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
|
<!-- 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/armnn/NetworkQuantizer.cpp Source File</title>
<link href="tabs.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<link href="navtree.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="resize.js"></script>
<script type="text/javascript" src="navtreedata.js"></script>
<script type="text/javascript" src="navtree.js"></script>
<script type="text/javascript">
$(document).ready(initResizable);
</script>
<link href="search/search.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="search/searchdata.js"></script>
<script type="text/javascript" src="search/search.js"></script>
<script type="text/x-mathjax-config">
MathJax.Hub.Config({
extensions: ["tex2jax.js"],
jax: ["input/TeX","output/HTML-CSS"],
});
</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script>
<link href="doxygen.css" rel="stylesheet" type="text/css" />
<link href="stylesheet.css" rel="stylesheet" type="text/css"/>
</head>
<body>
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
<div id="titlearea">
<table cellspacing="0" cellpadding="0">
<tbody>
<tr style="height: 56px;">
<img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/>
<td style="padding-left: 0.5em;">
<div id="projectname">
 <span id="projectnumber">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('_network_quantizer_8cpp_source.xhtml','');});
</script>
<div id="doc-content">
<!-- window showing the filter options -->
<div id="MSearchSelectWindow"
onmouseover="return searchBox.OnSearchSelectShow()"
onmouseout="return searchBox.OnSearchSelectHide()"
onkeydown="return searchBox.OnSearchSelectKey(event)">
</div>
<!-- iframe showing the search results (closed by default) -->
<div id="MSearchResultsWindow">
<iframe src="javascript:void(0)" frameborder="0"
name="MSearchResults" id="MSearchResults">
</iframe>
</div>
<div class="header">
<div class="headertitle">
<div class="title">NetworkQuantizer.cpp</div> </div>
</div><!--header-->
<div class="contents">
<a href="_network_quantizer_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_network_quantizer_8hpp.xhtml">NetworkQuantizer.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_network_quantizer_utils_8hpp.xhtml">NetworkQuantizerUtils.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_graph_8hpp.xhtml">Graph.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_layer_8hpp.xhtml">Layer.hpp</a>"</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include "<a class="code" href="_network_8hpp.xhtml">Network.hpp</a>"</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include "<a class="code" href="_dynamic_quantization_strategy_8hpp.xhtml">DynamicQuantizationStrategy.hpp</a>"</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include "<a class="code" href="_static_range_strategy_8hpp.xhtml">StaticRangeStrategy.hpp</a>"</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include "<a class="code" href="_quantizer_strategy_8hpp.xhtml">QuantizerStrategy.hpp</a>"</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include "<a class="code" href="_override_input_range_visitor_8hpp.xhtml">OverrideInputRangeVisitor.hpp</a>"</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_tensor_i_o_utils_8hpp.xhtml">TensorIOUtils.hpp</a>></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <<a class="code" href="_i_layer_visitor_8hpp.xhtml">armnn/ILayerVisitor.hpp</a>></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include <<a class="code" href="_i_network_8hpp.xhtml">armnn/INetwork.hpp</a>></span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <<a class="code" href="_tensor_8hpp.xhtml">armnn/Tensor.hpp</a>></span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include <<a class="code" href="_types_8hpp.xhtml">armnn/Types.hpp</a>></span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#include <<a class="code" href="_tensor_utils_8hpp.xhtml">armnnUtils/TensorUtils.hpp</a>></span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include <<a class="code" href="_polymorphic_downcast_8hpp.xhtml">armnn/utility/PolymorphicDowncast.hpp</a>></span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include <mapbox/variant.hpp></span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include <cmath></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> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> {</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#acf933608643ce27b3c68e3431d047d0a"> 34</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#acf933608643ce27b3c68e3431d047d0a">TContainer</a> = mapbox::util::variant<std::vector<float>, std::vector<int>, std::vector<unsigned char>>;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network_quantizer.xhtml#ab8c40aedacd27ec921e53f3a022e6a63"> 36</a></span> <a class="code" href="classarmnn_1_1_i_network_quantizer.xhtml">INetworkQuantizer</a>* <a class="code" href="classarmnn_1_1_i_network_quantizer.xhtml#ab8c40aedacd27ec921e53f3a022e6a63">INetworkQuantizer::CreateRaw</a>(<a