IVGCVSW-3726 Upload ArmNN Doxygen files

 * Upload current ArmNN Doxygen files

Signed-off-by: Ryan OShea <Ryan.OShea2@arm.com>
Change-Id: I8989ed16ee40a99a4495b100bd009cf3e24a7285
diff --git a/Documentation/_neon_convolution2d_workload_8cpp_source.xhtml b/Documentation/_neon_convolution2d_workload_8cpp_source.xhtml
new file mode 100644
index 0000000..2b87865
--- /dev/null
+++ b/Documentation/_neon_convolution2d_workload_8cpp_source.xhtml
@@ -0,0 +1,148 @@
+<!-- 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/neon/workloads/NeonConvolution2dWorkload.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">
+  $(document).ready(initResizable);
+</script>
+<link href="search/search.css" rel="stylesheet" type="text/css"/>
+<script type="text/javascript" src="search/searchdata.js"></script>
+<script type="text/javascript" src="search/search.js"></script>
+<script type="text/x-mathjax-config">
+  MathJax.Hub.Config({
+    extensions: ["tex2jax.js"],
+    jax: ["input/TeX","output/HTML-CSS"],
+});
+</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script>
+<link href="doxygen.css" rel="stylesheet" type="text/css" />
+<link href="stylesheet.css" rel="stylesheet" type="text/css"/>
+</head>
+<body>
+<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
+<div id="titlearea">
+<table cellspacing="0" cellpadding="0">
+ <tbody>
+ <tr style="height: 56px;">
+  <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/>
+  <td style="padding-left: 0.5em;">
+   <div id="projectname">
+   &#160;<span id="projectnumber">20.02</span>
+   </div>
+  </td>
+ </tr>
+ </tbody>
+</table>
+</div>
+<!-- end header part -->
+<!-- Generated by Doxygen 1.8.13 -->
+<script type="text/javascript">
+var searchBox = new SearchBox("searchBox", "search",false,'Search');
+</script>
+<script type="text/javascript" src="menudata.js"></script>
+<script type="text/javascript" src="menu.js"></script>
+<script type="text/javascript">
+$(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('_neon_convolution2d_workload_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">NeonConvolution2dWorkload.cpp</div>  </div>
+</div><!--header-->
+<div class="contents">
+<a href="_neon_convolution2d_workload_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>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_neon_convolution2d_workload_8hpp.xhtml">NeonConvolution2dWorkload.hpp</a>&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;</div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_cpu_tensor_handle_8hpp.xhtml">backendsCommon/CpuTensorHandle.hpp</a>&gt;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_arm_compute_tensor_utils_8hpp.xhtml">aclCommon/ArmComputeTensorUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_neon_workload_utils_8hpp.xhtml">neon/workloads/NeonWorkloadUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;</div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;arm_compute/runtime/NEON/functions/NEConvolutionLayer.h&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;</div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_types_8hpp.xhtml">armnn/Types.hpp</a>&gt;</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_half_8hpp.xhtml">Half.hpp</a>&gt;</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;</div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;{</div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="keyword">using namespace </span>armcomputetensorutils;</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;</div><div class="line"><a name="l00022"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#af64bb043263ba7d09c98fd88da60726d">   22</a></span>&#160;<a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> <a class="code" href="namespacearmnn.xhtml#af64bb043263ba7d09c98fd88da60726d">NeonConvolution2dWorkloadValidate</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; input,</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; output,</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;    <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a>&amp; descriptor,</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; weights,</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_optional.xhtml">Optional&lt;TensorInfo&gt;</a>&amp; biases)</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;{</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;    <span class="keyword">const</span> arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    <span class="keyword">const</span> arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;    <span class="keyword">const</span> arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    <span class="keyword">const</span> arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a>,</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;                                                                      descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a>);</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    arm_compute::TensorInfo aclBiasesInfo;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    arm_compute::TensorInfo *optionalAclBiasesInfo = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    {</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;        BOOST_ASSERT(biases.<a class="code" href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">has_value</a>());</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;        aclBiasesInfo = BuildArmComputeTensorInfo(biases.