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diff --git a/20.02/_network_quantizer_8cpp_source.xhtml b/20.02/_network_quantizer_8cpp_source.xhtml new file mode 100644 index 0000000000..115cc34122 --- /dev/null +++ b/20.02/_network_quantizer_8cpp_source.xhtml @@ -0,0 +1,169 @@ +<!-- 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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">20.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_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_visitor_8hpp.xhtml">DynamicQuantizationVisitor.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_visitor_8hpp.xhtml">StaticRangeVisitor.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_visitor_8hpp.xhtml">QuantizerVisitor.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> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include <boost/variant.hpp></span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include <cmath></span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> {</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a9eb69ebdaf4ceb8014e7c8a540266100"> 33</a></span> <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#a9eb69ebdaf4ceb8014e7c8a540266100">TContainer</a> = boost::variant<std::vector<float>, std::vector<int>, std::vector<unsigned char>>;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network_quantizer.xhtml#ab8c40aedacd27ec921e53f3a022e6a63"> 35</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>& <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a6560146509197f3e197d8d36f76c1347">options</a>)</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="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="l00038"></a><span class="lineno"> 38</span> }</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network_quantizer.xhtml#a3a4d01d9351c02a703740290f226441f"> 40</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>& <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a6560146509197f3e197d8d36f76c1347">options</a>)</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</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="l00043"></a><span class="lineno"> 43</span> }</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="classarmnn_1_1_i_network_quantizer.xhtml#ad1ad5b83dc4d8bed64c29adf21c8958a"> 45</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="l00046"></a><span class="lineno"> 46</span> {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keyword">delete</span> boost::polymorphic_downcast<NetworkQuantizer*>(quantizer);</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> </div><div class="line"><a name="l00050"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_quantizer.xhtml#a0de9803a30020e30ec8c9c0ba8592dc6"> 50</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="l00051"></a><span class="lineno"> 51</span> {</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = boost::polymorphic_downcast<const Network*>(m_InputNetwork)->GetGraph();</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</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="l00054"></a><span class="lineno"> 54</span> </div><div class="line"><a name="l00055"></a><span class="lineno"> 55</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="l00056"></a><span class="lineno"> 56</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="l00057"></a><span class="lineno"> 57</span>  <a class="code" href="namespacearmnn.xhtml#a9835ef753dda5b5a2fe827680e41fda7">VisitLayers</a>(inputLayers, overrideInputRangeVisitor);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> }</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_quantizer.xhtml#acff529f0d8ffed99123e3a729942be12"> 60</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="l00061"></a><span class="lineno"> 61</span> {</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// The first time Refine is called the m_Runtime and the DynamicQuantizationVisitor</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</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="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// DynamicQuantizationVisitor created and run over the network to initialise itself</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="comment">// and the RangeTracker the Debug callback registered and an initial inference</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="comment">// done to set up the first min/max values</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">if</span> (!m_Runtime)</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  m_RefineCount = 0;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  m_Ranges.SetDynamicMode(<span class="keyword">true</span>);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& cGraph = boost::polymorphic_downcast<const Network*>(m_InputNetwork)->GetGraph().<a class="code" href="classarmnn_1_1_graph.xhtml#a9a7209345edfdb2b066b0ceb66414d7c">TopologicalSort</a>();</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// need to insert Debug layers in the DynamicQuantizationVisitor</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</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="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="comment">// Initialize RangeTracker to the default values for each layer.</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="comment">// The default values are overwritten by the min/max that is</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="comment">// recorded during the first dataset min/max calibration. This</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="comment">// initialisation is only required for the first call of Refine().