class="code" href="classarmnn_1_1_i_network.xhtml">INetwork</a>* inputNetwork, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_quantizer_options.xhtml">QuantizerOptions</a>& options)</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> <a class="code" href="classarmnn_1_1_network_quantizer.xhtml">NetworkQuantizer</a>(inputNetwork, options);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> }</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network_quantizer.xhtml#a3a4d01d9351c02a703740290f226441f"> 41</a></span> <a class="code" href="namespacearmnn.xhtml#a41119e261eec9343888d2ceab1e4999a">INetworkQuantizerPtr</a> <a class="code" href="classarmnn_1_1_i_network_quantizer.xhtml#a3a4d01d9351c02a703740290f226441f">INetworkQuantizer::Create</a>(<a class="code" href="classarmnn_1_1_i_network.xhtml">INetwork</a>* inputNetwork, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_quantizer_options.xhtml">QuantizerOptions</a>& options)</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> {</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a41119e261eec9343888d2ceab1e4999a">INetworkQuantizerPtr</a>(<a class="code" href="classarmnn_1_1_i_network_quantizer.xhtml#ab8c40aedacd27ec921e53f3a022e6a63">CreateRaw</a>(inputNetwork, options), &<a class="code" href="classarmnn_1_1_i_network_quantizer.xhtml#ad1ad5b83dc4d8bed64c29adf21c8958a">INetworkQuantizer::Destroy</a>);</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> </div><div class="line"><a name="l00046"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network_quantizer.xhtml#ad1ad5b83dc4d8bed64c29adf21c8958a"> 46</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_i_network_quantizer.xhtml#ad1ad5b83dc4d8bed64c29adf21c8958a">INetworkQuantizer::Destroy</a>(<a class="code" href="classarmnn_1_1_i_network_quantizer.xhtml">INetworkQuantizer</a> *quantizer)</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> {</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keyword">delete</span> PolymorphicDowncast<NetworkQuantizer*>(quantizer);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> }</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_quantizer.xhtml#a0de9803a30020e30ec8c9c0ba8592dc6"> 51</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_network_quantizer.xhtml#a0de9803a30020e30ec8c9c0ba8592dc6">NetworkQuantizer::OverrideInputRange</a>(<a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">LayerBindingId</a> layerId, <span class="keywordtype">float</span> min, <span class="keywordtype">float</span> max)</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = m_InputNetwork->pNetworkImpl->GetGraph();</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keyword">auto</span> inputLayers = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a919fb58873ef3a6549e4490e226f2eae">GetInputLayers</a>();</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">// Walk the input layers of the graph and override the quantization parameters of the one with the given id</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <a class="code" href="classarmnn_1_1_override_input_range_visitor.xhtml">OverrideInputRangeVisitor</a> overrideInputRangeVisitor(m_Ranges, layerId, <a class="code" href="classarmnn_1_1_range_tracker.xhtml#a997e96288bdb106c922202e3f33d5d7b">RangeTracker::MinMaxRange</a>{min, max});</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="namespacearmnn.xhtml#a9835ef753dda5b5a2fe827680e41fda7">VisitLayers</a>(inputLayers, overrideInputRangeVisitor);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> }</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_quantizer.xhtml#acff529f0d8ffed99123e3a729942be12"> 61</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_network_quantizer.xhtml#acff529f0d8ffed99123e3a729942be12">NetworkQuantizer::Refine</a>(<span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a>& inputTensors)</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> {</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// The first time Refine is called the m_Runtime and the DynamicQuantizationStrategy</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// will not have been created. Need to get the environment set up, Runtime loaded,</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="comment">// DynamicQuantizationStrategy created and run over the network to initialise itself</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="comment">// and the RangeTracker the Debug callback registered and an initial inference</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="comment">// done to set up the first min/max values</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordflow">if</span> (!m_Runtime)</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  {</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  m_RefineCount = 0;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  m_Ranges.SetDynamicMode(<span class="keyword">true</span>);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& cGraph = m_InputNetwork->pNetworkImpl->GetGraph().