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
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
|
<!-- 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/cl/test/ClFallbackTests.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">21.02</span>
</div>
</td>
</tr>
</tbody>
</table>
</div>
<!-- end header part -->
<!-- Generated by Doxygen 1.8.13 -->
<script type="text/javascript">
var searchBox = new SearchBox("searchBox", "search",false,'Search');
</script>
<script type="text/javascript" src="menudata.js"></script>
<script type="text/javascript" src="menu.js"></script>
<script type="text/javascript">
$(function() {
initMenu('',true,false,'search.php','Search');
$(document).ready(function() { init_search(); });
});
</script>
<div id="main-nav"></div>
</div><!-- top -->
<div id="side-nav" class="ui-resizable side-nav-resizable">
<div id="nav-tree">
<div id="nav-tree-contents">
<div id="nav-sync" class="sync"></div>
</div>
</div>
<div id="splitbar" style="-moz-user-select:none;"
class="ui-resizable-handle">
</div>
</div>
<script type="text/javascript">
$(document).ready(function(){initNavTree('_cl_fallback_tests_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">ClFallbackTests.cpp File Reference</div> </div>
</div><!--header-->
<div class="contents">
<div class="textblock"><code>#include <<a class="el" href="_common_test_utils_8hpp_source.xhtml">backendsCommon/test/CommonTestUtils.hpp</a>></code><br />
<code>#include <<a class="el" href="_graph_utils_8hpp_source.xhtml">test/GraphUtils.hpp</a>></code><br />
<code>#include <boost/test/unit_test.hpp></code><br />
</div>
<p><a href="_cl_fallback_tests_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:af63c7e2def59e048cf7df08ebef3a1f0"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_cl_fallback_tests_8cpp.xhtml#af63c7e2def59e048cf7df08ebef3a1f0">BOOST_AUTO_TEST_CASE</a> (ClImportEnabledFallbackToNeon)</td></tr>
<tr class="separator:af63c7e2def59e048cf7df08ebef3a1f0"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a80907255c8ac09ae9b200c38396249b8"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_cl_fallback_tests_8cpp.xhtml#a80907255c8ac09ae9b200c38396249b8">BOOST_AUTO_TEST_CASE</a> (ClImportDisabledFallbackToNeon)</td></tr>
<tr class="separator:a80907255c8ac09ae9b200c38396249b8"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:ade94e5ddaebf77f2affcff5f745e05a1"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_cl_fallback_tests_8cpp.xhtml#ade94e5ddaebf77f2affcff5f745e05a1">BOOST_AUTO_TEST_CASE</a> (ClImportEnabledFallbackSubgraphToNeon)</td></tr>
<tr class="separator:ade94e5ddaebf77f2affcff5f745e05a1"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:a818d7c05921cbc3c9aa0c16c8f95a0ca"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="_cl_fallback_tests_8cpp.xhtml#a818d7c05921cbc3c9aa0c16c8f95a0ca">BOOST_AUTO_TEST_CASE</a> (ClImportDisableFallbackSubgraphToNeon)</td></tr>
<tr class="separator:a818d7c05921cbc3c9aa0c16c8f95a0ca"><td class="memSeparator" colspan="2"> </td></tr>
</table>
<h2 class="groupheader">Function Documentation</h2>
<a id="af63c7e2def59e048cf7df08ebef3a1f0"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af63c7e2def59e048cf7df08ebef3a1f0">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[1/4]</span></h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">BOOST_AUTO_TEST_CASE </td>
<td>(</td>
<td class="paramtype">ClImportEnabledFallbackToNeon </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="_cl_fallback_tests_8cpp_source.xhtml#l00014">14</a> of file <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml">ClFallbackTests.cpp</a>.</p>
<p class="reference">References <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">IConnectableLayer::BackendSelectionHint()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00068">CheckOrder()</a>, <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">IOutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::CpuAcc</a>, <a class="el" href="_runtime_8cpp_source.xhtml#l00037">IRuntime::Create()</a>, <a class="el" href="_network_8cpp_source.xhtml#l00510">INetwork::Create()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00269">Layer::GetBackendId()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00022">GetFirstLayerWithName()</a>, <a class="el" href="_test_utils_8cpp_source.xhtml#l00025">armnn::GetGraphForTesting()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">IConnectableLayer::GetInputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00489">ProfilerManager::GetInstance()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">IConnectableLayer::GetOutputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00501">ProfilerManager::GetProfiler()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00265">Layer::GetType()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::GpuAcc</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="_i_network_8hpp_source.xhtml#l00165">OptimizerOptions::m_ImportEnabled</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::MemCopy</a>, <a class="el" href="_network_8cpp_source.xhtml#l01502">armnn::Optimize()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00522">IProfiler::Print()</a>, and <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">IOutputSlot::SetTensorInfo()</a>.</p>
<div class="fragment"><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> {</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</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>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</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="l00020"></a><span class="lineno"> 20</span> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</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="l00023"></a><span class="lineno"> 23</span> </div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input0 = net->AddInputLayer(0, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input1 = net->AddInputLayer(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input2 = net->AddInputLayer(2, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* add = net->AddAdditionLayer(<span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* sub = net->AddSubtractionLayer(<span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = net->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</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>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</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>  std::vector<BackendId> backends = { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">Compute::GpuAcc</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> };</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="comment">// Use BackendSelectionHint to specify CpuAcc for Subtraction layer</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">BackendSelectionHint</a>(backends[1]);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="comment">// optimize the network</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a> optOptions;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  optOptions.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a05c1bba6ba3ecc1339d4c4c10c0d8890">m_ImportEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*net, backends, runtime->GetDeviceSpec(), optOptions);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = <a class="code" href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">GetGraphForTesting</a>(optNet.get());</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>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer0 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer1 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer2 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer3 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer4 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ add (0) -> sub (1) ]"</span>);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer5 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer6 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// Checks order is valid.</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer0, layer1));</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer1, layer2));</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer2, layer3));</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer3, layer4));</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer4, layer5));</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer5, layer6));</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>  <span class="comment">// Use memory import between backends</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  BOOST_TEST((layer4-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> </div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="comment">// Correctly use backend hint</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  BOOST_TEST((layer5-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> ));</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="comment">// Load it into the runtime. It should pass.