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author | James Ward <james.ward@arm.com> | 2020-11-26 11:08:12 +0000 |
---|---|---|
committer | Colm Donelan <colm.donelan@arm.com> | 2020-11-26 14:39:49 +0000 |
commit | fb14ebbd68e04876809145296af96f6f41857418 (patch) | |
tree | 7eacc90dd6c79f3a6eae6e3c7b04d3a04161c794 /20.11/_cl_optimized_network_tests_8cpp_source.xhtml | |
parent | 4840dfb7543d66652dc11c5ff39c8f5c1e2f9370 (diff) | |
download | armnn-fb14ebbd68e04876809145296af96f6f41857418.tar.gz |
IVGCVSW-5348 Update Doxygen Docu
* Update Doxygen Documentation for 20.11 release
Signed-off-by: James Ward <james.ward@arm.com>
Change-Id: Ib47edac7923a642a277b1169d1085e5622021dc0
Diffstat (limited to '20.11/_cl_optimized_network_tests_8cpp_source.xhtml')
-rw-r--r-- | 20.11/_cl_optimized_network_tests_8cpp_source.xhtml | 153 |
1 files changed, 153 insertions, 0 deletions
diff --git a/20.11/_cl_optimized_network_tests_8cpp_source.xhtml b/20.11/_cl_optimized_network_tests_8cpp_source.xhtml new file mode 100644 index 0000000000..3ef0e23165 --- /dev/null +++ b/20.11/_cl_optimized_network_tests_8cpp_source.xhtml @@ -0,0 +1,153 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/backends/cl/test/ClOptimizedNetworkTests.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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">20.11</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_cl_optimized_network_tests_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">ClOptimizedNetworkTests.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_cl_optimized_network_tests_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="_cl_workload_factory_helper_8hpp.xhtml">ClWorkloadFactoryHelper.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_network_8hpp.xhtml">Network.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_graph_utils_8hpp.xhtml">test/GraphUtils.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_cl_workload_factory_8hpp.xhtml">cl/ClWorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <boost/test/unit_test.hpp></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> <a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(ClOptimizedNetwork)</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"><a class="line" href="_cl_optimized_network_tests_8cpp.xhtml#a7b202b7840e9275a418d40a7d0f5e3b1"> 18</a></span> <a class="code" href="_cl_optimized_network_tests_8cpp.xhtml#a7b202b7840e9275a418d40a7d0f5e3b1">BOOST_AUTO_TEST_CASE</a>(OptimizeValidateGpuDeviceSupportLayerNoFallback)</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> {</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="comment">// build up the structure of the network</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>());</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>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* input = net->AddInputLayer(0);</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* output = net->AddOutputLayer(0);</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>  input-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  input-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({ 1, 1, 4, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</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>  std::vector<armnn::BackendId> backends = { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a> };</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(*net, backends, runtime->GetDeviceSpec());</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  BOOST_CHECK(optNet);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="comment">// validate workloads</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <a class="code" href="classarmnn_1_1_cl_workload_factory.xhtml">armnn::ClWorkloadFactory</a> fact =</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  ClWorkloadFactoryHelper::GetFactory(ClWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : static_cast<armnn::OptimizedNetwork*>(optNet.get())->GetGraph())</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>  BOOST_CHECK(layer->GetBackendId() == <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a>);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  BOOST_CHECK_NO_THROW(</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  layer->CreateWorkload(fact));</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  }</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> }</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"><a class="line" href="_cl_optimized_network_tests_8cpp.xhtml#a04ac30f1bc321aad1c1ec487bc520e10"> 46</a></span> <a class="code" href="_cl_optimized_network_tests_8cpp.xhtml#a7b202b7840e9275a418d40a7d0f5e3b1">BOOST_AUTO_TEST_CASE</a>(FP16TurboModeTestOnGpuAcc)</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="comment">// Test to check when Fp16 Turbo mode set</span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="comment">// it converts the Fp32 network to Fp16 Network</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="comment">// add Fp32ToFp16 conversion layer after the InputLayer</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="comment">// add Fp16ToFp32 conversion layer after the OutputLayer</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="comment">// checks the other layers if they are supported in Fp16</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="comment">// if they are not put the conversion layers before and after</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="comment">// if they are not supported in Fp16 use Fp32 instead</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="comment">// if there are inverse conversion layers remove them with optimization</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">// at the moment FloorLayer is not supported in Fp16 so it rolls back to Fp32</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// and inverse conversion layers are removed by the optimizer</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="classarmnn_1_1_network.xhtml">armnn::Network</a> net;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="comment">// Defines layers.