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
|
<!-- 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/backends/backendsCommon/test/StridedSliceAsyncEndToEndTest.hpp Source File</title>
<link href="tabs.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<link href="navtree.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="resize.js"></script>
<script type="text/javascript" src="navtreedata.js"></script>
<script type="text/javascript" src="navtree.js"></script>
<script type="text/javascript">
$(document).ready(initResizable);
</script>
<link href="search/search.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="search/searchdata.js"></script>
<script type="text/javascript" src="search/search.js"></script>
<script type="text/x-mathjax-config">
MathJax.Hub.Config({
extensions: ["tex2jax.js"],
jax: ["input/TeX","output/HTML-CSS"],
});
</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script>
<link href="doxygen.css" rel="stylesheet" type="text/css" />
<link href="stylesheet.css" rel="stylesheet" type="text/css"/>
</head>
<body>
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
<div id="titlearea">
<table cellspacing="0" cellpadding="0">
<tbody>
<tr style="height: 56px;">
<img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/>
<td style="padding-left: 0.5em;">
<div id="projectname">
 <span id="projectnumber">21.08</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('_strided_slice_async_end_to_end_test_8hpp_source.xhtml','');});
</script>
<div id="doc-content">
<!-- window showing the filter options -->
<div id="MSearchSelectWindow"
onmouseover="return searchBox.OnSearchSelectShow()"
onmouseout="return searchBox.OnSearchSelectHide()"
onkeydown="return searchBox.OnSearchSelectKey(event)">
</div>
<!-- iframe showing the search results (closed by default) -->
<div id="MSearchResultsWindow">
<iframe src="javascript:void(0)" frameborder="0"
name="MSearchResults" id="MSearchResults">
</iframe>
</div>
<div class="header">
<div class="headertitle">
<div class="title">StridedSliceAsyncEndToEndTest.hpp</div> </div>
</div><!--header-->
<div class="contents">
<a href="_strided_slice_async_end_to_end_test_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_i_working_mem_handle_8hpp.xhtml">armnn/IWorkingMemHandle.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_i_network_8hpp.xhtml">armnn/INetwork.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_threadpool_8hpp.xhtml">armnn/Threadpool.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_i_async_execution_callback_8hpp.xhtml">armnn/IAsyncExecutionCallback.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_async_execution_callback_8hpp.xhtml">AsyncExecutionCallback.hpp</a>></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_common_test_utils_8hpp.xhtml">backendsCommon/test/CommonTestUtils.hpp</a>></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <doctest/doctest.h></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> </div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></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> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="keyword">namespace </span>experimental</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> {</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="keyword">template</span><<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> ArmnnIType, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> ArmnnOType,</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keyword">typename</span> TInput = ResolveType <ArmnnIType>, <span class="keyword">typename</span> TOutput = ResolveType <ArmnnOType>></div><div class="line"><a name="l00030"></a><span class="lineno"><a class="line" href="namespacearmnn_1_1experimental.xhtml#ae9bd946ed0ec9f8a41197b83037a401f"> 30</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn_1_1experimental.xhtml#ae9bd946ed0ec9f8a41197b83037a401f">AsyncThreadedEndToEndTestImpl</a>(<a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network,</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keyword">const</span> std::vector<std::map<<span class="keywordtype">int</span>, std::vector<TInput>>>& inputTensorData,</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keyword">const</span> std::vector<std::map<<span class="keywordtype">int</span>, std::vector<TOutput>>>& expectedOutputData,</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  std::vector<BackendId> backends,</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> numberOfInferences,</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keywordtype">float</span> tolerance = 0.000001f)</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="comment">// Create Runtime in which test will run</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(options));</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="comment">// Optimize the Network</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*network, backends, runtime->GetDeviceSpec());</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="comment">// Creates AsyncNetwork</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <a class="code" href="namespacearmnn.xhtml#a0d8160388a127c1a23b37bc88dc6e2ec">NetworkId</a> networkId = 0;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  std::string errorMessage;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_i_network_properties.xhtml">INetworkProperties</a> networkProperties(<span class="keyword">true</span>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  runtime->LoadNetwork(networkId, std::move(optNet), errorMessage, networkProperties);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  std::vector<InputTensors> inputTensorsVec;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  