</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  m_DynamicQuantizationVisitor = <a class="code" href="classarmnn_1_1_dynamic_quantization_visitor.xhtml">DynamicQuantizationVisitor</a>(m_Ranges, graph);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="namespacearmnn.xhtml#a9835ef753dda5b5a2fe827680e41fda7">VisitLayers</a>(cGraph, m_DynamicQuantizationVisitor.value());</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>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a> <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a6560146509197f3e197d8d36f76c1347">options</a>;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  m_Runtime = <a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(options);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="comment">// Optimize network - debug already enabled for layers that require quantization</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</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="l00088"></a><span class="lineno"> 88</span>  std::vector<BackendId> backends = {<span class="stringliteral">"CpuRef"</span>};</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</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="l00090"></a><span class="lineno"> 90</span>  backends,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  m_Runtime->GetDeviceSpec(),</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  optimizerOptions);</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>  m_Runtime->LoadNetwork(m_NetworkId, std::move(optimizedNet));</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>  <span class="comment">// Debug callback function to refine min/max in RangeTracker</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</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="l00098"></a><span class="lineno"> 98</span>  <span class="comment">// Get min/max pair from tensor data</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  std::pair<float, float> minMax = <a class="code" href="namespacearmnn_utils.xhtml#a1c9097ab13afc54b48c503c6487aaee1">armnnUtils::FindMinMax</a>(tensorHandle);</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>  <span class="comment">// For first calibration dataset, set min/max range in RangeTracker to</span></div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="comment">// min/max ranges gathered during inference</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordflow">if</span> (m_RefineCount == 0)</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>  m_Ranges.ResetMinMax(guid, slotIndex, minMax.first, minMax.second);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  }</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  {</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="comment">// For every other calibration dataset, only set min/max range if the</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// values gathered are less than / greater than originally recorded.</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  m_Ranges.RefineMin(guid, slotIndex, minMax.first);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  m_Ranges.RefineMax(guid, slotIndex, minMax.second);</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>  };</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>  m_Runtime->RegisterDebugCallback(m_NetworkId, rangeTrackerCallback);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  }</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="comment">// Create output tensor for EnqueueWorkload</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  std::vector<armnn::BindingPointInfo> outputBindings;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keyword">auto</span> outputLayers = m_DynamicQuantizationVisitor.value().GetOutputLayers();</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  std::vector<TContainer> outputVectors;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span> outputLayerBindingId : outputLayers)</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  {</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keyword">auto</span> outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkId, outputLayerBindingId);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  outputBindings.push_back(std::make_pair(outputLayerBindingId, outputTensorInfo));</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  outputVectors.push_back(std::vector<float>(outputTensorInfo.GetNumElements(), 0));</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  }</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors = armnnUtils::MakeOutputTensors<TContainer>(outputBindings, outputVectors);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="comment">// Execute EnqueueWorkload with calibration image</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  m_Runtime->EnqueueWorkload(m_NetworkId, inputTensors, outputTensors);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  ++m_RefineCount;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> }</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div><div class="line"><a name="l00136"></a><span class="lineno"><a class="line" href="classarmnn_1_1_network_quantizer.xhtml#a8768a9dd173e985bfc0c72338662d631"> 136</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="l00137"></a><span class="lineno"> 137</span> {</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph = boost::polymorphic_downcast<const Network*>(m_InputNetwork)->GetGraph().<a class="code" href="classarmnn_1_1_graph.xhtml#a9a7209345edfdb2b066b0ceb66414d7c">TopologicalSort</a>();</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="comment">// Step 1) Walk the graph and populate default min/max values for</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="comment">// intermediate tensors, only if Runtime does not exist (created</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="comment">// if Refine has been called)</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keywordflow">if</span> (!m_Runtime)</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  {</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  m_Ranges.SetDynamicMode(<span class="keyword">false</span>);</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <a class="code" href="classarmnn_1_1_static_range_visitor.xhtml">StaticRangeVisitor</a> rangeVisitor(m_Ranges);</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <a class="code" href="namespacearmnn.xhtml#a9835ef753dda5b5a2fe827680e41fda7">VisitLayers</a>(graph, rangeVisitor);</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  }</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  {</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="comment">// Set min/max range of non-calibrated layers to parent layer's range</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  m_DynamicQuantizationVisitor.value().VisitNonCalibratedLayers();</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="comment">// now tear down the runtime and the dynamic visitor.