a2c6cbc594d9">BOOST_FIXTURE_TEST_CASE</a>(GetSubgraphOutputsInvalidSubgraph, GetSubgraphInputsOutputsFixture)</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> {</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <a class="code" href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d">TfLiteParser::ModelPtr</a> model = TfLiteParser::LoadModelFromBinary(m_GraphBinary.data(), m_GraphBinary.size());</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  BOOST_CHECK_THROW(TfLiteParser::GetSubgraphOutputs(model, 2), <a class="code" href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a>);</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> }</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> </div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <a class="code" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="ttc" id="_output_shape_of_squeeze_8cpp_xhtml_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div> +<div class="ttc" id="_get_subgraph_inputs_outputs_8cpp_xhtml_a742e7359d9eaa6561681a2c6cbc594d9"><div class="ttname"><a href="_get_subgraph_inputs_outputs_8cpp.xhtml#a742e7359d9eaa6561681a2c6cbc594d9">BOOST_FIXTURE_TEST_CASE</a></div><div class="ttdeci">BOOST_FIXTURE_TEST_CASE(GetEmptySubgraphInputs, GetEmptySubgraphInputsOutputsFixture)</div><div class="ttdef"><b>Definition:</b> <a href="_get_subgraph_inputs_outputs_8cpp_source.xhtml#l00154">GetSubgraphInputsOutputs.cpp:154</a></div></div> +<div class="ttc" id="classarmnn_tf_lite_parser_1_1_tf_lite_parser_xhtml"><div class="ttname"><a href="classarmnn_tf_lite_parser_1_1_tf_lite_parser.xhtml">armnnTfLiteParser::TfLiteParser</a></div><div class="ttdef"><b>Definition:</b> <a href="_tf_lite_parser_8hpp_source.xhtml#l00019">TfLiteParser.hpp:19</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#l00102">ParserFlatbuffersFixture.hpp:102</a></div></div> +<div class="ttc" id="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp_xhtml_a503ae4f55dae1486e53978657083b35d"><div class="ttname"><a href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp.xhtml#a503ae4f55dae1486e53978657083b35d">ModelPtr</a></div><div class="ttdeci">std::unique_ptr< onnx::ModelProto > ModelPtr</div><div class="ttdef"><b>Definition:</b> <a href="armnn_onnx_parser_2test_2_get_inputs_outputs_8cpp_source.xhtml#l00012">GetInputsOutputs.cpp:12</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#l00037">ParserFlatbuffersFixture.hpp:37</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="_get_subgraph_inputs_outputs_8cpp_xhtml_a18208ff9ca4d7b590527411427ac286c"><div class="ttname"><a href="_get_subgraph_inputs_outputs_8cpp.xhtml#a18208ff9ca4d7b590527411427ac286c">TensorRawPtr</a></div><div class="ttdeci">TfLiteParser::TensorRawPtr TensorRawPtr</div><div class="ttdef"><b>Definition:</b> <a href="_get_subgraph_inputs_outputs_8cpp_source.xhtml#l00011">GetSubgraphInputsOutputs.cpp:11</a></div></div> +<div class="ttc" id="_parser_flatbuffers_fixture_8hpp_xhtml"><div class="ttname"><a href="_parser_flatbuffers_fixture_8hpp.xhtml">ParserFlatbuffersFixture.hpp</a></div></div> +<div class="ttc" id="_profiler_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div> +<div class="ttc" id="classarmnn_1_1_parse_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_parse_exception.xhtml">armnn::ParseException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00092">Exceptions.hpp:92</a></div></div> +<div class="ttc" id="_get_subgraph_inputs_outputs_8cpp_xhtml_ab8262a23f76732432e30196fa09a5d4d"><div class="ttname"><a href="_get_subgraph_inputs_outputs_8cpp.xhtml#ab8262a23f76732432e30196fa09a5d4d">ModelPtr</a></div><div class="ttdeci">TfLiteParser::ModelPtr ModelPtr</div><div class="ttdef"><b>Definition:</b> <a href="_get_subgraph_inputs_outputs_8cpp_source.xhtml#l00010">GetSubgraphInputsOutputs.cpp:10</a></div></div> +<div class="ttc" id="_get_subgraph_inputs_outputs_8cpp_xhtml_af38468442423eba2b603a187582e697f"><div class="ttname"><a href="_get_subgraph_inputs_outputs_8cpp.xhtml#af38468442423eba2b603a187582e697f">BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(GetSubgraphInputsNullModel)</div><div class="ttdef"><b>Definition:</b> <a href="_get_subgraph_inputs_outputs_8cpp_source.xhtml#l00208">GetSubgraphInputsOutputs.cpp:208</a></div></div> +</div><!-- fragment --></div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_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="_get_subgraph_inputs_outputs_8cpp.xhtml">GetSubgraphInputsOutputs.cpp</a></li> + <li class="footer">Generated on Fri Mar 13 2020 16:09:10 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> |