std::vector<OutputTensors> outputTensorsVec;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  std::vector<std::map<int, std::vector<TOutput>>> outputStorageVec;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  std::vector<std::unique_ptr<IWorkingMemHandle>> workingMemHandles;</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numberOfInferences; ++i)</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  {</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors;</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  outputStorageVec.emplace_back(std::map<<span class="keywordtype">int</span>, std::vector<TOutput>>());</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>  inputTensors.reserve(inputTensorData.size());</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : inputTensorData[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>  inputTensors.push_back({it.first,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>(runtime->GetInputTensorInfo(networkId, it.first), it.second.data())});</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  }</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> </div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  outputTensors.reserve(expectedOutputData.size());</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : expectedOutputData[i])</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>  std::vector<TOutput> out(it.second.size());</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  outputStorageVec[i].emplace(it.first, out);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  outputTensors.push_back({it.first,</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="classarmnn_1_1_tensor.xhtml">Tensor</a>(runtime->GetOutputTensorInfo(networkId, it.first),</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  outputStorageVec[i].at(it.first).data())});</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>  inputTensorsVec.push_back(inputTensors);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  outputTensorsVec.push_back(outputTensors);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  workingMemHandles.push_back(runtime->CreateWorkingMemHandle(networkId));</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  }</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  std::vector<std::thread> threads;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numberOfInferences; ++i)</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  {</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="comment">// Access the vectors before we do anything multi-threaded</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a>& inputTensors = inputTensorsVec[i];</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a>& outputTensors = outputTensorsVec[i];</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="classarmnn_1_1experimental_1_1_i_working_mem_handle.xhtml">IWorkingMemHandle</a>& workingMemHandle = *workingMemHandles[i].get();</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>  threads.emplace_back([&]()</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  {</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="comment">// Run the async network</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  runtime->Execute(workingMemHandle, inputTensors, outputTensors);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  });</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  }</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numberOfInferences; ++i)</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  {</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  threads[i].join();</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  }</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="comment">// Checks the results.</span></div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numberOfInferences; ++i)</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  {</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> &&it : expectedOutputData[i])</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  {</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  std::vector<TOutput> out = outputStorageVec[i].at(it.first);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = 0; j < out.size(); ++j)</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  CHECK(Compare<ArmnnOType>(it.second[j], out[j], tolerance) == <span class="keyword">true</span>);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  }</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  }</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  }</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> }</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="keyword">template</span><<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> ArmnnIType, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> ArmnnOType,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keyword">typename</span> TInput = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">ResolveType<ArmnnIType></a>, <span class="keyword">typename</span> TOutput = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">ResolveType<ArmnnOType></a>></div><div class="line"><a name="l00122"></a><span class="lineno"><a class="line" href="namespacearmnn_1_1experimental.xhtml#a6c8cd7552424617a2e4361c1d966f734"> 122</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn_1_1experimental.xhtml#a6c8cd7552424617a2e4361c1d966f734">AsyncEndToEndTestImpl</a>(<a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keyword">const</span> std::map<<span class="keywordtype">int</span>, std::vector<TInput>>& inputTensorData,</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">const</span> std::map<<span