</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  std::string ignoredErrorMessage;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="structarmnn_1_1_i_network_properties.xhtml">INetworkProperties</a> networkProperties(<span class="keyword">true</span>, <span class="keyword">true</span>);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  runtime->LoadNetwork(netId, std::move(optNet), ignoredErrorMessage, networkProperties);</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>  <span class="comment">// Creates structures for input & output</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  std::vector<float> inputData0</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>  1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f, 6.0f</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>  std::vector<float> inputData1</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  {</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  0.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  };</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  std::vector<float> inputData2</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  {</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  12.0f, 11.0f, 10.0f, 9.0f, 8.0f, 7.0f, 6.0f, 5.0f, 4.0f, 3.0f, 2.0f, 1.0f</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>  std::vector<float> outputData(12);</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  std::vector<float> expectedOutput</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  {</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  11.0f, 9.0f, 7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f, -7.0f, -9.0f, -11.0f</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  };</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors</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>  { 0, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 0), inputData0.data()) },</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  { 1, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 1), inputData1.data()) },</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  { 2, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 2), inputData2.data()) }</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  };</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  {</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  { 0,<a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(runtime->GetOutputTensorInfo(netId, 0), outputData.data()) }</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>  runtime->GetProfiler(netId)->EnableProfiling(<span class="keyword">true</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>  <span class="comment">// Do the inference</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  runtime->EnqueueWorkload(netId, inputTensors, outputTensors);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="comment">// Retrieve the Profiler.Print() output to get the workload execution</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <a class="code" href="classarmnn_1_1_profiler_manager.xhtml">ProfilerManager</a>& profilerManager = <a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a>();</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  std::stringstream ss;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  profilerManager.<a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">GetProfiler</a>()-><a class="code" href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">Print</a>(ss);;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  std::string dump = ss.str();</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="comment">// Executed Subtraction using CpuAcc</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  std::size_t found = dump.find(<span class="stringliteral">"NeonSubtractionWorkload_Execute"</span>);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="comment">// Contain CopyMemGeneric</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  found = dump.find(<span class="stringliteral">"CopyMemGeneric"</span>);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  BOOST_TEST(found != std::string::npos);</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">// Check output is as expected</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  BOOST_TEST(outputData == expectedOutput);</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</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#l00037">Runtime.cpp:37</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#l00062">INetwork.hpp:62</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_a5f17e02e0054dac0a691685a0464ed36"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a></div><div class="ttdeci">armnn::Layer * GetFirstLayerWithName(armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00022">GraphUtils.cpp:22</a></div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a93857080c2523bf3395e7aa7e6024d5c"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a></div><div class="ttdeci">static ProfilerManager & GetInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00489">Profiling.cpp:489</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_a21d963c71be62057ed99b5007e7bbbfd"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a></div><div class="ttdeci">bool CheckOrder(const armnn::Graph &graph, const armnn::Layer *first, const armnn::Layer *second)</div><div class="ttdoc">Checks that first comes before second in the order. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00068">GraphUtils.cpp:68</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a833170f92e96b3ef414b6cf6e5720d2b"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">armnn::IConnectableLayer::BackendSelectionHint</a></div><div class="ttdeci">virtual void BackendSelectionHint(Optional< BackendId > backend)=0</div><div class="ttdoc">Provide a hint for the optimizer as to which backend to prefer for this layer. </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#l00026">IRuntime.hpp:26</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_profiler_xhtml_a038bb767bbc6abc0ee0d9b509616b896"><div class="ttname"><a href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">armnn::IProfiler::Print</a></div><div class="ttdeci">void Print(std::ostream &outStream) const</div><div class="ttdoc">Print stats for events in JSON Format to the given output stream. </div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00522">Profiling.cpp:522</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00340">Tensor.hpp:340</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00020">IRuntime.hpp:20</a></div></div>
<div class="ttc" id="namespacearmnn_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="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</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#l00028">IRuntime.hpp:28</a></div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a3756986bc88b9b212d3f983c70c5c129"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">armnn::ProfilerManager::GetProfiler</a></div><div class="ttdeci">IProfiler * GetProfiler()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00501">Profiling.cpp:501</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00306">Tensor.hpp:306</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</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#l00174">INetwork.hpp:174</a></div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml">armnn::ProfilerManager</a></div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00091">Profiling.hpp:91</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div>
<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml">armnn::OptimizerOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00110">INetwork.hpp:110</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_afdb1d37740e7a083b625d669588b6a0e"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">armnn::Layer::GetBackendId</a></div><div class="ttdeci">const BackendId & GetBackendId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00269">Layer.hpp:269</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div>