<a class="code" href="classarmnn_1_1_graph.xhtml#a9a7209345edfdb2b066b0ceb66414d7c">TopologicalSort</a>();</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="comment">// need to insert Debug layers in the DynamicQuantizationStrategy</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = <span class="keyword">const_cast<</span><a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>&<span class="keyword">></span>(cGraph);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="comment">// Initialize RangeTracker to the default values for each layer.</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="comment">// The default values are overwritten by the min/max that is</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="comment">// recorded during the first dataset min/max calibration. This</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="comment">// initialisation is only required for the first call of Refine().</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  m_DynamicQuantizationStrategy = <a class="code" href="classarmnn_1_1_dynamic_quantization_strategy.xhtml">DynamicQuantizationStrategy</a>(m_Ranges, graph);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="namespacearmnn.xhtml#a929027fc5caf6a6e20d3b9ac6fcd128b">ApplyStrategyToLayers</a>(cGraph, m_DynamicQuantizationStrategy.value());</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  m_Runtime = <a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(options);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="comment">// Optimize network - debug already enabled for layers that require quantization</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">OptimizerOptions</a> optimizerOptions(<span class="keyword">false</span>, <span class="keyword">false</span>);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  std::vector<BackendId> backends = {<span class="stringliteral">"CpuRef"</span>};</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optimizedNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*m_InputNetwork,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  backends,</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  m_Runtime->GetDeviceSpec(),</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  optimizerOptions);</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> </div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  m_Runtime->LoadNetwork(m_NetworkId, std::move(optimizedNet));</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="comment">// Debug callback function to refine min/max in RangeTracker</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keyword">auto</span> rangeTrackerCallback = [&](<a class="code" href="classarmnn_1_1profiling_1_1_profiling_guid.xhtml">LayerGuid</a> guid, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> slotIndex, <a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml">ITensorHandle</a> *tensorHandle) {</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="comment">// Get min/max pair from tensor data</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  std::pair<float, float> minMax = <a class="code" href="namespacearmnn_utils.xhtml#a1c9097ab13afc54b48c503c6487aaee1">armnnUtils::FindMinMax</a>(tensorHandle);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> </div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="comment">// For first calibration dataset, set min/max range in RangeTracker to</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="comment">// min/max ranges gathered during inference</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordflow">if</span> (m_RefineCount == 0)</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>  m_Ranges.ResetMinMax(guid, slotIndex, minMax.first, minMax.second);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  }</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  {</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// For every other calibration dataset, only set min/max range if the</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="comment">// values gathered are less than / greater than originally recorded.