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diff --git a/20.02/_depthwise_convolution2d_layer_8cpp_source.xhtml b/20.02/_depthwise_convolution2d_layer_8cpp_source.xhtml new file mode 100644 index 0000000000..c374d56b74 --- /dev/null +++ b/20.02/_depthwise_convolution2d_layer_8cpp_source.xhtml @@ -0,0 +1,175 @@ +<!-- 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/layers/DepthwiseConvolution2dLayer.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('_depthwise_convolution2d_layer_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">DepthwiseConvolution2dLayer.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_depthwise_convolution2d_layer_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="_depthwise_convolution2d_layer_8hpp.xhtml">DepthwiseConvolution2dLayer.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_layer_clone_base_8hpp.xhtml">LayerCloneBase.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_types_utils_8hpp.xhtml">armnn/TypesUtils.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_data_layout_indexed_8hpp.xhtml">armnnUtils/DataLayoutIndexed.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_cpu_tensor_handle_8hpp.xhtml">backendsCommon/CpuTensorHandle.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_workload_factory_8hpp.xhtml">backendsCommon/WorkloadFactory.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 <string></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="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.xhtml">armnnUtils</a>;</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="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> {</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"><a class="line" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#ae7927aab32dbcb1b0a6fb5e43bcd4419"> 23</a></span> <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#ae7927aab32dbcb1b0a6fb5e43bcd4419">DepthwiseConvolution2dLayer::DepthwiseConvolution2dLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a>& param,</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  : <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml">LayerWithParameters</a>(1, 1, <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>::<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4af97adbfc88b7012a0243215b1076e7e7">DepthwiseConvolution2d</a>, param, name)</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> {</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> }</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"><a class="line" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2ca654770a1890f15e3c7aab98e434a5"> 29</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2ca654770a1890f15e3c7aab98e434a5">DepthwiseConvolution2dLayer::SerializeLayerParameters</a>(<a class="code" href="namespacearmnn.xhtml#a8c42c6647e31ebe525aeba878d133e45">ParameterStringifyFunction</a>& fn)<span class="keyword"> const</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword"></span>{</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keyword">const</span> std::vector<TensorShape>& inputShapes =</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  {</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->GetTensorInfo().GetShape()</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  };</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> filterShape = inputShapes[1];</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml">DataLayoutIndexed</a> dataLayoutIndex(<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = filterShape[1];</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterWidth = filterShape[3];</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterHeight = filterShape[2];</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthMultiplier = filterShape[0];</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  fn(<span class="stringliteral">"FilterWidth"</span>,std::to_string(filterWidth));</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  fn(<span class="stringliteral">"FilterHeight"</span>,std::to_string(filterHeight));</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  fn(<span class="stringliteral">"DepthMultiplier"</span>,std::to_string(depthMultiplier));</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  fn(<span class="stringliteral">"InputChannels"</span>,std::to_string(inputChannels));</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>  <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#a2ca654770a1890f15e3c7aab98e434a5">LayerWithParameters<DepthwiseConvolution2dDescriptor>::SerializeLayerParameters</a>(fn);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> }</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#adfa912d0c4c6c00f1af2cbfa799572b7"> 51</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#adfa912d0c4c6c00f1af2cbfa799572b7">DepthwiseConvolution2dLayer::CreateWorkload</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">IWorkloadFactory</a>& factory)<span class="keyword"> const</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="keyword"></span>{</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="comment">// on this level constant data should not be released..</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> != <span class="keyword">nullptr</span>, <span class="stringliteral">"DepthwiseConvolution2dLayer: Weights data should not be null."</span>);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">DepthwiseConvolution2dQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">m_Weight</a> = <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a>.get();</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="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</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>  BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> != <span class="keyword">nullptr</span>, <span class="stringliteral">"DepthwiseConvolution2dLayer: Bias data should not be null."