<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml_a05c1bba6ba3ecc1339d4c4c10c0d8890"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a05c1bba6ba3ecc1339d4c4c10c0d8890">armnn::OptimizerOptions::m_ImportEnabled</a></div><div class="ttdeci">bool m_ImportEnabled</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00165">INetwork.hpp:165</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#l00043">IRuntime.hpp:43</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a6a2659750d6161b693d0e51616791959"><div class="ttname"><a href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">armnn::GetGraphForTesting</a></div><div class="ttdeci">Graph & GetGraphForTesting(IOptimizedNetwork *optNet)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00025">TestUtils.cpp:25</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a></div><div class="ttdoc">CPU Execution: NEON: ArmCompute. </div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </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_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#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</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#l00510">Network.cpp:510</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</a></div></div>
</div><!-- fragment -->
</div>
</div>
<a id="a80907255c8ac09ae9b200c38396249b8"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a80907255c8ac09ae9b200c38396249b8">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[2/4]</span></h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">BOOST_AUTO_TEST_CASE </td>
<td>(</td>
<td class="paramtype">ClImportDisabledFallbackToNeon </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="_cl_fallback_tests_8cpp_source.xhtml#l00140">140</a> of file <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml">ClFallbackTests.cpp</a>.</p>
<p class="reference">References <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">IConnectableLayer::BackendSelectionHint()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00068">CheckOrder()</a>, <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">IOutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::CpuAcc</a>, <a class="el" href="_runtime_8cpp_source.xhtml#l00037">IRuntime::Create()</a>, <a class="el" href="_network_8cpp_source.xhtml#l00510">INetwork::Create()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00269">Layer::GetBackendId()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00022">GetFirstLayerWithName()</a>, <a class="el" href="_test_utils_8cpp_source.xhtml#l00025">armnn::GetGraphForTesting()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">IConnectableLayer::GetInputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00489">ProfilerManager::GetInstance()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">IConnectableLayer::GetOutputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00501">ProfilerManager::GetProfiler()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00265">Layer::GetType()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::GpuAcc</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::MemCopy</a>, <a class="el" href="_network_8cpp_source.xhtml#l01502">armnn::Optimize()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00522">IProfiler::Print()</a>, and <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">IOutputSlot::SetTensorInfo()</a>.</p>
<div class="fragment"><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>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</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>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</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="l00146"></a><span class="lineno"> 146</span> </div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</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="l00149"></a><span class="lineno"> 149</span> </div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input0 = net->AddInputLayer(0, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input1 = net->AddInputLayer(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input2 = net->AddInputLayer(2, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* add = net->AddAdditionLayer(<span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* sub = net->AddSubtractionLayer(<span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = net->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</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>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  std::vector<BackendId> backends = { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">Compute::GpuAcc</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> };</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="comment">// Use BackendSelectionHint to specify CpuAcc for Subtraction layer</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">BackendSelectionHint</a>(backends[1]);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> </div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="comment">// optimize the network</span></div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a> optOptions;</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*net, backends, runtime->GetDeviceSpec(), optOptions);</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = <a class="code" href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">GetGraphForTesting</a>(optNet.get());</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer0 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer1 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer2 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer3 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer4 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ add (0) -> sub (1) ]"</span>);</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer5 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer6 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="comment">// Checks order is valid.</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer0, layer1));</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer1, layer2));</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer2, layer3));</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer3, layer4));</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer4, layer5));</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer5, layer6));</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">// Use memory import between backends</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  BOOST_TEST((layer4-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</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="comment">// Correctly use backend hint</span></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  BOOST_TEST((layer5-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> ));</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="comment">// Load it into the runtime. It should pass.</span></div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  runtime->LoadNetwork(netId, std::move(optNet));</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="comment">// Creates structures for input & output</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  std::vector<float> inputData0</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  {</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f, 6.0f</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  };</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  std::vector<float> inputData1</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  {</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  0.