</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  m_Ranges.RefineMin(guid, slotIndex, minMax.first);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  m_Ranges.RefineMax(guid, slotIndex, minMax.second);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  }</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  };</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  m_Runtime->RegisterDebugCallback(m_NetworkId, rangeTrackerCallback);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  }</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="comment">// Create output tensor for EnqueueWorkload</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  std::vector<armnn::BindingPointInfo> outputBindings;</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keyword">auto</span> outputLayers = m_DynamicQuantizationStrategy.value().GetOutputLayers();</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  std::vector<TContainer> outputVectors;</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> outputLayerBindingId : outputLayers)</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  {</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keyword">auto</span> outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkId, outputLayerBindingId);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  outputBindings.push_back(std::make_pair(outputLayerBindingId, outputTensorInfo));</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  outputVectors.push_back(std::vector<float>(outputTensorInfo.GetNumElements(), 0));</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  }</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors = armnnUtils::MakeOutputTensors<TContainer>(outputBindings, outputVectors);</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">// Execute EnqueueWorkload with calibration image</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  m_Runtime->EnqueueWorkload(m_NetworkId, inputTensors, outputTensors);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  ++m_RefineCount;</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> </div><div class="line"><a name="l00137"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_quantizer.xhtml#a8768a9dd173e985bfc0c72338662d631"> 137</a></span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> <a class="code" href="classarmnn_1_1_network_quantizer.xhtml#a8768a9dd173e985bfc0c72338662d631">NetworkQuantizer::ExportNetwork</a>()</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> {</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = m_InputNetwork->pNetworkImpl->GetGraph().<a class="code" href="classarmnn_1_1_graph.xhtml#a9a7209345edfdb2b066b0ceb66414d7c">TopologicalSort</a>();</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="comment">// Step 1) Walk the graph and populate default min/max values for</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="comment">// intermediate tensors, only if Runtime does not exist (created</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// if Refine has been called)</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordflow">if</span> (!m_Runtime)</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  m_Ranges.SetDynamicMode(<span class="keyword">false</span>);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <a class="code" href="classarmnn_1_1_static_range_strategy.xhtml">StaticRangeStrategy</a> rangeStrategy(m_Ranges);</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <a class="code" href="namespacearmnn.xhtml#a929027fc5caf6a6e20d3b9ac6fcd128b">ApplyStrategyToLayers</a>(graph, rangeStrategy);</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>  <span class="keywordflow">else</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  {</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="comment">// Set min/max range of non-calibrated layers to parent layer's range</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  m_DynamicQuantizationStrategy.value().VisitNonCalibratedLayers();</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="comment">// now tear down the runtime and the dynamic visitor.</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  m_Runtime.reset(<span class="keyword">nullptr</span>);</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  m_DynamicQuantizationStrategy = <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>();</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  m_RefineCount = 0;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  }</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> </div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="comment">// Step 2) Convert input InputNetwork to Quantized InputNetwork</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  std::unique_ptr<IQuantizationScheme> quantizationScheme;</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keywordflow">switch</span> (m_Options.m_ActivationFormat)</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  {</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>:</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  quantizationScheme = std::make_unique<QAsymmU8QuantizationScheme>();</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">DataType::QAsymmS8</a>:</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  quantizationScheme = std::make_unique<QAsymmS8QuantizationScheme>();</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>:</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  quantizationScheme = std::make_unique<QSymmS8QuantizationScheme>();</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>:</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  