</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">auto</span> input = net.<a class="code" href="classarmnn_1_1_network.xhtml#a90d8841cfbbc82ab02328f33fed24ac6">AddInputLayer</a>(0, <span class="stringliteral">"input layer"</span>);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// ReLu1</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a> activation1Descriptor;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  activation1Descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a>;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  activation1Descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a017b2990003a014234f13e999dc7c689">m_A</a> = 1.f;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  activation1Descriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a28c4c9cb15f6be3499abbc46b356060b">m_B</a> = -1.f;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">auto</span> activation = net.<a class="code" href="classarmnn_1_1_network.xhtml#a36a40a1209689f39a5a283209991da3c">AddActivationLayer</a>(activation1Descriptor, <span class="stringliteral">"activation layer"</span>);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keyword">auto</span> output = net.<a class="code" href="classarmnn_1_1_network.xhtml#ad55ff20f4c7e60c18b849e61f28f0e2e">AddOutputLayer</a>(0, <span class="stringliteral">"output layer"</span>);</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>  <span class="comment">// Connects layers.</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  input-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(activation->GetInputSlot(0));</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  activation->GetOutputSlot(0).Connect(output->GetInputSlot(0));</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>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> shape({4});</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> info(shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  input->GetOutputSlot(0).SetTensorInfo(info);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  activation->GetOutputSlot(0).SetTensorInfo(info);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  std::vector<armnn::BackendId> backends = {<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a>};</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_optimizer_options.xhtml">armnn::OptimizerOptions</a> optimizerOptions;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  optimizerOptions.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a6e1a42622ca43dafc7ba8e684c016eb4">m_ReduceFp32ToFp16</a> = <span class="keyword">true</span>;</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>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optimizedNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  net, backends, runtime->GetDeviceSpec(), optimizerOptions);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a>& graph = <span class="keyword">static_cast<</span><a class="code" href="classarmnn_1_1_optimized_network.xhtml">armnn::OptimizedNetwork</a>*<span class="keyword">></span>(optimizedNet.get())->GetGraph();</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="comment">// Tests that all layers are present in the graph.</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  BOOST_TEST(graph.GetNumLayers() == 5);</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> </div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="comment">// Tests that the vertices exist and have correct names.</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#ac73a43305233b7e5f70debdb2d14a8d3">GraphHasNamedLayer</a>(graph, <span class="stringliteral">"input layer"</span>));</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#ac73a43305233b7e5f70debdb2d14a8d3">GraphHasNamedLayer</a>(graph, <span class="stringliteral">"convert_fp32_to_fp16-0-input layer"</span>));</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#ac73a43305233b7e5f70debdb2d14a8d3">GraphHasNamedLayer</a>(graph, <span class="stringliteral">"activation layer"</span>));</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#ac73a43305233b7e5f70debdb2d14a8d3">GraphHasNamedLayer</a>(graph, <span class="stringliteral">"convert_fp16_to_fp32-0-output layer"</span>));</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  BOOST_TEST(<a class="code" href="_graph_utils_8cpp.xhtml#ac73a43305233b7e5f70debdb2d14a8d3">GraphHasNamedLayer</a>(graph, <span class="stringliteral">"output layer"</span>));</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> </div><div class="line"><a name="l00103"></a><span class="lineno"><a class="line" href="_cl_optimized_network_tests_8cpp.xhtml#ad2472388efc119bcd4790a7e24bf3b5e"> 