</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  m_Runtime.reset(<span class="keyword">nullptr</span>);</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  m_DynamicQuantizationVisitor = <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>();</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  m_RefineCount = 0;</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  }</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> </div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">// Step 2) Convert input InputNetwork to Quantized InputNetwork</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  std::unique_ptr<IQuantizationScheme> quantizationScheme;</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="keywordflow">switch</span> (m_Options.m_ActivationFormat)</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>:</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  quantizationScheme = std::make_unique<QAsymmU8QuantizationScheme>();</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">DataType::QAsymmS8</a>:</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  quantizationScheme = std::make_unique<QAsymmS8QuantizationScheme>();</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>:</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  quantizationScheme = std::make_unique<QSymmS8QuantizationScheme>();</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>:</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  quantizationScheme = std::make_unique<QSymm16QuantizationScheme>();</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</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="l00177"></a><span class="lineno"> 177</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>  <a class="code" href="classarmnn_1_1_quantizer_visitor.xhtml">QuantizerVisitor</a> quantizerVisitor(m_Ranges, quantizationScheme.get(), m_Options.m_PreserveType);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="namespacearmnn.xhtml#a9835ef753dda5b5a2fe827680e41fda7">VisitLayers</a>(graph, quantizerVisitor);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> </div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="comment">// clear the ranges</span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  m_Ranges.Reset();</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keywordflow">return</span> quantizerVisitor.RetrieveFinalNetwork();</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> }</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"> 188</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#l00032">Runtime.cpp:32</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#l00018">OverrideInputRangeVisitor.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#l00252">Types.hpp:252</a></div></div> +<div class="ttc" id="_quantizer_visitor_8hpp_xhtml"><div class="ttname"><a href="_quantizer_visitor_8hpp.xhtml">QuantizerVisitor.hpp</a></div></div> +<div class="ttc" id="_static_range_visitor_8hpp_xhtml"><div class="ttname"><a href="_static_range_visitor_8hpp.xhtml">StaticRangeVisitor.hpp</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#l00105">INetwork.hpp:105</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#l00225">Tensor.hpp:225</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) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</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#l00171">Types.hpp:171</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#l00045">NetworkQuantizer.cpp:45</a></div></div> +<div class="ttc" id="classarmnn_1_1_static_range_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_static_range_visitor.xhtml">armnn::StaticRangeVisitor</a></div><div class="ttdoc">Visitor class to establish min/max ranges based on the type of the layer. </div><div class="ttdef"><b>Definition:</b> <a href="_static_range_visitor_8hpp_source.xhtml#l00019">StaticRangeVisitor.hpp:19</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#l00060">NetworkQuantizer.cpp:60</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#l00050">NetworkQuantizer.cpp:50</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#l00890">Network.cpp:890</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#l00035">NetworkQuantizer.cpp:35</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#l00226">Tensor.hpp:226</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#l00566">INetwork.hpp:566</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="classarmnn_1_1_quantizer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_quantizer_visitor.xhtml">armnn::QuantizerVisitor</a></div><div class="ttdoc">Visitor object for quantizing layers in a network. </div><div class="ttdef"><b>Definition:</b> <a href="_quantizer_visitor_8hpp_source.xhtml#l00025">QuantizerVisitor.hpp:25</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#l00582">INetwork.hpp:582</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#l00041">IRuntime.hpp:41</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a9eb69ebdaf4ceb8014e7c8a540266100"><div class="ttname"><a href="namespacearmnn.xhtml#a9eb69ebdaf4ceb8014e7c8a540266100">armnn::TContainer</a></div><div class="ttdeci">boost::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#l00033">NetworkQuantizer.cpp:33</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="_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="classarmnn_1_1_dynamic_quantization_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_dynamic_quantization_visitor.xhtml">armnn::DynamicQuantizationVisitor</a></div><div class="ttdoc">Visitor class to establish min/max ranges based on the type of the layer. </div><div class="ttdef"><b>Definition:</b> <a href="_dynamic_quantization_visitor_8hpp_source.xhtml#l00019">DynamicQuantizationVisitor.hpp:19</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#l00173">Graph.hpp:173</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#l00181">Graph.hpp:181</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#l00101">INetwork.hpp:101</a></div></div> +<div class="ttc" id="_dynamic_quantization_visitor_8hpp_xhtml"><div class="ttname"><a href="_dynamic_quantization_visitor_8hpp.xhtml">DynamicQuantizationVisitor.hpp</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="_file_only_profiling_decorator_tests_8cpp_xhtml_a6560146509197f3e197d8d36f76c1347"><div class="ttname"><a href="_file_only_profiling_decorator_tests_8cpp.xhtml#a6560146509197f3e197d8d36f76c1347">options</a></div><div class="ttdeci">armnn::Runtime::CreationOptions::ExternalProfilingOptions options</div><div class="ttdef"><b>Definition:</b> <a href="_file_only_profiling_decorator_tests_8cpp_source.xhtml#l00045">FileOnlyProfilingDecoratorTests.cpp:45</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#l00136">NetworkQuantizer.cpp:136</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#l00040">NetworkQuantizer.cpp:40</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 13 2020 16:09:08 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> |