1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
|
<!-- 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/Unsupported.cpp File Reference</title>
<link href="tabs.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<link href="navtree.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="resize.js"></script>
<script type="text/javascript" src="navtreedata.js"></script>
<script type="text/javascript" src="navtree.js"></script>
<script type="text/javascript">
$(document).ready(initResizable);
</script>
<link href="search/search.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="search/searchdata.js"></script>
<script type="text/javascript" src="search/search.js"></script>
<script type="text/x-mathjax-config">
MathJax.Hub.Config({
extensions: ["tex2jax.js"],
jax: ["input/TeX","output/HTML-CSS"],
});
</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script>
<link href="doxygen.css" rel="stylesheet" type="text/css" />
<link href="stylesheet.css" rel="stylesheet" type="text/css"/>
</head>
<body>
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
<div id="titlearea">
<table cellspacing="0" cellpadding="0">
<tbody>
<tr style="height: 56px;">
<img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/>
<td style="padding-left: 0.5em;">
<div id="projectname">
 <span id="projectnumber">22.08</span>
</div>
</td>
</tr>
</tbody>
</table>
</div>
<!-- end header part -->
<!-- Generated by Doxygen 1.8.13 -->
<script type="text/javascript">
var searchBox = new SearchBox("searchBox", "search",false,'Search');
</script>
<script type="text/javascript" src="menudata.js"></script>
<script type="text/javascript" src="menu.js"></script>
<script type="text/javascript">
$(function() {
initMenu('',true,false,'search.php','Search');
$(document).ready(function() { init_search(); });
});
</script>
<div id="main-nav"></div>
</div><!-- top -->
<div id="side-nav" class="ui-resizable side-nav-resizable">
<div id="nav-tree">
<div id="nav-tree-contents">
<div id="nav-sync" class="sync"></div>
</div>
</div>
<div id="splitbar" style="-moz-user-select:none;"
class="ui-resizable-handle">
</div>
</div>
<script type="text/javascript">
$(document).ready(function(){initNavTree('_unsupported_8cpp.xhtml','');});
</script>
<div id="doc-content">
<!-- window showing the filter options -->
<div id="MSearchSelectWindow"
onmouseover="return searchBox.OnSearchSelectShow()"
onmouseout="return searchBox.OnSearchSelectHide()"
onkeydown="return searchBox.OnSearchSelectKey(event)">
</div>
<!-- iframe showing the search results (closed by default) -->
<div id="MSearchResultsWindow">
<iframe src="javascript:void(0)" frameborder="0"
name="MSearchResults" id="MSearchResults">
</iframe>
</div>
<div class="header">
<div class="summary">
<a href="#func-members">Functions</a> </div>
<div class="headertitle">
<div class="title">Unsupported.cpp File Reference</div> </div>
</div><!--header-->
<div class="contents">
<div class="textblock"><code>#include "<a class="el" href="_parser_flatbuffers_fixture_8hpp_source.xhtml">ParserFlatbuffersFixture.hpp</a>"</code><br />
<code>#include <<a class="el" href="_strategy_base_8hpp_source.xhtml">armnn/StrategyBase.hpp</a>></code><br />
<code>#include <<a class="el" href="_assert_8hpp_source.xhtml">armnn/utility/Assert.hpp</a>></code><br />
<code>#include <<a class="el" href="_numeric_cast_8hpp_source.xhtml">armnn/utility/NumericCast.hpp</a>></code><br />
<code>#include <<a class="el" href="_polymorphic_downcast_8hpp_source.xhtml">armnn/utility/PolymorphicDowncast.hpp</a>></code><br />
<code>#include <<a class="el" href="_stand_in_layer_8hpp_source.xhtml">layers/StandInLayer.hpp</a>></code><br />
<code>#include <sstream></code><br />
<code>#include <vector></code><br />
</div>
<p><a href="_unsupported_8cpp_source.xhtml">Go to the source code of this file.</a></p>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
Functions</h2></td></tr>
<tr class="memitem:a9f749799c3b53246d5434090e69898a0"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_unsupported_8cpp.xhtml#a9f749799c3b53246d5434090e69898a0">TEST_SUITE</a> ("TensorflowLiteParser_Unsupported")</td></tr>
<tr class="separator:a9f749799c3b53246d5434090e69898a0"><td class="memSeparator" colspan="2"> </td></tr>
</table>
<h2 class="groupheader">Function Documentation</h2>
<a id="a9f749799c3b53246d5434090e69898a0"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a9f749799c3b53246d5434090e69898a0">◆ </a></span>TEST_SUITE()</h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">TEST_SUITE </td>
<td>(</td>
<td class="paramtype">"TensorflowLiteParser_Unsupported" </td>
<td class="paramname"></td><td>)</td>
<td></td>
</tr>
</table>
</div><div class="memdoc">
<p class="definition">Definition at line <a class="el" href="_unsupported_8cpp_source.xhtml#l00018">18</a> of file <a class="el" href="_unsupported_8cpp_source.xhtml">Unsupported.cpp</a>.</p>
<p class="reference">References <a class="el" href="_assert_8hpp_source.xhtml#l00014">ARMNN_ASSERT</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00198">TensorInfo::GetDataType()</a>, <a class="el" href="_internal_types_8cpp_source.xhtml#l00013">armnn::GetLayerTypeAsCString()</a>, <a class="el" href="_tensor_8cpp_source.xhtml#l00174">TensorShape::GetNumDimensions()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a9c2cba04b6d7ace4fc2a2436b82a5a63">IConnectableLayer::GetNumInputSlots()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#ac2dac3b61c94de52093616be4ab17f8d">IConnectableLayer::GetNumOutputSlots()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">IConnectableLayer::GetOutputSlot()</a>, <a class="el" href="_tensor_8cpp_source.xhtml#l00478">TensorInfo::GetQuantizationOffset()</a>, <a class="el" href="_tensor_8cpp_source.xhtml#l00461">TensorInfo::GetQuantizationScale()</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00191">TensorInfo::GetShape()</a>, <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">IOutputSlot::GetTensorInfo()</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00092">OutputSlot::GetTensorInfo()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">IConnectableLayer::GetType()</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_numeric_cast_8hpp_source.xhtml#l00035">armnn::numeric_cast()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::QAsymmU8</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a93bca63ecbb003649425dd0e4ba79a99">armnn::StandIn</a>, and <a class="el" href="_mem_copy_tests_8cpp_source.xhtml#l00089">TEST_CASE_FIXTURE()</a>.</p>