quantizationScheme = std::make_unique<QSymm16QuantizationScheme>();</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">InvalidArgumentException</a>(<span class="stringliteral">"Unsupported quantization target"</span>);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  }</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="classarmnn_1_1_quantizer_strategy.xhtml">QuantizerStrategy</a> quantizerVisitor(m_Ranges, quantizationScheme.get(), m_Options.m_PreserveType);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <a class="code" href="namespacearmnn.xhtml#a929027fc5caf6a6e20d3b9ac6fcd128b">ApplyStrategyToLayers</a>(graph, quantizerVisitor);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="comment">// clear the ranges</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  m_Ranges.Reset();</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> </div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="keywordflow">return</span> quantizerVisitor.RetrieveFinalNetwork();</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</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">//namespace armn</span></div><div class="ttc" id="_tensor_i_o_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_i_o_utils_8hpp.xhtml">TensorIOUtils.hpp</a></div></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="_tensor_8hpp_xhtml"><div class="ttname"><a href="_tensor_8hpp.xhtml">Tensor.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_override_input_range_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_override_input_range_visitor.xhtml">armnn::OverrideInputRangeVisitor</a></div><div class="ttdoc">Visitor object for overriding the input range of the quantized input layers in a network. </div><div class="ttdef"><b>Definition:</b> <a href="_override_input_range_visitor_8hpp_source.xhtml#l00069">OverrideInputRangeVisitor.hpp:69</a></div></div>
<div class="ttc" id="classarmnn_1_1_static_range_strategy_xhtml"><div class="ttname"><a href="classarmnn_1_1_static_range_strategy.xhtml">armnn::StaticRangeStrategy</a></div><div class="ttdef"><b>Definition:</b> <a href="_static_range_strategy_8hpp_source.xhtml#l00018">StaticRangeStrategy.hpp:18</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_quantizer_xhtml"><div class="ttname"><a href="classarmnn_1_1_network_quantizer.xhtml">armnn::NetworkQuantizer</a></div><div class="ttdef"><b>Definition:</b> <a href="_network_quantizer_8hpp_source.xhtml#l00020">NetworkQuantizer.hpp:20</a></div></div>
<div class="ttc" id="classarmnn_1_1profiling_1_1_profiling_guid_xhtml"><div class="ttname"><a href="classarmnn_1_1profiling_1_1_profiling_guid.xhtml">armnn::profiling::ProfilingGuid</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00291">Types.hpp:291</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a41119e261eec9343888d2ceab1e4999a"><div class="ttname"><a href="namespacearmnn.xhtml#a41119e261eec9343888d2ceab1e4999a">armnn::INetworkQuantizerPtr</a></div><div class="ttdeci">std::unique_ptr< class INetworkQuantizer, void(*)(INetworkQuantizer *quantizer)> INetworkQuantizerPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_quantizer_8hpp_source.xhtml#l00029">INetworkQuantizer.hpp:29</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml">armnn::INetwork</a></div><div class="ttdoc">Main network class which provides the interface for building up a neural network. ...</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00178">INetwork.hpp:178</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</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_ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantizer_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_quantizer_options.xhtml">armnn::QuantizerOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_network_quantizer_8hpp_source.xhtml#l00015">INetworkQuantizer.hpp:15</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="namespacearmnn_xhtml_a9835ef753dda5b5a2fe827680e41fda7"><div class="ttname"><a href="namespacearmnn.xhtml#a9835ef753dda5b5a2fe827680e41fda7">armnn::VisitLayers</a></div><div class="ttdeci">void VisitLayers(const LayerContainer &layerContainer, ILayerVisitor &visitor)</div><div class="ttdef"><b>Definition:</b> <a href="_network_quantizer_utils_8hpp_source.xhtml#l00050">NetworkQuantizerUtils.hpp:50</a></div></div>
<div class="ttc" id="_network_quantizer_8hpp_xhtml"><div class="ttname"><a href="_network_quantizer_8hpp.xhtml">NetworkQuantizer.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_range_tracker_xhtml_a997e96288bdb106c922202e3f33d5d7b"><div class="ttname"><a href="classarmnn_1_1_range_tracker.xhtml#a997e96288bdb106c922202e3f33d5d7b">armnn::RangeTracker::MinMaxRange</a></div><div class="ttdeci">std::pair< float, float > MinMaxRange</div><div class="ttdef"><b>Definition:</b> <a href="_range_tracker_8hpp_source.xhtml#l00020">RangeTracker.hpp:20</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a></div><div class="ttdeci">int LayerBindingId</div><div class="ttdoc">Type of identifiers for bindable layers (inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00210">Types.hpp:210</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_acf933608643ce27b3c68e3431d047d0a"><div class="ttname"><a href="namespacearmnn.xhtml#acf933608643ce27b3c68e3431d047d0a">armnn::TContainer</a></div><div class="ttdeci">mapbox::util::variant< std::vector< float >, std::vector< int >, std::vector< unsigned char > > TContainer</div><div class="ttdef"><b>Definition:</b> <a href="_network_quantizer_8cpp_source.xhtml#l00034">NetworkQuantizer.cpp:34</a></div></div>
