diff --git a/Documentation/backends_2reference_2workloads_2_mean_8cpp_source.xhtml b/Documentation/backends_2reference_2workloads_2_mean_8cpp_source.xhtml
new file mode 100644
index 0000000..50e576d
--- /dev/null
+++ b/Documentation/backends_2reference_2workloads_2_mean_8cpp_source.xhtml
@@ -0,0 +1,128 @@
+<!-- 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/reference/workloads/Mean.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('backends_2reference_2workloads_2_mean_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">Mean.cpp</div>  </div>
+</div><!--header-->
+<div class="contents">
+<a href="backends_2reference_2workloads_2_mean_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="_mean_8hpp.xhtml">Mean.hpp</a>&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_workload_data_8hpp.xhtml">backendsCommon/WorkloadData.hpp</a>&gt;</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;</div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="preprocessor">#include &lt;boost/numeric/conversion/cast.hpp&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;</div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;cmath&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;cstddef&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#include &lt;functional&gt;</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &lt;limits&gt;</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;{</div><div class="line"><a name="l00018"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a869f740e9c2fcb8642350c6e3d0b3742">   18</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="namespacearmnn.xhtml#a869f740e9c2fcb8642350c6e3d0b3742">NextIndex</a>(<span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDims, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>&amp; dims, std::vector&lt;unsigned int&gt;&amp; current)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> carry = 1;</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">   22</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = numDims; idx-- &gt; 0; )</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;    {</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> current_val = current[idx] + carry;</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;        <span class="keywordflow">if</span> (dims[idx] == current_val)</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;        {</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;            current[idx] = 0;</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;        }</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;        <span class="keywordflow">else</span></div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;        {</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;            current[idx] = current_val;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;            carry = 0;</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;            <span class="keywordflow">break</span>;</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;    }</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    <span class="keywordflow">return</span> (carry == 0);</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;</div><div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#ae86f1ca23eaa764da9e589cc8e39a969">   39</a></span>&#160;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearmnn.xhtml#ae86f1ca23eaa764da9e589cc8e39a969">ReducedOutputOffset</a>(<span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDims,</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;                                 <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>&amp; dims,</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;                                 std::vector&lt;unsigned int&gt;&amp; index,</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;                                 <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numAxis,</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;                                 <span class="keyword">const</span> std::vector&lt;unsigned int&gt;&amp; axis)</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;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> offset = 0;</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 0; idx &lt; numDims; ++idx)</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="keywordtype">bool</span> isAxis = <span class="keyword">false</span>;</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;        <span class="keywordflow">if</span> (!axis.empty())</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;        {</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;            <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axisIdx = 0; axisIdx &lt; numAxis; ++axisIdx)</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;            {</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;                <span class="keywordflow">if</span> (idx == axis[axisIdx])</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;                {</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;                    isAxis = <span class="keyword">true</span>;</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;                    <span class="keywordflow">break</span>;</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;                }</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;            }</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;        }</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;        <span class="keywordflow">if</span> (!isAxis)</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;            offset = offset * dims[idx] + index[idx];</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;    }</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    <span class="keywordflow">return</span> offset;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;}</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;} <span class="comment">// namespace</span></div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></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"><a class="line" href="namespacearmnn.xhtml#a165ae372a7f67cad64ef3395d30122ce">   71</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#a165ae372a7f67cad64ef3395d30122ce">Mean</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>&amp; inputInfo,</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;          <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>&amp; outputInfo,</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;          <span class="keyword">const</span> std::vector&lt;unsigned int&gt;&amp; axis,</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;          <a class="code" href="classarmnn_1_1_decoder.xhtml">Decoder&lt;float&gt;</a>&amp; input,</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;          <a class="code" href="classarmnn_1_1_encoder.xhtml">Encoder&lt;float&gt;</a>&amp; output)</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;{</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputNumDims = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputNumDims = outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> outputDims = outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputDims = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</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;    <span class="comment">// Initialise output data.</span></div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputs = 1;</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 0; idx &lt; outputNumDims; ++idx)</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    {</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;        numOutputs *= outputDims[idx];</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    }</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    std::vector&lt;float&gt; tempSum(numOutputs);</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 0; idx &lt; numOutputs; ++idx)</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    {</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;        output[idx];</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        output.