103</a></span> <a class="code" href="_cl_optimized_network_tests_8cpp.xhtml#a7b202b7840e9275a418d40a7d0f5e3b1">BOOST_AUTO_TEST_CASE</a>(FastMathEnabledTestOnGpuAcc)</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>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>());</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>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* input = net->AddInputLayer(0);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* output = net->AddOutputLayer(0);</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>  input-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  input-><a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({ 1, 1, 4, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a> options;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</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>  std::vector<armnn::BackendId> backends = {<a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a>};</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="structarmnn_1_1_optimizer_options.xhtml">armnn::OptimizerOptions</a> optimizerOptions;</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="structarmnn_1_1_backend_options.xhtml">armnn::BackendOptions</a> modelOptions(<span class="stringliteral">"GpuAcc"</span>, {{<span class="stringliteral">"FastMathEnabled"</span>, <span class="keyword">true</span>}});</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  optimizerOptions.<a class="code" href="structarmnn_1_1_optimizer_options.xhtml#a71194277c60153a5f86539f5d39f01db">m_ModelOptions</a>.push_back(modelOptions);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optimizedNet = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  *net, backends, runtime->GetDeviceSpec(), optimizerOptions);</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  BOOST_CHECK(optimizedNet);</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> modelOptionsOut = <span class="keyword">static_cast<</span><a class="code" href="classarmnn_1_1_optimized_network.xhtml">armnn::OptimizedNetwork</a>*<span class="keyword">></span>(optimizedNet.get())->GetModelOptions();</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  BOOST_TEST(modelOptionsOut.size() == 1);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  BOOST_TEST(modelOptionsOut[0].GetOption(0).GetName() == <span class="stringliteral">"FastMathEnabled"</span>);</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  BOOST_TEST(modelOptionsOut[0].GetOption(0).GetValue().AsBool() == <span class="keyword">true</span>);</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> </div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <a class="code" href="_cl_optimized_network_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>();</div><div class="ttc" id="_output_shape_of_squeeze_8cpp_xhtml_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div> +<div class="ttc" id="classarmnn_1_1_cl_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_cl_workload_factory.xhtml">armnn::ClWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_cl_workload_factory_8hpp_source.xhtml#l00019">ClWorkloadFactory.hpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml_a71194277c60153a5f86539f5d39f01db"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a71194277c60153a5f86539f5d39f01db">armnn::OptimizerOptions::m_ModelOptions</a></div><div class="ttdeci">ModelOptions m_ModelOptions</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00674">INetwork.hpp:674</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="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00061">INetwork.hpp:61</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_ad55ff20f4c7e60c18b849e61f28f0e2e"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#ad55ff20f4c7e60c18b849e61f28f0e2e">armnn::Network::AddOutputLayer</a></div><div class="ttdeci">IConnectableLayer * AddOutputLayer(LayerBindingId id, const char *name=nullptr) override</div><div class="ttdoc">Adds an output layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01467">Network.cpp:1467</a></div></div> +<div class="ttc" id="_cl_workload_factory_helper_8hpp_xhtml"><div class="ttname"><a href="_cl_workload_factory_helper_8hpp.xhtml">ClWorkloadFactoryHelper.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr< IRuntime, void(*)(IRuntime *runtime)> IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00025">IRuntime.hpp:25</a></div></div> +<div class="ttc" id="_graph_utils_8cpp_xhtml_ac73a43305233b7e5f70debdb2d14a8d3"><div class="ttname"><a href="_graph_utils_8cpp.xhtml#ac73a43305233b7e5f70debdb2d14a8d3">GraphHasNamedLayer</a></div><div class="ttdeci">bool GraphHasNamedLayer(const armnn::Graph &graph, const std::string &name)</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00010">GraphUtils.cpp:10</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a90d8841cfbbc82ab02328f33fed24ac6"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a90d8841cfbbc82ab02328f33fed24ac6">armnn::Network::AddInputLayer</a></div><div class="ttdeci">IConnectableLayer * AddInputLayer(LayerBindingId id, const char *name=nullptr) override</div><div class="ttdoc">Adds an input layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01192">Network.cpp:1192</a></div></div> +<div class="ttc" id="_cl_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_cl_workload_factory_8hpp.xhtml">ClWorkloadFactory.