blob: ed23f5f32eaafa54387c0e6f684d9f6eb0d0fee2 [file] [log] [blame]
<!-- HTML header for doxygen 1.8.15-->
<!-- Remember to use version doxygen 1.8.15 +-->
<!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 1.8.15"/>
<meta name="robots" content="NOINDEX, NOFOLLOW" /> <!-- Prevent indexing by search engines -->
<title>Compute Library: NEReduceMean Class Reference</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">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
$(document).ready(initResizable);
/* @license-end */</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" async="async" 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="Compute Library" src="https://raw.githubusercontent.com/ARM-software/ComputeLibrary/gh-pages/ACL_logo.png" style="max-width: 100%;margin-top: 15px;margin-left: 10px"/>
<td style="padding-left: 0.5em;">
<div id="projectname">
&#160;<span id="projectnumber">19.08</span>
</div>
</td>
</tr>
</tbody>
</table>
</div>
<!-- end header part -->
<!-- Generated by Doxygen 1.8.15 -->
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
var searchBox = new SearchBox("searchBox", "search",false,'Search');
/* @license-end */
</script>
<script type="text/javascript" src="menudata.js"></script>
<script type="text/javascript" src="menu.js"></script>
<script type="text/javascript">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
$(function() {
initMenu('',true,false,'search.php','Search');
$(document).ready(function() { init_search(); });
});
/* @license-end */</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">
/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&amp;dn=gpl-2.0.txt GPL-v2 */
$(document).ready(function(){initNavTree('classarm__compute_1_1_n_e_reduce_mean.xhtml','');});
/* @license-end */
</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="summary">
<a href="#pub-methods">Public Member Functions</a> &#124;
<a href="#pub-static-methods">Static Public Member Functions</a> </div>
<div class="headertitle">
<div class="title">NEReduceMean Class Reference</div> </div>
</div><!--header-->
<div class="contents">
<p>Basic function to perform reduce operation.
<a href="classarm__compute_1_1_n_e_reduce_mean.xhtml#details">More...</a></p>
<p><code>#include &lt;<a class="el" href="_n_e_reduce_mean_8h_source.xhtml">NEReduceMean.h</a>&gt;</code></p>
<div class="dynheader">
Collaboration diagram for NEReduceMean:</div>
<div class="dyncontent">
<div class="center"><iframe scrolling="no" frameborder="0" src="classarm__compute_1_1_n_e_reduce_mean__coll__graph.svg" width="132" height="112"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe>
</div>
<center><span class="legend">[<a target="top" href="graph_legend.xhtml">legend</a>]</span></center></div>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:a1f208adec0739b6ce732abb5cc8e5a58"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#a1f208adec0739b6ce732abb5cc8e5a58">NEReduceMean</a> (std::shared_ptr&lt; <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> &gt; memory_manager=nullptr)</td></tr>
<tr class="memdesc:a1f208adec0739b6ce732abb5cc8e5a58"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor. <a href="#a1f208adec0739b6ce732abb5cc8e5a58">More...</a><br /></td></tr>
<tr class="separator:a1f208adec0739b6ce732abb5cc8e5a58"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac741a3edd9fdd407099870bbb27925d7"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#ac741a3edd9fdd407099870bbb27925d7">configure</a> (<a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input, const <a class="el" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp;reduction_axis, bool keep_dims, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output)</td></tr>
<tr class="memdesc:ac741a3edd9fdd407099870bbb27925d7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Configure kernel. <a href="#ac741a3edd9fdd407099870bbb27925d7">More...</a><br /></td></tr>
<tr class="separator:ac741a3edd9fdd407099870bbb27925d7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad1717410afd0be936c6213a63c8005fb"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a> () override</td></tr>
<tr class="memdesc:ad1717410afd0be936c6213a63c8005fb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Run the kernels contained in the function. <a href="#ad1717410afd0be936c6213a63c8005fb">More...</a><br /></td></tr>
<tr class="separator:ad1717410afd0be936c6213a63c8005fb"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classarm__compute_1_1_i_function"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarm__compute_1_1_i_function')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarm__compute_1_1_i_function.xhtml">IFunction</a></td></tr>
<tr class="memitem:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">~IFunction</a> ()=default</td></tr>
<tr class="memdesc:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destructor. <a href="classarm__compute_1_1_i_function.xhtml#ab921ecc3f3f6ae2b4bd61f3e1998d8c4">More...</a><br /></td></tr>
<tr class="separator:ab921ecc3f3f6ae2b4bd61f3e1998d8c4 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">prepare</a> ()</td></tr>
<tr class="memdesc:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="mdescLeft">&#160;</td><td class="mdescRight">Prepare the function for executing. <a href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26">More...</a><br /></td></tr>
<tr class="separator:a820f7291c24155a2980512fae45aac26 inherit pub_methods_classarm__compute_1_1_i_function"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
Static Public Member Functions</h2></td></tr>
<tr class="memitem:a4399d123b93fac32d66025caa251cdfe"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classarm__compute_1_1_status.xhtml">Status</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1_n_e_reduce_mean.xhtml#a4399d123b93fac32d66025caa251cdfe">validate</a> (const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input, const <a class="el" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp;reduction_axis, bool keep_dims, const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output)</td></tr>