</span>);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#ab3437cee6b0687812104fc1b37cbe8b3">m_Bias</a> = <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>.get();</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  }</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">return</span> factory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#accb9759dfd2880efe0f8d2705ddee448">CreateDepthwiseConvolution2d</a>(descriptor, <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#a30a858b2b26d651a066537e499fbf40d">PrepInfoAndDesc</a>(descriptor));</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> }</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div><div class="line"><a name="l00068"></a><span class="lineno"><a class="line" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a6f56b4ee567a69e7daf2e9bd3053646c"> 68</a></span> <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">DepthwiseConvolution2dLayer</a>* <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a6f56b4ee567a69e7daf2e9bd3053646c">DepthwiseConvolution2dLayer::Clone</a>(<a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& graph)<span class="keyword"> const</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="keyword"></span>{</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keyword">auto</span> layer = CloneBase<DepthwiseConvolution2dLayer>(graph, <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>, <a class="code" href="classarmnn_1_1_layer.xhtml#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) : <span class="keyword">nullptr</span>;</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="keywordflow">if</span> (layer->m_Param.m_BiasEnabled)</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  layer->m_Bias = <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  }</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">return</span> std::move(layer);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> }</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> </div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> std::vector<TensorShape></div><div class="line"><a name="l00082"></a><span class="lineno"><a class="line" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a65ca562c882ad619684445a1402f415a"> 82</a></span> <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a65ca562c882ad619684445a1402f415a">DepthwiseConvolution2dLayer::InferOutputShapes</a>(<span class="keyword">const</span> std::vector<TensorShape>& inputShapes)<span class="keyword"> const</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="keyword"></span>{</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  BOOST_ASSERT(inputShapes.size() == 2);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& inputShape = inputShapes[0];</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& filterShape = inputShapes[1];</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, <span class="stringliteral">"Convolutions will always have 4D input."</span>);</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>  <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.xhtml">DataLayoutIndexed</a> dataLayoutIndex(<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize = inputShape[0];</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = inputShape[dataLayoutIndex.GetHeightIndex()];</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = inputShape[dataLayoutIndex.GetWidthIndex()];</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = inputShape[dataLayoutIndex.GetChannelsIndex()];</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> </div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="comment">// Expected filter shape: [ M, I, H, W ] - This shape does NOT depend on the data layout</span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="comment">// Namely: [ depth multiplier, input channels, filter height, filter width ]</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="comment">// Output channels = input channels * depthMultiplier</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthMultiplier = filterShape[0];</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> </div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterHeight = filterShape[2];</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dilatedFilterHeight = filterHeight + (<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> - 1) * (filterHeight - 1);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> readHeight = (inputHeight + <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> + <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>) - dilatedFilterHeight;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = 1 + (readHeight / <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterWidth = filterShape[3];</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dilatedFilterWidth = filterWidth + (<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> - 1) * (filterWidth - 1);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> readWidth = (inputWidth + <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> + <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>) - dilatedFilterWidth;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = 1 + (readWidth / <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = inputChannels * depthMultiplier;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputBatchSize = inputBatchSize;</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>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> tensorShape = <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a> ?</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{ outputBatchSize, outputHeight, outputWidth, outputChannels } :</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{ outputBatchSize, outputChannels, outputHeight, outputWidth };</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="keywordflow">return</span> std::vector<TensorShape>{ tensorShape };</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> </div><div class="line"><a name="l00122"></a><span class="lineno"><a class="line" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a8c8f543d7e9729362c266d12ec169966"> 122</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a8c8f543d7e9729362c266d12ec169966">DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs</a>()</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>  <a class="code" href="classarmnn_1_1_layer.xhtml#a0607e36e88f38c34c71c663164b76776">VerifyLayerConnections</a>(1, <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</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="comment">// on this level constant data should not be released..</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> != <span class="keyword">nullptr</span>, <span class="stringliteral">"DepthwiseConvolution2dLayer: Weights data should not be null."