class="keywordtype">int</span>, std::vector<TOutput>>& expectedOutputData,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  std::vector<BackendId> backends,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keywordtype">float</span> tolerance = 0.000001f,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordtype">size_t</span> numThreads = 1)</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> {</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="comment">// Create Runtime in which test will run</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(options));</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> </div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="comment">// Optimize the Network</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*network, backends, runtime->GetDeviceSpec());</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="comment">// Creates AsyncNetwork</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <a class="code" href="namespacearmnn.xhtml#a0d8160388a127c1a23b37bc88dc6e2ec">NetworkId</a> networkId = 0;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  std::string errorMessage;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_i_network_properties.xhtml">INetworkProperties</a> networkProperties(<span class="keyword">true</span>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">MemorySource::Undefined</a>);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  runtime->LoadNetwork(networkId, std::move(optNet), errorMessage, networkProperties);</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors;</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  inputTensors.reserve(inputTensorData.size());</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : inputTensorData)</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>  inputTensors.push_back({it.first,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>(runtime->GetInputTensorInfo(networkId, it.first), it.second.data())});</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</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>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors;</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  outputTensors.reserve(expectedOutputData.size());</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  std::map<int, std::vector<TOutput>> outputStorage;</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : expectedOutputData)</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  {</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  std::vector<TOutput> out(it.second.size());</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  outputStorage.emplace(it.first, out);</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  outputTensors.push_back({it.first,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <a class="code" href="classarmnn_1_1_tensor.xhtml">Tensor</a>(runtime->GetOutputTensorInfo(networkId, it.first),</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  outputStorage.at(it.first).data())});</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  }</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keywordflow">if</span> (numThreads <= 1)</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>  <span class="comment">// Create WorkingMemHandle for this async network</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  std::unique_ptr<IWorkingMemHandle> workingMemHandle = runtime->CreateWorkingMemHandle(networkId);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="classarmnn_1_1experimental_1_1_i_working_mem_handle.xhtml">IWorkingMemHandle</a>& workingMemHandleRef = *workingMemHandle.get();</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="comment">// Run the async network</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  runtime->Execute(workingMemHandleRef, inputTensors, outputTensors);</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  }</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordflow">else</span></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>  std::vector<std::shared_ptr<IWorkingMemHandle>> memHandles;</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> </div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < numThreads; ++i)</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>  memHandles.emplace_back(runtime->CreateWorkingMemHandle(networkId));</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  }</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="classarmnn_1_1experimental_1_1_threadpool.xhtml">Threadpool</a> threadpool(numThreads, runtime.get(), memHandles);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <a class="code" href="classarmnn_1_1experimental_1_1_async_callback_manager.xhtml">AsyncCallbackManager</a> callbackManager;</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> </div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="comment">// For the asyncronous execution, we are adding a pool of working memory handles (1 per thread) in the</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="comment">// LoadedNetwork with a each scheduled inference having a spefic priority</span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < 1000; ++i)</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>  threadpool.Schedule(networkId,</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  inputTensors,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  outputTensors,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  static_cast<QosExecPriority>(rand()%3),</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  callbackManager.GetNewCallback());</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> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// Wait until the execution signals a notify</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < 1000; ++i)</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  {</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keyword">auto</span> cb = callbackManager.