<tr class="memdesc:a4399d123b93fac32d66025caa251cdfe"><td class="mdescLeft">&#160;</td><td class="mdescRight">Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_n_e_reduce_mean.xhtml">NEReduceMean</a>. <a href="#a4399d123b93fac32d66025caa251cdfe">More...</a><br /></td></tr>
<tr class="separator:a4399d123b93fac32d66025caa251cdfe"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Basic function to perform reduce operation. </p>
<p class="definition">Definition at line <a class="el" href="_n_e_reduce_mean_8h_source.xhtml#l00040">40</a> of file <a class="el" href="_n_e_reduce_mean_8h_source.xhtml">NEReduceMean.h</a>.</p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="a1f208adec0739b6ce732abb5cc8e5a58"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a1f208adec0739b6ce732abb5cc8e5a58">&#9670;&nbsp;</a></span>NEReduceMean()</h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname"><a class="el" href="classarm__compute_1_1_n_e_reduce_mean.xhtml">NEReduceMean</a> </td>
<td>(</td>
<td class="paramtype">std::shared_ptr&lt; <a class="el" href="classarm__compute_1_1_i_memory_manager.xhtml">IMemoryManager</a> &gt;&#160;</td>
<td class="paramname"><em>memory_manager</em> = <code>nullptr</code></td><td>)</td>
<td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Constructor. </p>
<p class="definition">Definition at line <a class="el" href="_n_e_reduce_mean_8cpp_source.xhtml#l00032">32</a> of file <a class="el" href="_n_e_reduce_mean_8cpp_source.xhtml">NEReduceMean.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; : _memory_group(std::move(memory_manager)), _reduction_kernels(), _reduced_outs(), _reshape(), _reduction_ops(), _keep_dims()</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><!-- fragment -->
</div>
</div>
<h2 class="groupheader">Member Function Documentation</h2>
<a id="ac741a3edd9fdd407099870bbb27925d7"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ac741a3edd9fdd407099870bbb27925d7">&#9670;&nbsp;</a></span>configure()</h2>
<div class="memitem">
<div class="memproto">
<table class="memname">
<tr>
<td class="memname">void configure </td>
<td>(</td>
<td class="paramtype"><a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *&#160;</td>
<td class="paramname"><em>input</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp;&#160;</td>
<td class="paramname"><em>reduction_axis</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">bool&#160;</td>
<td class="paramname"><em>keep_dims</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype"><a class="el" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *&#160;</td>
<td class="paramname"><em>output</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</div><div class="memdoc">
<p>Configure kernel. </p>
<dl class="section note"><dt>Note</dt><dd>Supported tensor rank: up to 4</dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Source tensor. Data type supported: QASYMM8/F16/F32 </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">reduction_axis</td><td>Reduction axis vector. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">keep_dims</td><td>If positive, retains reduced dimensions with length 1. </td></tr>
<tr><td class="paramdir">[out]</td><td class="paramname">output</td><td>Destination tensor. Data type supported: Same as <code>input</code> </td></tr>
</table>
</dd>
</dl>
<p class="definition">Definition at line <a class="el" href="_n_e_reduce_mean_8cpp_source.xhtml#l00080">80</a> of file <a class="el" href="_n_e_reduce_mean_8cpp_source.xhtml">NEReduceMean.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160;{</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(input);</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; _reduction_ops = reduction_axis.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>();</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; _reduction_kernels.resize(_reduction_ops);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; _reduced_outs.resize(_reduction_ops - (keep_dims ? 1 : 0));</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; _keep_dims = keep_dims;</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; <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> axis_local = reduction_axis;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> input_dims = input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>();</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> reduction_ops = reduction_axis.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>();</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160;</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="comment">// Convert negative axis</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; reduction_ops; ++i)</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; {</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; axis_local[i] = <a class="code" href="namespacearm__compute.xhtml#aeb6881009f40f57d430752441ec5c4f4">wrap_around</a>(axis_local[i], input_dims);</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">// Perform reduction for every axis</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; _reduction_ops; ++i)</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="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> out_shape = i == 0 ? input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>() : (&amp;_reduced_outs[i - 1])-&gt;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>()-&gt;tensor_shape();</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; out_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">set</a>(axis_local[i], 