<a class="code" href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">value</a>(), descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;        optionalAclBiasesInfo = &amp;aclBiasesInfo;</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    }</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor);</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;    <span class="keywordflow">return</span> arm_compute::NEConvolutionLayer::validate(&amp;aclInputInfo,</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;                                                     &amp;aclWeightsInfo,</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;                                                     optionalAclBiasesInfo,</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;                                                     &amp;aclOutputInfo,</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;                                                     layerInfo,</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;                                                     arm_compute::WeightsInfo(),</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;                                                     aclDilationInfo);</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;}</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;</div><div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_convolution2d_workload.xhtml#a47763294588d6290ada7eda9e9047dbb">   57</a></span>&#160;<a class="code" href="classarmnn_1_1_neon_convolution2d_workload.xhtml#a47763294588d6290ada7eda9e9047dbb">NeonConvolution2dWorkload::NeonConvolution2dWorkload</a>(</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">Convolution2dQueueDescriptor</a>&amp; descriptor, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>&amp; <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>,</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    std::shared_ptr&lt;arm_compute::MemoryManagerOnDemand&gt;&amp; memoryManager)</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    : <a class="code" href="classarmnn_1_1_base_workload.xhtml">BaseWorkload</a>&lt;<a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">Convolution2dQueueDescriptor</a>&gt;(descriptor, info)</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;{</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    <span class="keyword">using</span> arm_compute::NEDirectConvolutionLayer;</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">ValidateInputsOutputs</a>(<span class="stringliteral">&quot;NeonConvolution2dWorkload&quot;</span>, 1, 1);</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="comment">// todo: check tensor shapes match.</span></div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    arm_compute::ITensor&amp; input = boost::polymorphic_downcast&lt;IAclTensorHandle*&gt;(<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0])-&gt;GetTensor();</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    arm_compute::ITensor&amp; output = boost::polymorphic_downcast&lt;IAclTensorHandle*&gt;(<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0])-&gt;GetTensor();</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a> aclDataLayout = ConvertDataLayout(<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    input.info()-&gt;set_data_layout(aclDataLayout);</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    output.info()-&gt;set_data_layout(aclDataLayout);</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    m_KernelTensor = std::make_unique&lt;arm_compute::Tensor&gt;();</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    BuildArmComputeTensor(*m_KernelTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">m_Weight</a>-&gt;<a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>(), <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    {</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;        m_BiasTensor = std::make_unique&lt;arm_compute::Tensor&gt;();</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;        BuildArmComputeTensor(*m_BiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml#ab3437cee6b0687812104fc1b37cbe8b3">m_Bias</a>-&gt;<a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>(), <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    }</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>);</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    <span class="keyword">const</span> arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D(<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a>,</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;                                                                      <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a>);</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    <span class="keyword">auto</span> convolutionLayer = std::make_unique&lt;arm_compute::NEConvolutionLayer&gt;(memoryManager);</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;    convolutionLayer-&gt;configure(&amp;input,</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;                                m_KernelTensor.get(),</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;                                m_BiasTensor.get(),</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;                                &amp;output,</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;                                