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f</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>  std::vector<float> inputData2</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>  12.0f, 11.0f, 10.0f, 9.0f, 8.0f, 7.0f, 6.0f, 5.0f, 4.0f, 3.0f, 2.0f, 1.0f</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> </div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  std::vector<float> outputData(12);</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> </div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  std::vector<float> expectedOutput</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  {</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  11.0f, 9.0f, 7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f, -7.0f, -9.0f, -11.0f</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  };</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> </div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors</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>  { 0, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 0), inputData0.data()) },</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  { 1, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 1), inputData1.data()) },</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  { 2, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 2), inputData2.data()) }</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  };</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors</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>  { 0,<a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(runtime->GetOutputTensorInfo(netId, 0), outputData.data()) }</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> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  runtime->GetProfiler(netId)->EnableProfiling(<span class="keyword">true</span>);</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="comment">// Do the inference</span></div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  runtime->EnqueueWorkload(netId, inputTensors, outputTensors);</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <span class="comment">// Retrieve the Profiler.Print() output to get the workload execution</span></div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <a class="code" href="classarmnn_1_1_profiler_manager.xhtml">ProfilerManager</a>& profilerManager = <a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a>();</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  std::stringstream ss;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  profilerManager.<a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">GetProfiler</a>()-><a class="code" href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">Print</a>(ss);;</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  std::string dump = ss.str();</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="comment">// Executed Subtraction using CpuAcc</span></div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  std::size_t found = dump.find(<span class="stringliteral">"NeonSubtractionWorkload_Execute"</span>);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> </div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="comment">// Contain CopyMemGeneric</span></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  found = dump.find(<span class="stringliteral">"CopyMemGeneric"</span>);</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  BOOST_TEST(found != std::string::npos);</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>  <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  BOOST_TEST(outputData == expectedOutput);</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</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#l00037">Runtime.cpp:37</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#l00062">INetwork.hpp:62</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_a5f17e02e0054dac0a691685a0464ed36"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a></div><div class="ttdeci">armnn::Layer * GetFirstLayerWithName(armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00022">GraphUtils.cpp:22</a></div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a93857080c2523bf3395e7aa7e6024d5c"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a></div><div class="ttdeci">static ProfilerManager & GetInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00489">Profiling.cpp:489</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_a21d963c71be62057ed99b5007e7bbbfd"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a></div><div class="ttdeci">bool CheckOrder(const armnn::Graph &graph, const armnn::Layer *first, const armnn::Layer *second)</div><div class="ttdoc">Checks that first comes before second in the order. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00068">GraphUtils.cpp:68</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a833170f92e96b3ef414b6cf6e5720d2b"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">armnn::IConnectableLayer::BackendSelectionHint</a></div><div class="ttdeci">virtual void BackendSelectionHint(Optional< BackendId > backend)=0</div><div class="ttdoc">Provide a hint for the optimizer as to which backend to prefer for this layer. </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#l00026">IRuntime.hpp:26</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_profiler_xhtml_a038bb767bbc6abc0ee0d9b509616b896"><div class="ttname"><a href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">armnn::IProfiler::Print</a></div><div class="ttdeci">void Print(std::ostream &outStream) const</div><div class="ttdoc">Print stats for events in JSON Format to the given output stream. </div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00522">Profiling.cpp:522</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00340">Tensor.hpp:340</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00020">IRuntime.hpp:20</a></div></div>
<div class="ttc" id="namespacearmnn_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="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a3756986bc88b9b212d3f983c70c5c129"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">armnn::ProfilerManager::GetProfiler</a></div><div class="ttdeci">IProfiler * GetProfiler()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00501">Profiling.cpp:501</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00306">Tensor.hpp:306</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</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#l00174">INetwork.hpp:174</a></div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml">armnn::ProfilerManager</a></div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00091">Profiling.hpp:91</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div>
<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml">armnn::OptimizerOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00110">INetwork.hpp:110</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_afdb1d37740e7a083b625d669588b6a0e"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">armnn::Layer::GetBackendId</a></div><div class="ttdeci">const BackendId & GetBackendId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00269">Layer.hpp:269</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</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#l00043">IRuntime.hpp:43</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a6a2659750d6161b693d0e51616791959"><div class="ttname"><a href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">armnn::GetGraphForTesting</a></div><div class="ttdeci">Graph & GetGraphForTesting(IOptimizedNetwork *optNet)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00025">TestUtils.cpp:25</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a></div><div class="ttdoc">CPU Execution: NEON: ArmCompute. </div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </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_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#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</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#l00510">Network.cpp:510</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</a></div></div>
</div><!-- fragment -->
</div>
</div>
<a id="ade94e5ddaebf77f2affcff5f745e05a1"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ade94e5ddaebf77f2affcff5f745e05a1">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[3/4]</span></h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">BOOST_AUTO_TEST_CASE </td>
<td>(</td>
<td class="paramtype">ClImportEnabledFallbackSubgraphToNeon </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="_cl_fallback_tests_8cpp_source.xhtml#l00262">262</a> of file <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml">ClFallbackTests.cpp</a>.</p>
<p class="reference">References <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">IConnectableLayer::BackendSelectionHint()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00068">CheckOrder()</a>, <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">IOutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::CpuAcc</a>, <a class="el" href="_runtime_8cpp_source.xhtml#l00037">IRuntime::Create()</a>, <a class="el" href="_network_8cpp_source.xhtml#l00510">INetwork::Create()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00269">Layer::GetBackendId()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00022">GetFirstLayerWithName()</a>, <a class="el" href="_test_utils_8cpp_source.xhtml#l00025">armnn::GetGraphForTesting()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">IConnectableLayer::GetInputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00489">ProfilerManager::GetInstance()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">IConnectableLayer::GetOutputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00501">ProfilerManager::GetProfiler()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00265">Layer::GetType()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::GpuAcc</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="_i_network_8hpp_source.xhtml#l00165">OptimizerOptions::m_ImportEnabled</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::MemCopy</a>, <a class="el" href="_network_8cpp_source.xhtml#l01502">armnn::Optimize()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00522">IProfiler::Print()</a>, and <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">IOutputSlot::SetTensorInfo()</a>.</p>