<a class="code" href="classarmnn_1_1experimental_1_1_async_callback_manager.xhtml#a9ee5b1dd7d3a6f619d2ed3d97d75d9b1">GetNotifiedCallback</a>();</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="comment">// Checks the results.</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  CHECK(cb->GetStatus() == <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">Status::Success</a>);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  }</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  }</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>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& it : expectedOutputData)</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>  std::vector<TOutput> out = outputStorage.at(it.first);</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>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < out.size(); ++i)</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  {</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  CHECK(Compare<ArmnnOType>(it.second[i], out[i], tolerance) == <span class="keyword">true</span>);</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  }</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  }</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> }</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> <span class="keyword">template</span><<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00219"></a><span class="lineno"><a class="line" href="namespacearmnn_1_1experimental.xhtml#adef78ee82cfcce4c9061f266ccf0a29d"> 219</a></span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> <a class="code" href="namespacearmnn_1_1experimental.xhtml#adef78ee82cfcce4c9061f266ccf0a29d">CreateStridedSliceNetwork</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& inputShape,</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& outputShape,</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keyword">const</span> std::vector<int>& beginData,</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <span class="keyword">const</span> std::vector<int>& endData,</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <span class="keyword">const</span> std::vector<int>& stridesData,</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordtype">int</span> beginMask = 0,</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordtype">int</span> endMask = 0,</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="keywordtype">int</span> shrinkAxisMask = 0,</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordtype">int</span> ellipsisMask = 0,</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="keywordtype">int</span> newAxisMask = 0,</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keyword">const</span> int32_t qOffset = 0)</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">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>());</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> </div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputTensorInfo(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>, qScale, qOffset);</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputTensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>, qScale, qOffset);</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml">armnn::StridedSliceDescriptor</a> stridedSliceDescriptor;</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  stridedSliceDescriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#a118fe06b7c2599da60398ee311ede923">m_Begin</a> = beginData;</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  stridedSliceDescriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#aa68194dd6258ab5b04123005a066ea25">m_End</a> = endData;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  stridedSliceDescriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#a0d53caff836b84204adbd1c28752a201">m_Stride</a> = stridesData;</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  stridedSliceDescriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#a61081be1483984e33db452c75d569f51">m_BeginMask</a> = beginMask;</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  stridedSliceDescriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#ac37e49c0d6e6e54f9d2015d0f11f8ee7">m_EndMask</a> = endMask;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  stridedSliceDescriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#a6d0384878432cfc9652b7ae8bc59506f">m_ShrinkAxisMask</a> = shrinkAxisMask;</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  stridedSliceDescriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#af996d82c47e43a16f4c8faa6c6b3e030">m_EllipsisMask</a> = ellipsisMask;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  stridedSliceDescriptor.