<div class="fragment"><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="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</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="keyword">class </span>StandInLayerVerifier : <span class="keyword">public</span> <a class="code" href="classarmnn_1_1_strategy_base.xhtml">StrategyBase</a><NoThrowStrategy></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="keyword">public</span>:</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  StandInLayerVerifier(<span class="keyword">const</span> std::vector<TensorInfo>& inputInfos,</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keyword">const</span> std::vector<TensorInfo>& outputInfos)</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  : m_InputInfos(inputInfos)</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  , m_OutputInfos(outputInfos) {}</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="keywordtype">void</span> ExecuteStrategy(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer,</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_base_descriptor.xhtml">armnn::BaseDescriptor</a>& descriptor,</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keyword">const</span> std::vector<armnn::ConstTensor>& constants,</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name,</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> <span class="keywordtype">id</span> = 0)<span class="keyword"> override</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a>(descriptor, constants, <span class="keywordtype">id</span>);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordflow">switch</span> (layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">GetType</a>())</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  {</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a93bca63ecbb003649425dd0e4ba79a99">armnn::LayerType::StandIn</a>:</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  {</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keyword">auto</span> standInDescriptor = <span class="keyword">static_cast<</span><span class="keyword">const </span><a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml">armnn::StandInDescriptor</a>&<span class="keyword">></span>(descriptor);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(m_InputInfos.size());</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  CHECK(standInDescriptor.m_NumInputs == numInputs);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  CHECK(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a9c2cba04b6d7ace4fc2a2436b82a5a63">GetNumInputSlots</a>() == numInputs);</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputs = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(m_OutputInfos.size());</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  CHECK(standInDescriptor.m_NumOutputs == numOutputs);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  CHECK(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#ac2dac3b61c94de52093616be4ab17f8d">GetNumOutputSlots</a>() == numOutputs);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_stand_in_layer.xhtml">StandInLayer</a>* standInLayer = PolymorphicDowncast<const StandInLayer*>(layer);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < numInputs; ++i)</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_output_slot.xhtml">OutputSlot</a>* connectedSlot = standInLayer->GetInputSlot(i).GetConnectedOutputSlot();</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  CHECK(connectedSlot != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputInfo = connectedSlot-><a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  CHECK(inputInfo == m_InputInfos[i]);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  }</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < numOutputs; ++i)</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  {</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& outputInfo = layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(i).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>();</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  CHECK(outputInfo == m_OutputInfos[i]);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  }</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  }</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  m_DefaultStrategy.Apply(<a class="code" href="namespacearmnn.xhtml#addb6b14dd1b632263ffe77430259a7c4">GetLayerTypeAsCString</a>(layer-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">GetType</a>()));</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>  }</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  }</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  std::vector<TensorInfo> m_InputInfos;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  std::vector<TensorInfo> m_OutputInfos;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> };</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="keyword">class </span>DummyCustomFixture : <span class="keyword">public</span> <a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a></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="keyword">public</span>:</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keyword">explicit</span> DummyCustomFixture(<span class="keyword">const</span> std::vector<TensorInfo>& inputInfos,</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keyword">const</span> std::vector<TensorInfo>& outputInfos)</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  : <a class="code" href="struct_parser_flatbuffers_fixture.xhtml">ParserFlatbuffersFixture</a>()</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  , m_StandInLayerVerifier(inputInfos, outputInfos)</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  {</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(inputInfos.size());</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(numInputs > 0);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputs = <a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(outputInfos.size());</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(numOutputs > 0);</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  m_JsonString = R<span class="stringliteral">"(</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="stringliteral"> "version": 3,</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="stringliteral"> "operator_codes": [{</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="stringliteral"> "builtin_code": "CUSTOM",</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="stringliteral"> "custom_code": "DummyCustomOperator"</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="stringliteral"> }],</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="stringliteral"> "subgraphs": [ {</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="stringliteral"> "tensors": [)";</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="stringliteral"></span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="stringliteral"> </span><span class="comment">// Add input tensors</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < numInputs; ++i)</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  {</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputInfo = inputInfos[i];</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  m_JsonString += R<span class="stringliteral">"(</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"> "shape": )" + GetTensorShapeAsString(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()) + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="stringliteral"> "type": )" + GetDataTypeAsString(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()) + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="stringliteral"> "name": "inputTensor)" + std::to_string(i) + R</span><span class="stringliteral">"(",</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="stringliteral"> "scale": [ )" + std::to_string(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>()) + R</span><span class="stringliteral">"( ],</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="stringliteral"> "zero_point": [ )" + std::to_string(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>()) + R</span><span class="stringliteral">"( ],</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="stringliteral"> },)";</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="stringliteral"></span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="stringliteral"> </span><span class="comment">// Add output tensors</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < numOutputs; ++i)</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  {</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& outputInfo = outputInfos[i];</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  m_JsonString += R<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"> "shape": )" + GetTensorShapeAsString(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()) + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="stringliteral"> "type": )" + GetDataTypeAsString(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()) + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="stringliteral"> "buffer": 0,</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="stringliteral"> "name": "outputTensor)" + std::to_string(i) + R</span><span class="stringliteral">"(",</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="stringliteral"> "quantization": {</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="stringliteral"> "min": [ 0.0 ],</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="stringliteral"> "max": [ 255.0 ],</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="stringliteral"> "scale": [ )" + std::to_string(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">GetQuantizationScale</a>()) + R</span><span class="stringliteral">"( ],</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="stringliteral"> "zero_point": [ )" + std::to_string(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">GetQuantizationOffset</a>()) + R</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"></span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="stringliteral"> </span><span class="keywordflow">if</span> (i + 1 < numOutputs)</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  {</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  m_JsonString += <span class="stringliteral">","</span>;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  }</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  }</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>  <span class="keyword">const</span> std::string inputIndices = GetIndicesAsString(0u, numInputs - 1u);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keyword">const</span> std::string outputIndices = GetIndicesAsString(numInputs, numInputs + numOutputs - 1u);</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="comment">// Add dummy custom operator</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  m_JsonString += R<span class="stringliteral">"(],</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> <span class="stringliteral"> "inputs": )" + inputIndices + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="stringliteral"> "outputs": )" + outputIndices + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> <span class="stringliteral"> "operators": [</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="stringliteral"> {</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> <span class="stringliteral"> "opcode_index": 0,</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="stringliteral"> "inputs": )" + inputIndices + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="stringliteral"> "outputs": )" + outputIndices + R</span><span class="stringliteral">"(,</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="stringliteral"> "builtin_options_type": 0,</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="stringliteral"> "custom_options": [ ],</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> <span class="stringliteral"> "custom_options_format": "FLEXBUFFERS"</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="stringliteral"> ],</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> <span class="stringliteral"> } ],</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> <span class="stringliteral"> "buffers" : [</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> <span class="stringliteral"> { },</span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> <span class="stringliteral"> { }</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> <span class="stringliteral"> ]</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> <span class="stringliteral"> )";</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> <span class="stringliteral"></span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> <span class="stringliteral"> ReadStringToBinary();</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> <span class="stringliteral"> }</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> <span class="stringliteral"></span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> <span class="stringliteral"> </span><span class="keywordtype">void</span> RunTest()</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  {</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = m_Parser->CreateNetworkFromBinary(m_GraphBinary);</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  network->ExecuteStrategy(m_StandInLayerVerifier);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  }</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keyword">static</span> std::string GetTensorShapeAsString(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& tensorShape)</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  {</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  std::stringstream stream;</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  stream << <span class="stringliteral">"[ "</span>;</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < tensorShape.