<div class="fragment"><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> {</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> </div><div class="line"><a name="l00266"></a><span class="lineno"> 266</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="l00267"></a><span class="lineno"> 267</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="l00268"></a><span class="lineno"> 268</span> </div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</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="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">Pooling2dDescriptor</a> desc;</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> </div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input0 = net->AddInputLayer(0, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input1 = net->AddInputLayer(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input2 = net->AddInputLayer(2, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* add = net->AddAdditionLayer(<span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* sub = net->AddSubtractionLayer(<span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* pooling = net->AddPooling2dLayer(desc, <span class="stringliteral">"pooling"</span>);</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = net->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> </div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> </div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> poolingInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> </div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(poolingInfo);</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  std::vector<BackendId> backends = { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">Compute::GpuAcc</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> };</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="comment">// Use BackendSelectionHint to specify CpuAcc for Subtraction layer</span></div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">BackendSelectionHint</a>(backends[1]);</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> </div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="comment">// optimize the network</span></div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a> optOptions;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  optOptions.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a05c1bba6ba3ecc1339d4c4c10c0d8890">m_ImportEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*net, backends, runtime->GetDeviceSpec(), optOptions);</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> </div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = <a class="code" href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">GetGraphForTesting</a>(optNet.get());</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> </div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer0 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer1 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer2 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer3 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer4 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ add (0) -> sub (1) ]"</span>);</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer5 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer6 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ sub (0) -> pooling (0) ]"</span>);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer7 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"pooling"</span>);</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer8 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> </div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="comment">// Checks order is valid.</span></div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer0, layer1));</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer1, layer2));</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer2, layer3));</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer3, layer4));</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer4, layer5));</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer5, layer6));</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer6, layer7));</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer7, layer8));</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">// Use memory import between backends</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  BOOST_TEST((layer4-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  BOOST_TEST((layer6-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> </div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="comment">// Correctly use backend hint</span></div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  BOOST_TEST((layer5-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> ));</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> </div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="comment">// Load it into the runtime. It should pass.</span></div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  std::string ignoredErrorMessage;</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <a class="code" href="structarmnn_1_1_i_network_properties.xhtml">INetworkProperties</a> networkProperties(<span class="keyword">true</span>, <span class="keyword">true</span>);</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>  runtime->LoadNetwork(netId, std::move(optNet), ignoredErrorMessage, networkProperties);</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<float> inputData0</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  {</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f, 6.0f</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  };</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  std::vector<float> inputData1</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  {</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  0.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f</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<float> inputData2</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>  12.0f, 11.0f, 10.0f, 9.0f, 8.0f, 7.0f, 6.0f, 5.0f, 4.0f, 3.0f, 2.0f, 1.0f</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  };</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> </div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  std::vector<float> outputData(2);</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span> </div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  std::vector<float> expectedOutput{ 11.0f, -1.0f };</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span> </div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors</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>  { 0, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 0), inputData0.data()) },</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  { 1, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 1), inputData1.data()) },</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  { 2, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 2), inputData2.data()) }</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  };</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  {</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  { 0,<a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(runtime->GetOutputTensorInfo(netId, 0), outputData.data()) }</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  };</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> </div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  runtime->GetProfiler(netId)->EnableProfiling(<span class="keyword">true</span>);</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> </div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="comment">// Do the inference</span></div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  runtime->EnqueueWorkload(netId, inputTensors, outputTensors);</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="comment">// Retrieve the Profiler.Print() output to get the workload execution</span></div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <a class="code" href="classarmnn_1_1_profiler_manager.xhtml">ProfilerManager</a>& profilerManager = <a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a>();</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  std::stringstream ss;</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  profilerManager.