<a class="code" href="classarmnn_1_1_encoder.xhtml#ae3b62b846a9c239f332830b9e36030eb">Set</a>(0.0f);</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;        tempSum[idx] = 0.0f;</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;</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    <span class="comment">// Initialise temp index.</span></div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    std::vector&lt;unsigned int&gt; tempIndex(inputNumDims);</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 0; idx &lt; inputNumDims; ++idx)</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    {</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;        tempIndex[idx] = 0;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    }</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;    std::vector&lt;unsigned int&gt; resolvedAxis = axis;</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    <span class="keywordflow">if</span> (resolvedAxis.empty())</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;      <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 0; idx &lt; inputNumDims; ++idx)</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;      {</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;          resolvedAxis.push_back(idx);</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">  113</span>&#160;    }</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;    <span class="keyword">auto</span> numResolvedAxis = <a class="code" href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">boost::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(resolvedAxis.size());</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    <span class="comment">// Iterates through input_data and sum up the reduced axis.</span></div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">bool</span> hasNext = <span class="keyword">true</span>; hasNext; hasNext = <a class="code" href="namespacearmnn.xhtml#a869f740e9c2fcb8642350c6e3d0b3742">NextIndex</a>(inputNumDims, inputDims, tempIndex))</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">unsigned</span> <span class="keywordtype">int</span> inputOffset = <a class="code" href="namespacearmnn.xhtml#ae86f1ca23eaa764da9e589cc8e39a969">ReducedOutputOffset</a>(inputNumDims, inputDims, tempIndex, 0, {});</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputOffset = <a class="code" href="namespacearmnn.xhtml#ae86f1ca23eaa764da9e589cc8e39a969">ReducedOutputOffset</a>(inputNumDims, inputDims, tempIndex,</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;                                                        numResolvedAxis, resolvedAxis);</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;        input[inputOffset];</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;        tempSum[outputOffset] += input.<a class="code" href="classarmnn_1_1_decoder.xhtml#ac729108381e2340bea12877971713ecb">Get</a>();</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;</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    <span class="comment">// Takes average by num of elements added to get mean.</span></div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    <span class="keywordtype">size_t</span> numElementsInAxis = 1;</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 0; idx &lt; numResolvedAxis; ++idx)</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    {</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> current = inputDims[resolvedAxis[idx]];</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;        BOOST_ASSERT(boost::numeric_cast&lt;float&gt;(current) &lt;</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;              (std::numeric_limits&lt;float&gt;::max() / boost::numeric_cast&lt;float&gt;(numElementsInAxis)));</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;        numElementsInAxis *= current;</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    }</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    <span class="keywordflow">if</span> (numElementsInAxis &gt; 0) {</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> idx = 0; idx &lt; numOutputs; ++idx)</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;        {</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;            output[idx];</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;            output.<a class="code" href="classarmnn_1_1_encoder.xhtml#ae3b62b846a9c239f332830b9e36030eb">Set</a>(tempSum[idx] / boost::numeric_cast&lt;float&gt;(numElementsInAxis));</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;        }</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    }</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;}</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;} <span class="comment">//namespace armnn</span></div><div class="ttc" id="namespacearmnn_xhtml_a869f740e9c2fcb8642350c6e3d0b3742"><div class="ttname"><a href="namespacearmnn.xhtml#a869f740e9c2fcb8642350c6e3d0b3742">armnn::NextIndex</a></div><div class="ttdeci">bool NextIndex(const unsigned int numDims, const armnn::TensorShape &amp;dims, std::vector&lt; unsigned int &gt; &amp;current)</div><div class="ttdef"><b>Definition:</b> <a href="backends_2reference_2workloads_2_mean_8cpp_source.xhtml#l00018">Mean.cpp:18</a></div></div>
+<div class="ttc" id="_workload_data_8hpp_xhtml"><div class="ttname"><a href="_workload_data_8hpp.xhtml">WorkloadData.hpp</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 &amp; 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="namespacearmnn_xhtml_ae86f1ca23eaa764da9e589cc8e39a969"><div class="ttname"><a href="namespacearmnn.xhtml#ae86f1ca23eaa764da9e589cc8e39a969">armnn::ReducedOutputOffset</a></div><div class="ttdeci">unsigned int ReducedOutputOffset(const unsigned int numDims, const armnn::TensorShape &amp;dims, std::vector&lt; unsigned int &gt; &amp;index, const unsigned int numAxis, const std::vector&lt; unsigned int &gt; &amp;axis)</div><div class="ttdef"><b>Definition:</b> <a href="backends_2reference_2workloads_2_mean_8cpp_source.xhtml#l00039">Mean.cpp:39</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="classarmnn_1_1_encoder_xhtml_ae3b62b846a9c239f332830b9e36030eb"><div class="ttname"><a href="classarmnn_1_1_encoder.xhtml#ae3b62b846a9c239f332830b9e36030eb">armnn::Encoder::Set</a></div><div class="ttdeci">virtual void Set(IType right)=0</div></div>
+<div class="ttc" id="classarmnn_1_1_encoder_xhtml"><div class="ttname"><a href="classarmnn_1_1_encoder.xhtml">armnn::Encoder&lt; float &gt;</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_decoder_xhtml_ac729108381e2340bea12877971713ecb"><div class="ttname"><a href="classarmnn_1_1_decoder.xhtml#ac729108381e2340bea12877971713ecb">armnn::Decoder::Get</a></div><div class="ttdeci">virtual IType Get() const =0</div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a37fa39012e90d568df7f774cd6d1e956"><div class="ttname"><a href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t&lt; std::is_unsigned&lt; Source &gt;::value &amp;&amp;std::is_unsigned&lt; Dest &gt;::value, Dest &gt; numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00033">NumericCast.hpp:33</a></div></div>
+<div class="ttc" id="_mean_8hpp_xhtml"><div class="ttname"><a href="_mean_8hpp.xhtml">Mean.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a165ae372a7f67cad64ef3395d30122ce"><div class="ttname"><a href="namespacearmnn.xhtml#a165ae372a7f67cad64ef3395d30122ce">armnn::Mean</a></div><div class="ttdeci">void Mean(const armnn::TensorInfo &amp;inputInfo, const armnn::TensorInfo &amp;outputInfo, const std::vector&lt; unsigned int &gt; &amp;axis, Decoder&lt; float &gt; &amp;input, Encoder&lt; float &gt; &amp;output)</div><div class="ttdef"><b>Definition:</b> <a href="backends_2reference_2workloads_2_mean_8cpp_source.xhtml#l00071">Mean.cpp:71</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00092">Tensor.hpp:92</a></div></div>
+<div class="ttc" id="classarmnn_1_1_decoder_xhtml"><div class="ttname"><a href="classarmnn_1_1_decoder.xhtml">armnn::Decoder&lt; float &gt;</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_efae4012d0e357ebeaba7d02491d70e5.xhtml">reference</a></li><li class="navelem"><a class="el" href="dir_d2f3b8e2e64df3181ebe92efcc0a3012.xhtml">workloads</a></li><li class="navelem"><a class="el" href="backends_2reference_2workloads_2_mean_8cpp.xhtml">Mean.cpp</a></li>
+    <li class="footer">Generated on Fri Mar 13 2020 16:09:10 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>