<div class="ttc" id="classarmnn_1_1_quantizer_strategy_xhtml"><div class="ttname"><a href="classarmnn_1_1_quantizer_strategy.xhtml">armnn::QuantizerStrategy</a></div><div class="ttdef"><b>Definition:</b> <a href="_quantizer_strategy_8hpp_source.xhtml#l00015">QuantizerStrategy.hpp:15</a></div></div>
<div class="ttc" id="_polymorphic_downcast_8hpp_xhtml"><div class="ttname"><a href="_polymorphic_downcast_8hpp.xhtml">PolymorphicDowncast.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_quantizer_xhtml_ad1ad5b83dc4d8bed64c29adf21c8958a"><div class="ttname"><a href="classarmnn_1_1_i_network_quantizer.xhtml#ad1ad5b83dc4d8bed64c29adf21c8958a">armnn::INetworkQuantizer::Destroy</a></div><div class="ttdeci">static void Destroy(INetworkQuantizer *quantizer)</div><div class="ttdoc">Destroy Quantizer object. </div><div class="ttdef"><b>Definition:</b> <a href="_network_quantizer_8cpp_source.xhtml#l00046">NetworkQuantizer.cpp:46</a></div></div>
<div class="ttc" id="_override_input_range_visitor_8hpp_xhtml"><div class="ttname"><a href="_override_input_range_visitor_8hpp.xhtml">OverrideInputRangeVisitor.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_quantizer_xhtml_acff529f0d8ffed99123e3a729942be12"><div class="ttname"><a href="classarmnn_1_1_network_quantizer.xhtml#acff529f0d8ffed99123e3a729942be12">armnn::NetworkQuantizer::Refine</a></div><div class="ttdeci">void Refine(const InputTensors &inputTensors) override</div><div class="ttdoc">Refine input network with a set of refinement data for specified LayerBindingId. </div><div class="ttdef"><b>Definition:</b> <a href="_network_quantizer_8cpp_source.xhtml#l00061">NetworkQuantizer.cpp:61</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_quantizer_xhtml_a0de9803a30020e30ec8c9c0ba8592dc6"><div class="ttname"><a href="classarmnn_1_1_network_quantizer.xhtml#a0de9803a30020e30ec8c9c0ba8592dc6">armnn::NetworkQuantizer::OverrideInputRange</a></div><div class="ttdeci">void OverrideInputRange(LayerBindingId layerId, float min, float max) override</div><div class="ttdoc">Overrides the default quantization values for the input layer with the given id. </div><div class="ttdef"><b>Definition:</b> <a href="_network_quantizer_8cpp_source.xhtml#l00051">NetworkQuantizer.cpp:51</a></div></div>
<div class="ttc" id="_quantizer_strategy_8hpp_xhtml"><div class="ttname"><a href="_quantizer_strategy_8hpp.xhtml">QuantizerStrategy.hpp</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="namespacearmnn_xhtml_a929027fc5caf6a6e20d3b9ac6fcd128b"><div class="ttname"><a href="namespacearmnn.xhtml#a929027fc5caf6a6e20d3b9ac6fcd128b">armnn::ApplyStrategyToLayers</a></div><div class="ttdeci">void ApplyStrategyToLayers(const LayerContainer &layerContainer, IStrategy &strategy)</div><div class="ttdef"><b>Definition:</b> <a href="_network_quantizer_utils_8hpp_source.xhtml#l00061">NetworkQuantizerUtils.hpp:61</a></div></div>
<div class="ttc" id="_i_layer_visitor_8hpp_xhtml"><div class="ttname"><a href="_i_layer_visitor_8hpp.xhtml">ILayerVisitor.hpp</a></div></div>
<div class="ttc" id="_graph_8hpp_xhtml"><div class="ttname"><a href="_graph_8hpp.xhtml">Graph.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.xhtml">armnn::ITensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_8hpp_source.xhtml#l00015">ITensorHandle.hpp:15</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
<div class="ttc" id="_types_8hpp_xhtml"><div class="ttname"><a href="_types_8hpp.xhtml">Types.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_quantizer_xhtml_ab8c40aedacd27ec921e53f3a022e6a63"><div class="ttname"><a href="classarmnn_1_1_i_network_quantizer.xhtml#ab8c40aedacd27ec921e53f3a022e6a63">armnn::INetworkQuantizer::CreateRaw</a></div><div class="ttdeci">static INetworkQuantizer * CreateRaw(INetwork *inputNetwork, const QuantizerOptions &options=QuantizerOptions())</div><div class="ttdoc">Create Quantizer object and return raw pointer. </div><div class="ttdef"><b>Definition:</b> <a href="_network_quantizer_8cpp_source.xhtml#l00036">NetworkQuantizer.cpp:36</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00341">Tensor.hpp:341</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_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="namespacearmnn_utils_xhtml_a1c9097ab13afc54b48c503c6487aaee1"><div class="ttname"><a href="namespacearmnn_utils.xhtml#a1c9097ab13afc54b48c503c6487aaee1">armnnUtils::FindMinMax</a></div><div class="ttdeci">std::pair< float, float > FindMinMax(armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_utils_8cpp_source.xhtml#l00058">TensorUtils.cpp:58</a></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_invalid_argument_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00080">Exceptions.hpp:80</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="_i_network_8hpp_xhtml"><div class="ttname"><a href="_i_network_8hpp.xhtml">INetwork.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00043">IRuntime.hpp:43</a></div></div>