<a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">GetProfiler</a>()-><a class="code" href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">Print</a>(ss);;</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  std::string dump = ss.str();</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> </div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="comment">// Executed Subtraction using CpuAcc</span></div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  std::size_t found = dump.find(<span class="stringliteral">"NeonSubtractionWorkload_Execute"</span>);</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> </div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="comment">// Correctly switch back to GpuAcc</span></div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  found = dump.find(<span class="stringliteral">"ClPooling2dWorkload_Execute"</span>);</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> </div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="comment">// Contain CopyMemGeneric</span></div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  found = dump.find(<span class="stringliteral">"CopyMemGeneric"</span>);</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> </div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  BOOST_TEST(outputData == expectedOutput);</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</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#l00037">Runtime.cpp:37</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#l00062">INetwork.hpp:62</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_a5f17e02e0054dac0a691685a0464ed36"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a></div><div class="ttdeci">armnn::Layer * GetFirstLayerWithName(armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00022">GraphUtils.cpp:22</a></div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a93857080c2523bf3395e7aa7e6024d5c"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a></div><div class="ttdeci">static ProfilerManager & GetInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00489">Profiling.cpp:489</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_a21d963c71be62057ed99b5007e7bbbfd"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a></div><div class="ttdeci">bool CheckOrder(const armnn::Graph &graph, const armnn::Layer *first, const armnn::Layer *second)</div><div class="ttdoc">Checks that first comes before second in the order. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00068">GraphUtils.cpp:68</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a833170f92e96b3ef414b6cf6e5720d2b"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">armnn::IConnectableLayer::BackendSelectionHint</a></div><div class="ttdeci">virtual void BackendSelectionHint(Optional< BackendId > backend)=0</div><div class="ttdoc">Provide a hint for the optimizer as to which backend to prefer for this layer. </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#l00026">IRuntime.hpp:26</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_profiler_xhtml_a038bb767bbc6abc0ee0d9b509616b896"><div class="ttname"><a href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">armnn::IProfiler::Print</a></div><div class="ttdeci">void Print(std::ostream &outStream) const</div><div class="ttdoc">Print stats for events in JSON Format to the given output stream. </div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00522">Profiling.cpp:522</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00340">Tensor.hpp:340</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00020">IRuntime.hpp:20</a></div></div>
<div class="ttc" id="namespacearmnn_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="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</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#l00028">IRuntime.hpp:28</a></div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a3756986bc88b9b212d3f983c70c5c129"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">armnn::ProfilerManager::GetProfiler</a></div><div class="ttdeci">IProfiler * GetProfiler()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00501">Profiling.cpp:501</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00306">Tensor.hpp:306</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</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#l00174">INetwork.hpp:174</a></div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml">armnn::ProfilerManager</a></div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00091">Profiling.hpp:91</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div>
<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml">armnn::OptimizerOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00110">INetwork.hpp:110</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_afdb1d37740e7a083b625d669588b6a0e"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">armnn::Layer::GetBackendId</a></div><div class="ttdeci">const BackendId & GetBackendId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00269">Layer.hpp:269</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div>
<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml_a05c1bba6ba3ecc1339d4c4c10c0d8890"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a05c1bba6ba3ecc1339d4c4c10c0d8890">armnn::OptimizerOptions::m_ImportEnabled</a></div><div class="ttdeci">bool m_ImportEnabled</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00165">INetwork.hpp:165</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#l00043">IRuntime.hpp:43</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a6a2659750d6161b693d0e51616791959"><div class="ttname"><a href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">armnn::GetGraphForTesting</a></div><div class="ttdeci">Graph & GetGraphForTesting(IOptimizedNetwork *optNet)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00025">TestUtils.cpp:25</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a></div><div class="ttdoc">CPU Execution: NEON: ArmCompute. </div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </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_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#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00329">Descriptors.hpp:329</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#l00510">Network.cpp:510</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</a></div></div>
</div><!-- fragment -->
</div>
</div>
<a id="a818d7c05921cbc3c9aa0c16c8f95a0ca"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a818d7c05921cbc3c9aa0c16c8f95a0ca">◆ </a></span>BOOST_AUTO_TEST_CASE() <span class="overload">[4/4]</span></h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">BOOST_AUTO_TEST_CASE </td>
<td>(</td>
<td class="paramtype">ClImportDisableFallbackSubgraphToNeon </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="_cl_fallback_tests_8cpp_source.xhtml#l00400">400</a> of file <a class="el" href="_cl_fallback_tests_8cpp_source.xhtml">ClFallbackTests.cpp</a>.</p>
<p class="reference">References <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">IConnectableLayer::BackendSelectionHint()</a>, <a class="el" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00068">CheckOrder()</a>, <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">IOutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::CpuAcc</a>, <a class="el" href="_runtime_8cpp_source.xhtml#l00037">IRuntime::Create()</a>, <a class="el" href="_network_8cpp_source.xhtml#l00510">INetwork::Create()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00269">Layer::GetBackendId()</a>, <a class="el" href="_graph_utils_8cpp_source.xhtml#l00022">GetFirstLayerWithName()</a>, <a class="el" href="_test_utils_8cpp_source.xhtml#l00025">armnn::GetGraphForTesting()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">IConnectableLayer::GetInputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00489">ProfilerManager::GetInstance()</a>, <a class="el" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">IConnectableLayer::GetOutputSlot()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00501">ProfilerManager::GetProfiler()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00265">Layer::GetType()</a>, <a class="el" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::GpuAcc</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::MemCopy</a>, <a class="el" href="_network_8cpp_source.xhtml#l01502">armnn::Optimize()</a>, <a class="el" href="_profiling_8cpp_source.xhtml#l00522">IProfiler::Print()</a>, and <a class="el" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">IOutputSlot::SetTensorInfo()</a>.</p>