</span>);</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">auto</span> inferredShapes = <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>({</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-><a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->GetTensorInfo().GetShape()</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> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  BOOST_ASSERT(inferredShapes.size() == 1);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  ConditionalThrowIfNotEqual<LayerValidationException>(</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="stringliteral">"DepthwiseConvolution2dLayer: TensorShape set on OutputSlot[0] does not match the inferred shape."</span>,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  inferredShapes[0]);</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> }</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> </div><div class="line"><a name="l00142"></a><span class="lineno"><a class="line" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#abe659a5afa7523f5dbc04bcba9b31f1a"> 142</a></span> <a class="code" href="classarmnn_1_1_layer.xhtml#a585d59ec610af46a76487fd6c1c55ac1">Layer::ConstantTensors</a> <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#abe659a5afa7523f5dbc04bcba9b31f1a">DepthwiseConvolution2dLayer::GetConstantTensorsByRef</a>()</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> {</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordflow">return</span> {<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a>, <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>};</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> }</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> </div><div class="line"><a name="l00147"></a><span class="lineno"><a class="line" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a75a50f464326fefa605ea84ae2c9be85"> 147</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a75a50f464326fefa605ea84ae2c9be85">DepthwiseConvolution2dLayer::Accept</a>(<a class="code" href="classarmnn_1_1_i_layer_visitor.xhtml">ILayerVisitor</a>& visitor)<span class="keyword"> const</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="keyword"></span>{</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> weightsTensor(<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->GetTensorInfo(), <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a> optionalBiasTensor = <a class="code" href="structarmnn_1_1_empty_optional.xhtml">EmptyOptional</a>();</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> </div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>().m_BiasEnabled)</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  {</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> biasTensor(<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>->GetTensorInfo(), <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>->Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  optionalBiasTensor = <a class="code" href="classarmnn_1_1_optional.xhtml">Optional<ConstTensor></a>(biasTensor);</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  }</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  visitor.<a class="code" href="classarmnn_1_1_i_layer_visitor.xhtml#ad39aaac8f8fb790ae364c87f1a249d68">VisitDepthwiseConvolution2dLayer</a>(<span class="keyword">this</span>, <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>(), weightsTensor, optionalBiasTensor, <a class="code" href="classarmnn_1_1_layer.xhtml#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> }</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> } <span class="comment">// namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::DepthwiseConvolution2dLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8cpp_source.xhtml#l00082">DepthwiseConvolution2dLayer.cpp:82</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_adfa912d0c4c6c00f1af2cbfa799572b7"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#adfa912d0c4c6c00f1af2cbfa799572b7">armnn::DepthwiseConvolution2dLayer::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override</div><div class="ttdoc">Makes a workload for the DepthwiseConvolution2d type. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8cpp_source.xhtml#l00051">DepthwiseConvolution2dLayer.cpp:51</a></div></div> +<div class="ttc" id="_data_layout_indexed_8hpp_xhtml"><div class="ttname"><a href="_data_layout_indexed_8hpp.xhtml">DataLayoutIndexed.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00490">Descriptors.hpp:490</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_with_parameters_xhtml_ad32ac22bc72e28dfd6b466d143c8e262"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">armnn::LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param</a></div><div class="ttdeci">DepthwiseConvolution2dDescriptor m_Param</div><div class="ttdoc">The parameters for the layer (not including tensor-valued weights etc.). </div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.xhtml#l00050">LayerWithParameters.hpp:50</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_with_parameters_xhtml_a502c06a1b13e6d90a6cbf47c081f1444"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.xhtml#a502c06a1b13e6d90a6cbf47c081f1444">armnn::LayerWithParameters< DepthwiseConvolution2dDescriptor >::GetParameters</a></div><div class="ttdeci">const DepthwiseConvolution2dDescriptor & GetParameters() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.xhtml#l00018">LayerWithParameters.hpp:18</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00088">Tensor.hpp:88</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::DepthwiseConvolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00480">Descriptors.hpp:480</a></div></div> +<div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00270">Optional.hpp:270</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a6f56b4ee567a69e7daf2e9bd3053646c"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a6f56b4ee567a69e7daf2e9bd3053646c">armnn::DepthwiseConvolution2dLayer::Clone</a></div><div class="ttdeci">DepthwiseConvolution2dLayer * Clone(Graph &graph) const override</div><div class="ttdoc">Creates a dynamically-allocated copy of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8cpp_source.xhtml#l00068">DepthwiseConvolution2dLayer.cpp:68</a></div></div> +<div class="ttc" id="_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_workload_factory_8hpp.xhtml">WorkloadFactory.