<div class="ttc" id="_layer_8hpp_xhtml"><div class="ttname"><a href="_layer_8hpp.xhtml">Layer.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_empty_optional_xhtml"><div class="ttname"><a href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a></div><div class="ttdoc">EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00032">Optional.hpp:32</a></div></div>
<div class="ttc" id="_static_range_strategy_8hpp_xhtml"><div class="ttname"><a href="_static_range_strategy_8hpp.xhtml">StaticRangeStrategy.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_dynamic_quantization_strategy_xhtml"><div class="ttname"><a href="classarmnn_1_1_dynamic_quantization_strategy.xhtml">armnn::DynamicQuantizationStrategy</a></div><div class="ttdoc">Visitor class implementation to gather the TensorInfo for LayerBindingID for creation of ConstTensor ...</div><div class="ttdef"><b>Definition:</b> <a href="_dynamic_quantization_strategy_8hpp_source.xhtml#l00019">DynamicQuantizationStrategy.hpp:19</a></div></div>
<div class="ttc" id="_tensor_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_utils_8hpp.xhtml">TensorUtils.hpp</a></div></div>
<div class="ttc" id="_network_8hpp_xhtml"><div class="ttname"><a href="_network_8hpp.xhtml">Network.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div></div>
<div class="ttc" id="_dynamic_quantization_strategy_8hpp_xhtml"><div class="ttname"><a href="_dynamic_quantization_strategy_8hpp.xhtml">DynamicQuantizationStrategy.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml_a9a7209345edfdb2b066b0ceb66414d7c"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a9a7209345edfdb2b066b0ceb66414d7c">armnn::Graph::TopologicalSort</a></div><div class="ttdeci">Graph & TopologicalSort()</div><div class="ttdoc">Sorts layers in topological order and return this. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00177">Graph.hpp:177</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml_a919fb58873ef3a6549e4490e226f2eae"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a919fb58873ef3a6549e4490e226f2eae">armnn::Graph::GetInputLayers</a></div><div class="ttdeci">InputLayersAccessor GetInputLayers() const</div><div class="ttdoc">Returns a wrapper object with begin(), end() methods to iterate over the input layers in a range-base...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00185">Graph.hpp:185</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_quantizer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_network_quantizer.xhtml">armnn::INetworkQuantizer</a></div><div class="ttdoc">Quantizer class Quantizes a float32 InputNetwork. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_quantizer_8hpp_source.xhtml#l00032">INetworkQuantizer.hpp:32</a></div></div>
<div class="ttc" id="_network_quantizer_utils_8hpp_xhtml"><div class="ttname"><a href="_network_quantizer_utils_8hpp.xhtml">NetworkQuantizerUtils.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_quantizer_xhtml_a8768a9dd173e985bfc0c72338662d631"><div class="ttname"><a href="classarmnn_1_1_network_quantizer.xhtml#a8768a9dd173e985bfc0c72338662d631">armnn::NetworkQuantizer::ExportNetwork</a></div><div class="ttdeci">INetworkPtr ExportNetwork() override</div><div class="ttdoc">Extract final quantized network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_quantizer_8cpp_source.xhtml#l00137">NetworkQuantizer.cpp:137</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_quantizer_xhtml_a3a4d01d9351c02a703740290f226441f"><div class="ttname"><a href="classarmnn_1_1_i_network_quantizer.xhtml#a3a4d01d9351c02a703740290f226441f">armnn::INetworkQuantizer::Create</a></div><div class="ttdeci">static INetworkQuantizerPtr Create(INetwork *inputNetwork, const QuantizerOptions &options=QuantizerOptions())</div><div class="ttdoc">Create Quantizer object wrapped in unique_ptr. </div><div class="ttdef"><b>Definition:</b> <a href="_network_quantizer_8cpp_source.xhtml#l00041">NetworkQuantizer.cpp:41</a></div></div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<!-- start footer part -->
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
<ul>
<li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_e0a84d05c80a2ef4231141dcbbeac5c8.xhtml">armnn</a></li><li class="navelem"><a class="el" href="_network_quantizer_8cpp.xhtml">NetworkQuantizer.cpp</a></li>
<li class="footer">Generated on Fri Mar 19 2021 15:25:36 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>
|