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &tensorInfo)=0</div></div> +<div class="ttc" id="structarmnn_1_1_optimizer_options_xhtml_a6e1a42622ca43dafc7ba8e684c016eb4"><div class="ttname"><a href="structarmnn_1_1_optimizer_options.xhtml#a6e1a42622ca43dafc7ba8e684c016eb4">armnn::OptimizerOptions::m_ReduceFp32ToFp16</a></div><div class="ttdeci">bool m_ReduceFp32ToFp16</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00659">INetwork.hpp:659</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#l01011">Network.cpp:1011</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#l00600">INetwork.hpp:600</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml_a36a40a1209689f39a5a283209991da3c"><div class="ttname"><a href="classarmnn_1_1_network.xhtml#a36a40a1209689f39a5a283209991da3c">armnn::Network::AddActivationLayer</a></div><div class="ttdeci">IConnectableLayer * AddActivationLayer(const ActivationDescriptor &activationDescriptor, const char *name=nullptr) override</div><div class="ttdoc">Adds an activation layer to the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01400">Network.cpp:1400</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div> +<div class="ttc" id="_graph_utils_8hpp_xhtml"><div class="ttname"><a href="_graph_utils_8hpp.xhtml">GraphUtils.hpp</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#l00616">INetwork.hpp:616</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00020">Descriptors.hpp:20</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a></div><div class="ttdoc">min(a, max(b, input)) ReLu1 & ReLu6. </div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00042">IRuntime.hpp:42</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_network.xhtml">armnn::Network</a></div><div class="ttdoc">Private implementation of INetwork. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00028">Network.hpp:28</a></div></div> +<div class="ttc" id="structarmnn_1_1_backend_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_backend_options.xhtml">armnn::BackendOptions</a></div><div class="ttdoc">Struct for the users to pass backend specific options. </div><div class="ttdef"><b>Definition:</b> <a href="_backend_options_8hpp_source.xhtml#l00020">BackendOptions.hpp:20</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_a017b2990003a014234f13e999dc7c689"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#a017b2990003a014234f13e999dc7c689">armnn::ActivationDescriptor::m_A</a></div><div class="ttdeci">float m_A</div><div class="ttdoc">Alpha upper bound value used by the activation functions. (BoundedReLu, Linear, TanH, Elu). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00045">Descriptors.hpp:45</a></div></div> +<div class="ttc" id="_cl_optimized_network_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_cl_optimized_network_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</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="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot & GetOutputSlot(unsigned int index) const =0</div><div class="ttdoc">Get the const output slot handle by slot index. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00101">INetwork.hpp:101</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &destination)=0</div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00046">Network.cpp:46</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_a28c4c9cb15f6be3499abbc46b356060b"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#a28c4c9cb15f6be3499abbc46b356060b">armnn::ActivationDescriptor::m_B</a></div><div class="ttdeci">float m_B</div><div class="ttdoc">Beta lower bound value used by the activation functions. (BoundedReLu, Linear, TanH). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00047">Descriptors.hpp:47</a></div></div> +<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_af10fa7883e3579950f477bee92a64844"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">armnn::ActivationDescriptor::m_Function</a></div><div class="ttdeci">ActivationFunction m_Function</div><div class="ttdoc">The activation function to use (Sigmoid, TanH, Linear, ReLu, BoundedReLu, SoftReLu, LeakyReLu, Abs, Sqrt, Square, Elu). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00043">Descriptors.hpp:43</a></div></div> +<div class="ttc" id="_cl_optimized_network_tests_8cpp_xhtml_a7b202b7840e9275a418d40a7d0f5e3b1"><div class="ttname"><a href="_cl_optimized_network_tests_8cpp.xhtml#a7b202b7840e9275a418d40a7d0f5e3b1">BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(OptimizeValidateGpuDeviceSupportLayerNoFallback)</div><div class="ttdef"><b>Definition:</b> <a href="_cl_optimized_network_tests_8cpp_source.xhtml#l00018">ClOptimizedNetworkTests.cpp:18</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimized_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_optimized_network.xhtml">armnn::OptimizedNetwork</a></div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00282">Network.hpp:282</a></div></div> +</div><!-- fragment --></div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_1ad86c6d39ab715a831555571b9e98a5.xhtml">cl</a></li><li class="navelem"><a class="el" href="dir_02bab2737bbb2fb3882a0be567244fbf.xhtml">test</a></li><li class="navelem"><a class="el" href="_cl_optimized_network_tests_8cpp.xhtml">ClOptimizedNetworkTests.cpp</a></li> + <li class="footer">Generated on Thu Nov 26 2020 11:04:25 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> |