padStrideInfo,</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;                                arm_compute::WeightsInfo(),</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;                                aclDilationInfo);</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    m_ConvolutionLayer.reset(convolutionLayer.release());</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    BOOST_ASSERT(m_ConvolutionLayer);</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ad9aa8d49d42ada3f757290033af39857">InitializeArmComputeTensorData</a>(*m_KernelTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">m_Weight</a>);</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;    {</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;        <a class="code" href="namespacearmnn.xhtml#ad9aa8d49d42ada3f757290033af39857">InitializeArmComputeTensorData</a>(*m_BiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml#ab3437cee6b0687812104fc1b37cbe8b3">m_Bias</a>);</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    }</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    m_ConvolutionLayer-&gt;prepare();</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;    FreeUnusedTensors();</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;}</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;</div><div class="line"><a name="l00113"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_convolution2d_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">  113</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_neon_convolution2d_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">NeonConvolution2dWorkload::Execute</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    <a class="code" href="_neon_workload_utils_8hpp.xhtml#a8bf91fd5e5875631bcf6abbcd97fe2f4">ARMNN_SCOPED_PROFILING_EVENT_NEON</a>(<span class="stringliteral">&quot;NeonConvolution2dWorkload_Execute&quot;</span>);</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    m_ConvolutionLayer-&gt;run();</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;}</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;<span class="keywordtype">void</span> NeonConvolution2dWorkload::FreeUnusedTensors()</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;{</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    FreeTensorIfUnused(m_KernelTensor);</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;    FreeTensorIfUnused(m_BiasTensor);</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;}</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;} <span class="comment">//namespace armnn</span></div><div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::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#l00438">Descriptors.hpp:438</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_queue_descriptor_xhtml_ab3437cee6b0687812104fc1b37cbe8b3"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml#ab3437cee6b0687812104fc1b37cbe8b3">armnn::Convolution2dQueueDescriptor::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#l00177">WorkloadData.hpp:177</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::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#l00440">Descriptors.hpp:440</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00049">Types.hpp:49</a></div></div>
+<div class="ttc" id="classarmnn_1_1_neon_convolution2d_workload_xhtml_ae071e8822437c78baea75c3aef3a263a"><div class="ttname"><a href="classarmnn_1_1_neon_convolution2d_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">armnn::NeonConvolution2dWorkload::Execute</a></div><div class="ttdeci">void Execute() const override</div><div class="ttdef"><b>Definition:</b> <a href="_neon_convolution2d_workload_8cpp_source.xhtml#l00113">NeonConvolution2dWorkload.cpp:113</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_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#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00392">Descriptors.hpp:392</a></div></div>
+<div class="ttc" id="classarmnn_1_1_base_workload_xhtml_a0a487c549c63319505095b855ea3c195"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#a0a487c549c63319505095b855ea3c195">armnn::BaseWorkload&lt; Convolution2dQueueDescriptor &gt;::m_Data</a></div><div class="ttdeci">const Convolution2dQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00046">Workload.hpp:46</a></div></div>
+<div class="ttc" id="_neon_workload_utils_8hpp_xhtml_a8bf91fd5e5875631bcf6abbcd97fe2f4"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml#a8bf91fd5e5875631bcf6abbcd97fe2f4">ARMNN_SCOPED_PROFILING_EVENT_NEON</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_NEON(name)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00017">NeonWorkloadUtils.hpp:17</a></div></div>
+<div class="ttc" id="_arm_compute_tensor_utils_8hpp_xhtml"><div class="ttname"><a href="_arm_compute_tensor_utils_8hpp.xhtml">ArmComputeTensorUtils.hpp</a></div></div>
+<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a765d2cee4ccce5b9467e0c2b6d25b84a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">armnn::QueueDescriptor::ValidateInputsOutputs</a></div><div class="ttdeci">void ValidateInputsOutputs(const std::string &amp;descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8cpp_source.xhtml#l00461">WorkloadData.cpp:461</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="structarmnn_1_1_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::Convolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation along y axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00436">Descriptors.hpp:436</a></div></div>