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00492">Descriptors.hpp:492</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.xhtml#l00021">WorkloadFactory.hpp:21</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">armnn::DepthwiseConvolution2dLayer</a></div><div class="ttdoc">This layer represents a depthwise convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.xhtml#l00015">DepthwiseConvolution2dLayer.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a39925bc24d3afcfb322a46a5884fadb9"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">armnn::DepthwiseConvolution2dLayer::m_Bias</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Bias</div><div class="ttdoc">A unique pointer to store Bias values. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.xhtml#l00021">DepthwiseConvolution2dLayer.hpp:21</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml_ab3437cee6b0687812104fc1b37cbe8b3"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#ab3437cee6b0687812104fc1b37cbe8b3">armnn::DepthwiseConvolution2dQueueDescriptor::m_Bias</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Bias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00192">WorkloadData.hpp:192</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::DepthwiseConvolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00474">Descriptors.hpp:474</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_abe659a5afa7523f5dbc04bcba9b31f1a"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#abe659a5afa7523f5dbc04bcba9b31f1a">armnn::DepthwiseConvolution2dLayer::GetConstantTensorsByRef</a></div><div class="ttdeci">ConstantTensors GetConstantTensorsByRef() override</div><div class="ttdoc">Retrieve the handles to the constant values stored by the layer. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8cpp_source.xhtml#l00142">DepthwiseConvolution2dLayer.cpp:142</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_with_parameters_xhtml_a2ca654770a1890f15e3c7aab98e434a5"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.xhtml#a2ca654770a1890f15e3c7aab98e434a5">armnn::LayerWithParameters::SerializeLayerParameters</a></div><div class="ttdeci">void SerializeLayerParameters(ParameterStringifyFunction &fn) const override</div><div class="ttdoc">Helper to serialize the layer parameters to string (currently used in DotSerializer and company)...</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.xhtml#l00022">LayerWithParameters.hpp:22</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="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_input_slot_xhtml_a3153abb7c0c0a84629079b2fac7db54f"><div class="ttname"><a href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">armnn::InputSlot::GetConnection</a></div><div class="ttdeci">const IOutputSlot * GetConnection() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00199">Layer.hpp:199</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::DepthwiseConvolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation factor value for height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00488">Descriptors.hpp:488</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml_a3369b66d9316a773a41711e3f590c041"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">armnn::DepthwiseConvolution2dQueueDescriptor::m_Weight</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Weight</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00191">WorkloadData.hpp:191</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a8c8f543d7e9729362c266d12ec169966">armnn::DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs</a></div><div class="ttdeci">void ValidateTensorShapesFromInputs() override</div><div class="ttdoc">Check if the input tensor shape(s) will lead to a valid configuration of DepthwiseConvolution2dLayer...</div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8cpp_source.xhtml#l00122">DepthwiseConvolution2dLayer.cpp:122</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a2ca654770a1890f15e3c7aab98e434a5"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2ca654770a1890f15e3c7aab98e434a5">armnn::DepthwiseConvolution2dLayer::SerializeLayerParameters</a></div><div class="ttdeci">void SerializeLayerParameters(ParameterStringifyFunction &fn) const override</div><div class="ttdoc">Helper to serialize the layer parameters to string. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8cpp_source.xhtml#l00029">DepthwiseConvolution2dLayer.cpp:29</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0607e36e88f38c34c71c663164b76776"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0607e36e88f38c34c71c663164b76776">armnn::Layer::VerifyLayerConnections</a></div><div class="ttdeci">void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00338">Layer.cpp:338</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div> +<div class="ttc" id="_types_utils_8hpp_xhtml"><div class="ttname"><a href="_types_utils_8hpp.xhtml">TypesUtils.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::DepthwiseConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00482">Descriptors.hpp:482</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::DepthwiseConvolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation factor value for width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00486">Descriptors.hpp:486</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::DepthwiseConvolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00478">Descriptors.hpp:478</a></div></div> +<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_xhtml"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.xhtml">armnnUtils::DataLayoutIndexed</a></div><div class="ttdoc">Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00017">DataLayoutIndexed.hpp:17</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_ae7927aab32dbcb1b0a6fb5e43bcd4419"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#ae7927aab32dbcb1b0a6fb5e43bcd4419">armnn::DepthwiseConvolution2dLayer::DepthwiseConvolution2dLayer</a></div><div class="ttdeci">DepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor &param, const char *name)</div><div class="ttdoc">Constructor to create a DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8cpp_source.xhtml#l00023">DepthwiseConvolution2dLayer.cpp:23</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00199">Tensor.hpp:199</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_layer_visitor_xhtml_ad39aaac8f8fb790ae364c87f1a249d68"><div class="ttname"><a href="classarmnn_1_1_i_layer_visitor.xhtml#ad39aaac8f8fb790ae364c87f1a249d68">armnn::ILayerVisitor::VisitDepthwiseConvolution2dLayer</a></div><div class="ttdeci">virtual void VisitDepthwiseConvolution2dLayer(const IConnectableLayer *layer, const DepthwiseConvolution2dDescriptor &convolution2dDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)=0</div><div class="ttdoc">Function that a 2D depthwise convolution layer with biases should call back to when its Accept(ILayer...