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#a7c91eda2b331d607bae92cd8ebf50bb9">m_NewAxisMask</a> = newAxisMask;</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> </div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input = net->AddInputLayer(0, <span class="stringliteral">"Input_Layer"</span>);</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* stridedSlice = net->AddStridedSliceLayer(stridedSliceDescriptor, <span class="stringliteral">"splitter"</span>);</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = net->AddOutputLayer(0);</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>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, stridedSlice, inputTensorInfo, 0, 0);</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(stridedSlice, output, outputTensorInfo, 0, 0);</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>  <span class="keywordflow">return</span> net;</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> }</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> </div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> <span class="keyword">template</span><armnn::DataType ArmnnType></div><div class="line"><a name="l00260"></a><span class="lineno"><a class="line" href="namespacearmnn_1_1experimental.xhtml#a88ec5950dc1ba35b8932373b5eda2729"> 260</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn_1_1experimental.xhtml#a88ec5950dc1ba35b8932373b5eda2729">StridedSlicedEndToEndTest</a>(<span class="keyword">const</span> std::vector<BackendId>& backends, <span class="keywordtype">size_t</span> numThreads)</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> {</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="keyword">using</span> T = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">ResolveType<ArmnnType></a>;</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> </div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& inputShape = {3, 2, 3, 1};</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& outputShape = {1, 2, 3, 1};</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="keyword">const</span> std::vector<int>& beginData = {1, 0, 0, 0};</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <span class="keyword">const</span> std::vector<int>& endData = {2, 2, 3, 1};</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keyword">const</span> std::vector<int>& stridesData = {1, 1, 1, 1};</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="keywordtype">int</span> beginMask = 0;</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <span class="keywordtype">int</span> endMask = 0;</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keywordtype">int</span> shrinkAxisMask = 0;</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="keywordtype">int</span> ellipsisMask = 0;</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keywordtype">int</span> newAxisMask = 0;</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> </div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <span class="comment">// Builds up the structure of the network</span></div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net = CreateStridedSliceNetwork<ArmnnType>(inputShape,</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  outputShape,</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  beginData,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  endData,</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  stridesData,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  beginMask,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  endMask,</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  shrinkAxisMask,</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  ellipsisMask,</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  newAxisMask);</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> </div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  CHECK(net);</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="comment">// Creates structures for input & output.</span></div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  std::vector<T> inputData{</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> </div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  };</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> </div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  std::vector<T> outputExpected{</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  };</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> </div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  std::map<int, std::vector<T>> inputTensorData = {{0, inputData}};</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  std::map<int, std::vector<T>> expectedOutputData = {{0, outputExpected}};</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  AsyncEndToEndTestImpl<ArmnnType, ArmnnType>(move(net),</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  inputTensorData,</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  expectedOutputData,</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  backends,</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  0.000001f,</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  numThreads);</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> }</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> <span class="keyword">template</span><armnn::DataType ArmnnType></div><div class="line"><a name="l00314"></a><span class="lineno"><a class="line" href="namespacearmnn_1_1experimental.xhtml#abc5302ddb43cf5de9a847fce043bae9b"> 314</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn_1_1experimental.xhtml#abc5302ddb43cf5de9a847fce043bae9b">StridedSlicedMultiThreadedEndToEndTest</a>(<span class="keyword">const</span> std::vector<BackendId>& backends)</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> {</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="keyword">using</span> T = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">ResolveType<ArmnnType></a>;</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> </div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& inputShape = {3, 2, 3, 1};</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& outputShape = {1, 2, 3, 1};</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keyword">const</span> std::vector<int>& beginData = {1, 0, 0, 0};</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keyword">const</span> std::vector<int>& endData = {2, 2, 3, 1};</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keyword">const</span> std::vector<int>& stridesData = {1, 1, 1, 1};</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordtype">int</span> beginMask = 0;</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="keywordtype">int</span> endMask = 0;</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keywordtype">int</span> shrinkAxisMask = 0;</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keywordtype">int</span> ellipsisMask = 0;</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keywordtype">int</span> newAxisMask = 0;</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="comment">// Builds up the structure of the network</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net = CreateStridedSliceNetwork<ArmnnType>(inputShape,</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  outputShape,</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  beginData,</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  endData,</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  stridesData,</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  beginMask,</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  endMask,</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  shrinkAxisMask,</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  ellipsisMask,</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  newAxisMask);</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span> </div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  CHECK(net);</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span> </div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="comment">// Creates structures for input & output.</span></div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  std::vector<T> inputData1{</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> </div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> </div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  };</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> </div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  std::vector<T> outputExpected1{ 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f };</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> </div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="comment">// Creates structures for input & output.</span></div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  std::vector<T> inputData2{</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> </div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  8.0f, 8.0f, 8.0f, 7.0f, 7.0f, 7.0f,</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span> </div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  };</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> </div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  std::vector<T> outputExpected2{ 8.0f, 8.0f, 8.0f, 7.0f, 7.0f, 7.0f };</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span> </div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  std::vector<std::map<int, std::vector<T>>> inputTensors;</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  std::vector<std::map<int, std::vector<T>>> outputTensors;</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> </div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  inputTensors.push_back(std::map<<span class="keywordtype">int</span>, std::vector<T>> {{0, inputData1}});</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  inputTensors.push_back(std::map<<span class="keywordtype">int</span>, std::vector<T>> {{0, inputData2}});</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  outputTensors.push_back(std::map<<span class="keywordtype">int</span>, std::vector<T>> {{0, outputExpected1}});</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  outputTensors.push_back(std::map<<span class="keywordtype">int</span>, std::vector<T>> {{0, outputExpected2}});</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> </div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  AsyncThreadedEndToEndTestImpl<ArmnnType, ArmnnType>(move(net), inputTensors, outputTensors, backends, 2);</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> }</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> </div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> } <span class="comment">// experimental namespace</span></div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> </div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> } <span class="comment">// armnn namespace</span></div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div><div class="ttc" id="classarmnn_1_1_i_runtime_xhtml_ad44ecd3700748dc30dc4bbe34ba5bde7"><div class="ttname"><a href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a></div><div class="ttdeci">static IRuntimePtr Create(const CreationOptions &options)</div><div class="ttdef"><b>Definition:</b> <a href="_runtime_8cpp_source.xhtml#l00039">Runtime.cpp:39</a></div></div>
<div class="ttc" id="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#l00061">INetwork.hpp:61</a></div></div>
<div class="ttc" id="_i_async_execution_callback_8hpp_xhtml"><div class="ttname"><a href="_i_async_execution_callback_8hpp.xhtml">IAsyncExecutionCallback.hpp</a></div></div>
<div class="ttc" id="_threadpool_8hpp_xhtml"><div class="ttname"><a href="_threadpool_8hpp.xhtml">Threadpool.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_a6d0384878432cfc9652b7ae8bc59506f"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#a6d0384878432cfc9652b7ae8bc59506f">armnn::StridedSliceDescriptor::m_ShrinkAxisMask</a></div><div class="ttdeci">int32_t m_ShrinkAxisMask</div><div class="ttdoc">Shrink axis mask value. If set, the nth specification shrinks the dimensionality by 1...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01146">Descriptors.hpp:1146</a></div></div>