<a class="code" href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</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>  stream << tensorShape[i];</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordflow">if</span> (i + 1 < tensorShape.GetNumDimensions())</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>  stream << <span class="stringliteral">","</span>;</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  }</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  stream << <span class="stringliteral">" "</span>;</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  }</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  stream << <span class="stringliteral">"]"</span>;</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keywordflow">return</span> stream.str();</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  }</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> </div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keyword">static</span> std::string GetDataTypeAsString(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dataType)</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  {</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keywordflow">switch</span> (dataType)</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  {</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>: <span class="keywordflow">return</span> <span class="stringliteral">"FLOAT32"</span>;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>: <span class="keywordflow">return</span> <span class="stringliteral">"UINT8"</span>;</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordflow">default</span>: <span class="keywordflow">return</span> <span class="stringliteral">"UNKNOWN"</span>;</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"> 208</span> </div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keyword">static</span> std::string GetIndicesAsString(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> first, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> last)</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  {</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  std::stringstream stream;</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  stream << <span class="stringliteral">"[ "</span>;</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = first; i <= last ; ++i)</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>  stream << i;</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordflow">if</span> (i + 1 <= last)</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  {</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  stream << <span class="stringliteral">","</span>;</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>  stream << <span class="stringliteral">" "</span>;</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  }</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  stream << <span class="stringliteral">"]"</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"> 224</span>  <span class="keywordflow">return</span> stream.str();</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  }</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  StandInLayerVerifier m_StandInLayerVerifier;</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> <span class="keyword">class </span>DummyCustom1Input1OutputFixture : <span class="keyword">public</span> DummyCustomFixture</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> {</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  DummyCustom1Input1OutputFixture()</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  : DummyCustomFixture({ <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>) },</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  { <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 2, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>) }) {}</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> };</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> </div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="keyword">class </span>DummyCustom2Inputs1OutputFixture : <span class="keyword">public</span> DummyCustomFixture</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> {</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  DummyCustom2Inputs1OutputFixture()</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  : DummyCustomFixture({ <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 2, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>) },</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  { <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 3, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>) }) {}</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> </div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> <a class="code" href="_mem_copy_tests_8cpp.xhtml#a3df1acc0ccc35bce0bd6c027e23e2c45">TEST_CASE_FIXTURE</a>(DummyCustom1Input1OutputFixture, <span class="stringliteral">"UnsupportedCustomOperator1Input1Output"</span>)</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> {</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  RunTest();</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> }</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> </div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <a class="code" href="_mem_copy_tests_8cpp.xhtml#a3df1acc0ccc35bce0bd6c027e23e2c45">TEST_CASE_FIXTURE</a>(DummyCustom2Inputs1OutputFixture, <span class="stringliteral">"UnsupportedCustomOperator2Inputs1Output"</span>)</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> {</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  