<div class="fragment"><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> {</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span> </div><div class="line"><a name="l00404"></a><span class="lineno"> 404</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="l00405"></a><span class="lineno"> 405</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="l00406"></a><span class="lineno"> 406</span> </div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00408"></a><span class="lineno"> 408</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="l00409"></a><span class="lineno"> 409</span> </div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <a class="code" href="structarmnn_1_1_pooling2d_descriptor.xhtml">Pooling2dDescriptor</a> desc;</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> </div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input0 = net->AddInputLayer(0, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input1 = net->AddInputLayer(1, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input2 = net->AddInputLayer(2, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* add = net->AddAdditionLayer(<span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* sub = net->AddSubtractionLayer(<span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* pooling = net->AddPooling2dLayer(desc, <span class="stringliteral">"pooling"</span>);</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = net->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> </div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> </div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a> = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> poolingInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span> </div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  input0-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  input1-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  input2-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  add-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  pooling-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(poolingInfo);</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  std::vector<BackendId> backends = { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">Compute::GpuAcc</a>, <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> };</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <span class="comment">// Use BackendSelectionHint to specify CpuAcc for Subtraction layer</span></div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  sub-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">BackendSelectionHint</a>(backends[1]);</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span> </div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="comment">// optimize the network</span></div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a> optOptions;</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*net, backends, runtime->GetDeviceSpec(), optOptions);</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span> </div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = <a class="code" href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">GetGraphForTesting</a>(optNet.get());</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span> </div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer0 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer1 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input1"</span>);</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer2 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"input2"</span>);</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer3 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"add"</span>);</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer4 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ add (0) -> sub (1) ]"</span>);</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer5 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"sub"</span>);</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer6 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"[ sub (0) -> pooling (0) ]"</span>);</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer7 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"pooling"</span>);</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> layer8 = <a class="code" href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a>(graph, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="comment">// Checks order is valid.</span></div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer0, layer1));</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer1, layer2));</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer2, layer3));</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer3, layer4));</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer4, layer5));</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer5, layer6));</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer6, layer7));</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a>(graph, layer7, layer8));</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span> </div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="comment">// Use memory import between backends</span></div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  BOOST_TEST((layer4-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  BOOST_TEST((layer6-><a class="code" href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">LayerType::MemCopy</a>));</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span> </div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <span class="comment">// Correctly use backend hint</span></div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  BOOST_TEST((layer5-><a class="code" href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">GetBackendId</a>() == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">Compute::CpuAcc</a> ));</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span> </div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="comment">// Load it into the runtime. It should pass.</span></div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  runtime->LoadNetwork(netId, std::move(optNet));</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span> </div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <span class="comment">// Creates structures for input & output</span></div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  std::vector<float> inputData0</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  {</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  1.0f, 1.0f, 2.0f, 2.0f, 2.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f, 6.0f</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  };</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  std::vector<float> inputData1</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  {</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  0.0f, 1.0f, 1.0f, 2.0f, 3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 5.0f, 5.0f, 6.0f</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  };</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  std::vector<float> inputData2</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  {</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  12.0f, 11.0f, 10.0f, 9.0f, 8.0f, 7.0f, 6.0f, 5.0f, 4.0f, 3.0f, 2.0f, 1.0f</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  };</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span> </div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  std::vector<float> outputData(2);</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span> </div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  std::vector<float> expectedOutput{ 11.0f, -1.0f };</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span> </div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputTensors</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  {</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  { 0, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 0), inputData0.data()) },</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  { 1, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 1), inputData1.data()) },</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  { 