+<div class="ttc" id="classarmnn_1_1_optional_reference_switch_xhtml_a77c7d528ac063d870b8c8426ec81c1c3"><div class="ttname"><a href="classarmnn_1_1_optional_reference_switch.xhtml#a77c7d528ac063d870b8c8426ec81c1c3">armnn::OptionalReferenceSwitch&lt; std::is_reference&lt; T &gt;::value, T &gt;::value</a></div><div class="ttdeci">const T &amp; value() const</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00146">Optional.hpp:146</a></div></div>
+<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00049">WorkloadData.hpp:49</a></div></div>
+<div class="ttc" id="classarmnn_1_1_base_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml">armnn::BaseWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00028">Workload.hpp:28</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_queue_descriptor_xhtml_a3369b66d9316a773a41711e3f590c041"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">armnn::Convolution2dQueueDescriptor::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#l00176">WorkloadData.hpp:176</a></div></div>
+<div class="ttc" id="classarmnn_1_1_optional_base_xhtml_a86b749ce2c4bc627fa8a1fcfaf0e314f"><div class="ttname"><a href="classarmnn_1_1_optional_base.xhtml#a86b749ce2c4bc627fa8a1fcfaf0e314f">armnn::OptionalBase::has_value</a></div><div class="ttdeci">bool has_value() const noexcept</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00053">Optional.hpp:53</a></div></div>
+<div class="ttc" id="_types_8hpp_xhtml"><div class="ttname"><a href="_types_8hpp.xhtml">Types.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70b"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a></div><div class="ttdeci">Status</div><div class="ttdoc">enumeration </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00026">Types.hpp:26</a></div></div>
+<div class="ttc" id="_neon_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml">NeonWorkloadUtils.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_af64bb043263ba7d09c98fd88da60726d"><div class="ttname"><a href="namespacearmnn.xhtml#af64bb043263ba7d09c98fd88da60726d">armnn::NeonConvolution2dWorkloadValidate</a></div><div class="ttdeci">arm_compute::Status NeonConvolution2dWorkloadValidate(const TensorInfo &amp;input, const TensorInfo &amp;output, const Convolution2dDescriptor &amp;descriptor, const TensorInfo &amp;weights, const Optional&lt; TensorInfo &gt; &amp;biases)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_convolution2d_workload_8cpp_source.xhtml#l00022">NeonConvolution2dWorkload.cpp:22</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_ad9aa8d49d42ada3f757290033af39857"><div class="ttname"><a href="namespacearmnn.xhtml#ad9aa8d49d42ada3f757290033af39857">armnn::InitializeArmComputeTensorData</a></div><div class="ttdeci">void InitializeArmComputeTensorData(arm_compute::Tensor &amp;tensor, const ConstCpuTensorHandle *handle)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00035">NeonWorkloadUtils.hpp:35</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="structarmnn_1_1_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">armnn::Convolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00168">WorkloadData.hpp:168</a></div></div>
+<div class="ttc" id="_half_8hpp_xhtml"><div class="ttname"><a href="_half_8hpp.xhtml">Half.hpp</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::Convolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation along x axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00434">Descriptors.hpp:434</a></div></div>
+<div class="ttc" id="_neon_convolution2d_workload_8hpp_xhtml"><div class="ttname"><a href="_neon_convolution2d_workload_8hpp.xhtml">NeonConvolution2dWorkload.hpp</a></div></div>
+<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00031">WorkloadData.hpp:31</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
+<div class="ttc" id="classarmnn_1_1_neon_convolution2d_workload_xhtml_a47763294588d6290ada7eda9e9047dbb"><div class="ttname"><a href="classarmnn_1_1_neon_convolution2d_workload.xhtml#a47763294588d6290ada7eda9e9047dbb">armnn::NeonConvolution2dWorkload::NeonConvolution2dWorkload</a></div><div class="ttdeci">NeonConvolution2dWorkload(const Convolution2dQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info, std::shared_ptr&lt; arm_compute::MemoryManagerOnDemand &gt; &amp;memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_convolution2d_workload_8cpp_source.xhtml#l00057">NeonConvolution2dWorkload.cpp:57</a></div></div>
+<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div>
+<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00030">WorkloadData.hpp:30</a></div></div>
+<div class="ttc" id="classarmnn_1_1_const_cpu_tensor_handle_xhtml_a66e8f43a5b42b500871ed96e15419567"><div class="ttname"><a href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">armnn::ConstCpuTensorHandle::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.xhtml#l00037">CpuTensorHandle.hpp:37</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_d86eb514662c7c08e168285f21d00ea1.xhtml">neon</a></li><li class="navelem"><a class="el" href="dir_369c3c20501d0d10bd0354bf11c2f559.xhtml">workloads</a></li><li class="navelem"><a class="el" href="_neon_convolution2d_workload_8cpp.xhtml">NeonConvolution2dWorkload.cpp</a></li>
+    <li class="footer">Generated on Fri Mar 13 2020 16:09:12 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>