RunTest();</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> }</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> </div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> }</div><div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_ac2dac3b61c94de52093616be4ab17f8d"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#ac2dac3b61c94de52093616be4ab17f8d">armnn::IConnectableLayer::GetNumOutputSlots</a></div><div class="ttdeci">virtual unsigned int GetNumOutputSlots() const =0</div><div class="ttdoc">Returns the number of connectable output slots. </div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00068">INetwork.hpp:68</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a9c2cba04b6d7ace4fc2a2436b82a5a63"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a9c2cba04b6d7ace4fc2a2436b82a5a63">armnn::IConnectableLayer::GetNumInputSlots</a></div><div class="ttdeci">virtual unsigned int GetNumInputSlots() const =0</div><div class="ttdoc">Returns the number of connectable input slots. </div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() 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="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="classarmnn_1_1_stand_in_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_stand_in_layer.xhtml">armnn::StandInLayer</a></div><div class="ttdoc">This layer represents an unknown operation in the input graph. </div><div class="ttdef"><b>Definition:</b> <a href="_stand_in_layer_8hpp_source.xhtml#l00014">StandInLayer.hpp:14</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__quick__start_8dox_source.xhtml#l00006">01_00_quick_start.dox:6</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</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#l00035">ParserFlatbuffersFixture.hpp:35</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</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#l00290">Types.hpp:290</a></div></div>
<div class="ttc" id="structarmnn_1_1_base_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_base_descriptor.xhtml">armnn::BaseDescriptor</a></div><div class="ttdoc">Base class for all descriptors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00022">Descriptors.hpp:22</a></div></div>
<div class="ttc" id="classarmnn_1_1_strategy_base_xhtml"><div class="ttname"><a href="classarmnn_1_1_strategy_base.xhtml">armnn::StrategyBase</a></div><div class="ttdoc">Strategy base class with empty implementations. </div><div class="ttdef"><b>Definition:</b> <a href="_strategy_base_8hpp_source.xhtml#l00027">StrategyBase.hpp:27</a></div></div>
<div class="ttc" id="_mem_copy_tests_8cpp_xhtml_a3df1acc0ccc35bce0bd6c027e23e2c45"><div class="ttname"><a href="_mem_copy_tests_8cpp.xhtml#a3df1acc0ccc35bce0bd6c027e23e2c45">TEST_CASE_FIXTURE</a></div><div class="ttdeci">TEST_CASE_FIXTURE(ClContextControlFixture, "CopyBetweenNeonAndGpu")</div><div class="ttdef"><b>Definition:</b> <a href="_mem_copy_tests_8cpp_source.xhtml#l00089">MemCopyTests.cpp:89</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00048">Types.hpp:48</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a770b51078da02f44a819e9f95d8058b5"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a770b51078da02f44a819e9f95d8058b5">armnn::TensorInfo::GetQuantizationOffset</a></div><div class="ttdeci">int32_t GetQuantizationOffset() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00478">Tensor.cpp:478</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a047ca888c43bd7fb5702853bf72410d0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a047ca888c43bd7fb5702853bf72410d0">armnn::TensorInfo::GetQuantizationScale</a></div><div class="ttdeci">float GetQuantizationScale() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00461">Tensor.cpp:461</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00198">Tensor.hpp:198</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml">armnn::OutputSlot</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00087">Layer.hpp:87</a></div></div>
<div class="ttc" id="_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div>
<div class="ttc" id="structarmnn_1_1_stand_in_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stand_in_descriptor.xhtml">armnn::StandInDescriptor</a></div><div class="ttdoc">A StandInDescriptor for the StandIn layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01258">Descriptors.hpp:1258</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_adceb04ae84c524e4d01881e3754a4d59"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">armnn::IConnectableLayer::GetType</a></div><div class="ttdeci">virtual LayerType GetType() const =0</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a93bca63ecbb003649425dd0e4ba79a99"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a93bca63ecbb003649425dd0e4ba79a99">armnn::LayerType::StandIn</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdoc">Function that returns the tensor rank. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00174">Tensor.cpp:174</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a375ca3cff9f1b005d1412dc5f3cf5b6e"><div class="ttname"><a href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00035">NumericCast.hpp:35</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a9943775a364fc4ab53b85ac88f311886"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">armnn::IOutputSlot::GetTensorInfo</a></div><div class="ttdeci">virtual const TensorInfo & GetTensorInfo() const =0</div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0</div><div class="ttdoc">Get the const output slot handle by slot index. </div></div>
<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00238">INetwork.hpp:238</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00092">Layer.cpp:92</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_addb6b14dd1b632263ffe77430259a7c4"><div class="ttname"><a href="namespacearmnn.xhtml#addb6b14dd1b632263ffe77430259a7c4">armnn::GetLayerTypeAsCString</a></div><div class="ttdeci">const char * GetLayerTypeAsCString(LayerType type)</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8cpp_source.xhtml#l00013">InternalTypes.cpp:13</a></div></div>
</div><!-- fragment -->
</div>
</div>
</div><!-- contents -->
</div><!-- doc-content -->
<!-- start footer part -->
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_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="_unsupported_8cpp.xhtml">Unsupported.cpp</a></li>
<li class="footer">Generated on Fri Aug 19 2022 14:38:32 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>
|