2, <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(runtime->GetInputTensorInfo(netId, 2), inputData2.data()) }</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  };</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  {</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  { 0,<a class="code" href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a>(runtime->GetOutputTensorInfo(netId, 0), outputData.data()) }</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  };</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span> </div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  runtime->GetProfiler(netId)->EnableProfiling(<span class="keyword">true</span>);</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span> </div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <span class="comment">// Do the inference</span></div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  runtime->EnqueueWorkload(netId, inputTensors, outputTensors);</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span> </div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <span class="comment">// Retrieve the Profiler.Print() output to get the workload execution</span></div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  <a class="code" href="classarmnn_1_1_profiler_manager.xhtml">ProfilerManager</a>& profilerManager = <a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a>();</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  std::stringstream ss;</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  profilerManager.<a class="code" href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">GetProfiler</a>()-><a class="code" href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">Print</a>(ss);;</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  std::string dump = ss.str();</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span> </div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="comment">// Executed Subtraction using CpuAcc</span></div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  std::size_t found = dump.find(<span class="stringliteral">"NeonSubtractionWorkload_Execute"</span>);</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span> </div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <span class="comment">// Correctly switch back to GpuAcc</span></div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  found = dump.find(<span class="stringliteral">"ClPooling2dWorkload_Execute"</span>);</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span> </div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  <span class="comment">// Contain CopyMemGeneric</span></div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  found = dump.find(<span class="stringliteral">"CopyMemGeneric"</span>);</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  BOOST_TEST(found != std::string::npos);</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span> </div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  BOOST_TEST(outputData == expectedOutput);</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</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#l00037">Runtime.cpp:37</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#l00062">INetwork.hpp:62</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_a5f17e02e0054dac0a691685a0464ed36"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a5f17e02e0054dac0a691685a0464ed36">GetFirstLayerWithName</a></div><div class="ttdeci">armnn::Layer * GetFirstLayerWithName(armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00022">GraphUtils.cpp:22</a></div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a93857080c2523bf3395e7aa7e6024d5c"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a93857080c2523bf3395e7aa7e6024d5c">armnn::ProfilerManager::GetInstance</a></div><div class="ttdeci">static ProfilerManager & GetInstance()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00489">Profiling.cpp:489</a></div></div>
<div class="ttc" id="_graph_utils_8cpp_xhtml_a21d963c71be62057ed99b5007e7bbbfd"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#a21d963c71be62057ed99b5007e7bbbfd">CheckOrder</a></div><div class="ttdeci">bool CheckOrder(const armnn::Graph &graph, const armnn::Layer *first, const armnn::Layer *second)</div><div class="ttdoc">Checks that first comes before second in the order. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00068">GraphUtils.cpp:68</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a833170f92e96b3ef414b6cf6e5720d2b"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a833170f92e96b3ef414b6cf6e5720d2b">armnn::IConnectableLayer::BackendSelectionHint</a></div><div class="ttdeci">virtual void BackendSelectionHint(Optional< BackendId > backend)=0</div><div class="ttdoc">Provide a hint for the optimizer as to which backend to prefer for this layer. </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#l00026">IRuntime.hpp:26</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_profiler_xhtml_a038bb767bbc6abc0ee0d9b509616b896"><div class="ttname"><a href="classarmnn_1_1_i_profiler.xhtml#a038bb767bbc6abc0ee0d9b509616b896">armnn::IProfiler::Print</a></div><div class="ttdeci">void Print(std::ostream &outStream) const</div><div class="ttdoc">Print stats for events in JSON Format to the given output stream. </div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00522">Profiling.cpp:522</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00340">Tensor.hpp:340</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00020">IRuntime.hpp:20</a></div></div>
<div class="ttc" id="namespacearmnn_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="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml_a3756986bc88b9b212d3f983c70c5c129"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml#a3756986bc88b9b212d3f983c70c5c129">armnn::ProfilerManager::GetProfiler</a></div><div class="ttdeci">IProfiler * GetProfiler()</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8cpp_source.xhtml#l00501">Profiling.cpp:501</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00306">Tensor.hpp:306</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01502">Network.cpp:1502</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00265">Layer.hpp:265</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a4dd48794eb3305a0f5aece88b111a97b">armnn::LayerType::MemCopy</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#l00174">INetwork.hpp:174</a></div></div>
<div class="ttc" id="classarmnn_1_1_profiler_manager_xhtml"><div class="ttname"><a href="classarmnn_1_1_profiler_manager.xhtml">armnn::ProfilerManager</a></div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00091">Profiling.hpp:91</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div>
<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml">armnn::OptimizerOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00110">INetwork.hpp:110</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_afdb1d37740e7a083b625d669588b6a0e"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#afdb1d37740e7a083b625d669588b6a0e">armnn::Layer::GetBackendId</a></div><div class="ttdeci">const BackendId & GetBackendId() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00269">Layer.hpp:269</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</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#l00043">IRuntime.hpp:43</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a6a2659750d6161b693d0e51616791959"><div class="ttname"><a href="namespacearmnn.xhtml#a6a2659750d6161b693d0e51616791959">armnn::GetGraphForTesting</a></div><div class="ttdeci">Graph & GetGraphForTesting(IOptimizedNetwork *optNet)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00025">TestUtils.cpp:25</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a></div><div class="ttdoc">CPU Execution: NEON: ArmCompute. </div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </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_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#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00329">Descriptors.hpp:329</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#l00510">Network.cpp:510</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</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_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_1ad86c6d39ab715a831555571b9e98a5.xhtml">cl</a></li><li class="navelem"><a class="el" href="dir_02bab2737bbb2fb3882a0be567244fbf.xhtml">test</a></li><li class="navelem"><a class="el" href="_cl_fallback_tests_8cpp.xhtml">ClFallbackTests.cpp</a></li>
<li class="footer">Generated on Thu Feb 25 2021 17:27:55 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>
|