<div class="ttc" id="namespacearmnn_1_1experimental_xhtml_ae9bd946ed0ec9f8a41197b83037a401f"><div class="ttname"><a href="namespacearmnn_1_1experimental.xhtml#ae9bd946ed0ec9f8a41197b83037a401f">armnn::experimental::AsyncThreadedEndToEndTestImpl</a></div><div class="ttdeci">void AsyncThreadedEndToEndTestImpl(INetworkPtr network, const std::vector< std::map< int, std::vector< TInput >>> &inputTensorData, const std::vector< std::map< int, std::vector< TOutput >>> &expectedOutputData, std::vector< BackendId > backends, const size_t numberOfInferences, float tolerance=0.000001f)</div><div class="ttdef"><b>Definition:</b> <a href="_strided_slice_async_end_to_end_test_8hpp_source.xhtml#l00030">StridedSliceAsyncEndToEndTest.hpp:30</a></div></div>
<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_a118fe06b7c2599da60398ee311ede923"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#a118fe06b7c2599da60398ee311ede923">armnn::StridedSliceDescriptor::m_Begin</a></div><div class="ttdeci">std::vector< int > m_Begin</div><div class="ttdoc">Begin values for the input that will be sliced. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01133">Descriptors.hpp:1133</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="namespacearmnn_xhtml_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr< IRuntime, void(*)(IRuntime *runtime)> IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00030">IRuntime.hpp:30</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a0743ed5e860c316a20b68ca96301b411"><div class="ttname"><a href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a></div><div class="ttdeci">typename ResolveTypeImpl< DT >::Type ResolveType</div><div class="ttdef"><b>Definition:</b> <a href="_resolve_type_8hpp_source.xhtml#l00079">ResolveType.hpp:79</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00360">Tensor.hpp:360</a></div></div>
<div class="ttc" id="_resolve_type_8hpp_xhtml"><div class="ttname"><a href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div>
<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_a61081be1483984e33db452c75d569f51"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#a61081be1483984e33db452c75d569f51">armnn::StridedSliceDescriptor::m_BeginMask</a></div><div class="ttdeci">int32_t m_BeginMask</div><div class="ttdoc">Begin mask value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01141">Descriptors.hpp:1141</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="structarmnn_1_1_strided_slice_descriptor_xhtml_ac37e49c0d6e6e54f9d2015d0f11f8ee7"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#ac37e49c0d6e6e54f9d2015d0f11f8ee7">armnn::StridedSliceDescriptor::m_EndMask</a></div><div class="ttdeci">int32_t m_EndMask</div><div class="ttdoc">End mask value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01144">Descriptors.hpp:1144</a></div></div>
<div class="ttc" id="namespacearmnn_1_1experimental_xhtml_a88ec5950dc1ba35b8932373b5eda2729"><div class="ttname"><a href="namespacearmnn_1_1experimental.xhtml#a88ec5950dc1ba35b8932373b5eda2729">armnn::experimental::StridedSlicedEndToEndTest</a></div><div class="ttdeci">void StridedSlicedEndToEndTest(const std::vector< BackendId > &backends, size_t numThreads)</div><div class="ttdef"><b>Definition:</b> <a href="_strided_slice_async_end_to_end_test_8hpp_source.xhtml#l00260">StridedSliceAsyncEndToEndTest.hpp:260</a></div></div>
<div class="ttc" id="structarmnn_1_1_i_network_properties_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_network_properties.xhtml">armnn::INetworkProperties</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00032">IRuntime.hpp:32</a></div></div>
<div class="ttc" id="_common_test_utils_8hpp_xhtml"><div class="ttname"><a href="_common_test_utils_8hpp.xhtml">CommonTestUtils.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00319">Tensor.hpp:319</a></div></div>
<div class="ttc" id="_i_working_mem_handle_8hpp_xhtml"><div class="ttname"><a href="_i_working_mem_handle_8hpp.xhtml">IWorkingMemHandle.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_1_1experimental_xhtml_abc5302ddb43cf5de9a847fce043bae9b"><div class="ttname"><a href="namespacearmnn_1_1experimental.xhtml#abc5302ddb43cf5de9a847fce043bae9b">armnn::experimental::StridedSlicedMultiThreadedEndToEndTest</a></div><div class="ttdeci">void StridedSlicedMultiThreadedEndToEndTest(const std::vector< BackendId > &backends)</div><div class="ttdef"><b>Definition:</b> <a href="_strided_slice_async_end_to_end_test_8hpp_source.xhtml#l00314">StridedSliceAsyncEndToEndTest.hpp:314</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70ba505a83f220c02df2f85c3810cd9ceb38">armnn::Status::Success</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00035">Types.hpp:35</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01613">Network.cpp:1613</a></div></div>
<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_a7c91eda2b331d607bae92cd8ebf50bb9"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#a7c91eda2b331d607bae92cd8ebf50bb9">armnn::StridedSliceDescriptor::m_NewAxisMask</a></div><div class="ttdeci">int32_t m_NewAxisMask</div><div class="ttdoc">New axis mask value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01151">Descriptors.hpp:1151</a></div></div>
<div class="ttc" id="namespacearmnn_1_1experimental_xhtml_a6c8cd7552424617a2e4361c1d966f734"><div class="ttname"><a href="namespacearmnn_1_1experimental.xhtml#a6c8cd7552424617a2e4361c1d966f734">armnn::experimental::AsyncEndToEndTestImpl</a></div><div class="ttdeci">void AsyncEndToEndTestImpl(INetworkPtr network, const std::map< int, std::vector< TInput >> &inputTensorData, const std::map< int, std::vector< TOutput >> &expectedOutputData, std::vector< BackendId > backends, float tolerance=0.000001f, size_t numThreads=1)</div><div class="ttdef"><b>Definition:</b> <a href="_strided_slice_async_end_to_end_test_8hpp_source.xhtml#l00122">StridedSliceAsyncEndToEndTest.hpp:122</a></div></div>