</div></div> +<div class="ttc" id="_depthwise_convolution2d_layer_8hpp_xhtml"><div class="ttname"><a href="_depthwise_convolution2d_layer_8hpp.xhtml">DepthwiseConvolution2dLayer.hpp</a></div></div> +<div class="ttc" id="_exceptions_8hpp_xhtml_aa3be76aec4ce713822a5ea1ecbb7bc61"><div class="ttname"><a href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a></div><div class="ttdeci">#define CHECK_LOCATION()</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00192">Exceptions.hpp:192</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="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4af97adbfc88b7012a0243215b1076e7e7"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4af97adbfc88b7012a0243215b1076e7e7">armnn::LayerType::DepthwiseConvolution2d</a></div></div> +<div class="ttc" id="_cpu_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.xhtml">CpuTensorHandle.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a75a50f464326fefa605ea84ae2c9be85"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a75a50f464326fefa605ea84ae2c9be85">armnn::DepthwiseConvolution2dLayer::Accept</a></div><div class="ttdeci">void Accept(ILayerVisitor &visitor) const override</div><div class="ttdoc">Apply a visitor to this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8cpp_source.xhtml#l00147">DepthwiseConvolution2dLayer.cpp:147</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="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::DepthwiseConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00484">Descriptors.hpp:484</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_with_parameters_xhtml_a30a858b2b26d651a066537e499fbf40d"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.xhtml#a30a858b2b26d651a066537e499fbf40d">armnn::LayerWithParameters< DepthwiseConvolution2dDescriptor >::PrepInfoAndDesc</a></div><div class="ttdeci">WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const</div><div class="ttdoc">Helper function to reduce duplication in *LayerCreateWorkload. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.xhtml#l00043">LayerWithParameters.hpp:43</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_layer_visitor.xhtml">armnn::ILayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_layer_visitor_8hpp_source.xhtml#l00016">ILayerVisitor.hpp:16</a></div></div> +<div class="ttc" id="namespacearmnn_utils_xhtml"><div class="ttname"><a href="namespacearmnn_utils.xhtml">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.xhtml#l00013">DataLayoutIndexed.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a9943775a364fc4ab53b85ac88f311886"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">armnn::IOutputSlot::GetTensorInfo</a></div><div class="ttdeci">virtual const TensorInfo & GetTensorInfo() const =0</div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a7ddf0cf6f620d59c10e63495ace795d0"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a7ddf0cf6f620d59c10e63495ace795d0">armnn::Layer::GetName</a></div><div class="ttdeci">const char * GetName() const override</div><div class="ttdoc">Returns the name of the layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00305">Layer.hpp:305</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_with_parameters_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.xhtml">armnn::LayerWithParameters</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.xhtml#l00013">LayerWithParameters.hpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::DepthwiseConvolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.xhtml#l00019">DepthwiseConvolution2dLayer.hpp:19</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8c42c6647e31ebe525aeba878d133e45"><div class="ttname"><a href="namespacearmnn.xhtml#a8c42c6647e31ebe525aeba878d133e45">armnn::ParameterStringifyFunction</a></div><div class="ttdeci">std::function< void(const std::string &name, const std::string &value)> ParameterStringifyFunction</div><div class="ttdef"><b>Definition:</b> <a href="_serialize_layer_parameters_8hpp_source.xhtml#l00014">SerializeLayerParameters.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a585d59ec610af46a76487fd6c1c55ac1"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a585d59ec610af46a76487fd6c1c55ac1">armnn::Layer::ConstantTensors</a></div><div class="ttdeci">std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >> ConstantTensors</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00363">Layer.hpp:363</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_accb9759dfd2880efe0f8d2705ddee448"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#accb9759dfd2880efe0f8d2705ddee448">armnn::IWorkloadFactory::CreateDepthwiseConvolution2d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateDepthwiseConvolution2d(const DepthwiseConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01177">WorkloadFactory.cpp:1177</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00063">Layer.cpp:63</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00444">Descriptors.hpp:444</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">armnn::DepthwiseConvolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00183">WorkloadData.hpp:183</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +<div class="ttc" id="_layer_clone_base_8hpp_xhtml"><div class="ttname"><a href="_layer_clone_base_8hpp.xhtml">LayerCloneBase.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8hpp_source.xhtml#l00014">InternalTypes.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::DepthwiseConvolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00476">Descriptors.hpp:476</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="dir_9da6642ce0fd5a8c83524f1b621275be.xhtml">layers</a></li><li class="navelem"><a class="el" href="_depthwise_convolution2d_layer_8cpp.xhtml">DepthwiseConvolution2dLayer.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> |