<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_af996d82c47e43a16f4c8faa6c6b3e030"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#af996d82c47e43a16f4c8faa6c6b3e030">armnn::StridedSliceDescriptor::m_EllipsisMask</a></div><div class="ttdeci">int32_t m_EllipsisMask</div><div class="ttdoc">Ellipsis mask value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01148">Descriptors.hpp:1148</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a0d8160388a127c1a23b37bc88dc6e2ec"><div class="ttname"><a href="namespacearmnn.xhtml#a0d8160388a127c1a23b37bc88dc6e2ec">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00024">IRuntime.hpp:24</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00327">Tensor.hpp:327</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00361">Tensor.hpp:361</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="classarmnn_1_1experimental_1_1_i_working_mem_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_i_working_mem_handle.xhtml">armnn::experimental::IWorkingMemHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_working_mem_handle_8hpp_source.xhtml#l00020">IWorkingMemHandle.hpp:20</a></div></div>
<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_a0d53caff836b84204adbd1c28752a201"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#a0d53caff836b84204adbd1c28752a201">armnn::StridedSliceDescriptor::m_Stride</a></div><div class="ttdeci">std::vector< int > m_Stride</div><div class="ttdoc">Stride values for the input that will be sliced. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01137">Descriptors.hpp:1137</a></div></div>
<div class="ttc" id="namespacearmnn_1_1experimental_xhtml_adef78ee82cfcce4c9061f266ccf0a29d"><div class="ttname"><a href="namespacearmnn_1_1experimental.xhtml#adef78ee82cfcce4c9061f266ccf0a29d">armnn::experimental::CreateStridedSliceNetwork</a></div><div class="ttdeci">INetworkPtr CreateStridedSliceNetwork(const TensorShape &inputShape, const TensorShape &outputShape, const std::vector< int > &beginData, const std::vector< int > &endData, const std::vector< int > &stridesData, int beginMask=0, int endMask=0, int shrinkAxisMask=0, int ellipsisMask=0, int newAxisMask=0, const float qScale=1.0f, const int32_t qOffset=0)</div><div class="ttdef"><b>Definition:</b> <a href="_strided_slice_async_end_to_end_test_8hpp_source.xhtml#l00219">StridedSliceAsyncEndToEndTest.hpp:219</a></div></div>
<div class="ttc" id="_i_network_8hpp_xhtml"><div class="ttname"><a href="_i_network_8hpp.xhtml">INetwork.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00101">IRuntime.hpp:101</a></div></div>
<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_aa68194dd6258ab5b04123005a066ea25"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#aa68194dd6258ab5b04123005a066ea25">armnn::StridedSliceDescriptor::m_End</a></div><div class="ttdeci">std::vector< int > m_End</div><div class="ttdoc">End values for the input that will be sliced. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01135">Descriptors.hpp:1135</a></div></div>
<div class="ttc" id="classarmnn_1_1experimental_1_1_threadpool_xhtml"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_threadpool.xhtml">armnn::experimental::Threadpool</a></div><div class="ttdef"><b>Definition:</b> <a href="_threadpool_8hpp_source.xhtml#l00024">Threadpool.hpp:24</a></div></div>
<div class="ttc" id="_async_execution_callback_8hpp_xhtml"><div class="ttname"><a href="_async_execution_callback_8hpp.xhtml">AsyncExecutionCallback.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1experimental_1_1_async_callback_manager_xhtml"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_async_callback_manager.xhtml">armnn::experimental::AsyncCallbackManager</a></div><div class="ttdef"><b>Definition:</b> <a href="_async_execution_callback_8hpp_source.xhtml#l00069">AsyncExecutionCallback.hpp:69</a></div></div>
<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml">armnn::StridedSliceDescriptor</a></div><div class="ttdoc">A StridedSliceDescriptor for the StridedSliceLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01094">Descriptors.hpp:1094</a></div></div>
<div class="ttc" id="_test_utils_8cpp_xhtml_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00012">TestUtils.cpp:12</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00172">INetwork.hpp:172</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00530">Network.cpp:530</a></div></div>
<div class="ttc" id="classarmnn_1_1experimental_1_1_async_callback_manager_xhtml_a9ee5b1dd7d3a6f619d2ed3d97d75d9b1"><div class="ttname"><a href="classarmnn_1_1experimental_1_1_async_callback_manager.xhtml#a9ee5b1dd7d3a6f619d2ed3d97d75d9b1">armnn::experimental::AsyncCallbackManager::GetNotifiedCallback</a></div><div class="ttdeci">std::shared_ptr< AsyncExecutionCallback > GetNotifiedCallback()</div><div class="ttdef"><b>Definition:</b> <a href="_async_execution_callback_8cpp_source.xhtml#l00051">AsyncExecutionCallback.cpp:51</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_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.xhtml">backendsCommon</a></li><li class="navelem"><a class="el" href="dir_28bfe507f7e135bdae07c2a6b7f66696.xhtml">test</a></li><li class="navelem"><a class="el" href="_strided_slice_async_end_to_end_test_8hpp.xhtml">StridedSliceAsyncEndToEndTest.hpp</a></li>
<li class="footer">Generated on Tue Aug 24 2021 16:18:43 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>
|