1);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keyword">auto</span> in = (i == 0) ? input : (&amp;_reduced_outs[i - 1]);</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; <span class="keywordflow">if</span>(i == _reduction_ops - 1 &amp;&amp; keep_dims)</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; _reduction_kernels[i].configure(in, output, axis_local[i], <a class="code" href="namespacearm__compute.xhtml#a5827eb9cb394e74af87f74bd354fb45bafc54513dae613e117ffc4169e48bfce5">ReductionOperation::MEAN_SUM</a>);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; }</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keywordflow">else</span></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; _reduced_outs[i].allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(out_shape, input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#ad7829ae79223ab87f9da4c0bd7d229ba">num_channels</a>(), input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>(), input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>()));</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; _memory_group.<a class="code" href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">manage</a>(&amp;_reduced_outs[i]);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; _reduction_kernels[i].configure(in, &amp;_reduced_outs[i], axis_local[i], <a class="code" href="namespacearm__compute.xhtml#a5827eb9cb394e74af87f74bd354fb45bafc54513dae613e117ffc4169e48bfce5">ReductionOperation::MEAN_SUM</a>);</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; }</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; <span class="comment">// Allocate intermediate tensors</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; _reduction_ops - (keep_dims ? 1 : 0); ++i)</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; _reduced_outs[i].allocator()-&gt;allocate();</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; }</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; <span class="comment">// Configure reshape layer if we want to drop the dimensions</span></div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <span class="keywordflow">if</span>(!keep_dims)</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; {</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> out_shape = input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>();</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160;</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <span class="comment">// We have to sort the reduction axis vectors in order for remove_dimension</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <span class="comment">// to work properly</span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; std::sort(axis_local.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">begin</a>(), axis_local.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">begin</a>() + _reduction_ops);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; _reduction_ops; ++i)</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; {</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; out_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#acb74edf42335de0dca0da5158b704c4b">remove_dimension</a>(axis_local[i] - i);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; }</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()-&gt;set_tensor_shape(out_shape));</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; _reshape.<a class="code" href="classarm__compute_1_1_n_e_reshape_layer.xhtml#a83a344e60eb7db895953a942abf16628">configure</a>(&amp;_reduced_outs[_reduction_ops - 1], output);</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; }</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a1f4e725b8e1ea36b30e09dc08ae6961d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">arm_compute::ITensorInfo::num_dimensions</a></div><div class="ttdeci">virtual size_t num_dimensions() const =0</div><div class="ttdoc">The number of dimensions of the tensor (rank)</div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_acb74edf42335de0dca0da5158b704c4b"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#acb74edf42335de0dca0da5158b704c4b">arm_compute::TensorShape::remove_dimension</a></div><div class="ttdeci">void remove_dimension(size_t n)</div><div class="ttdoc">Accessor to remove the dimension n from the tensor shape.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00110">TensorShape.h:110</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor.</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a47be6fa38308d0003c25b60b7dbc45ce"><div class="ttname"><a href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">arm_compute::auto_init_if_empty</a></div><div class="ttdeci">bool auto_init_if_empty(ITensorInfo &amp;info, const TensorShape &amp;shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())</div><div class="ttdoc">Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00201">Helpers.inl:201</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_aeb6881009f40f57d430752441ec5c4f4"><div class="ttname"><a href="namespacearm__compute.xhtml#aeb6881009f40f57d430752441ec5c4f4">arm_compute::wrap_around</a></div><div class="ttdeci">T wrap_around(T x, T m)</div><div class="ttdoc">Wrap-around a number within the range 0 &lt;= x &lt; m.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00764">Helpers.h:764</a></div></div>
<div class="ttc" id="classarm__compute_1_1_memory_group_base_xhtml_ac1f67376afb7822f262a0174ef4a3104"><div class="ttname"><a href="classarm__compute_1_1_memory_group_base.xhtml#ac1f67376afb7822f262a0174ef4a3104">arm_compute::MemoryGroupBase::manage</a></div><div class="ttdeci">void manage(TensorType *obj)</div><div class="ttdoc">Sets a object to be managed by the given memory group.</div><div class="ttdef"><b>Definition:</b> <a href="_memory_group_base_8h_source.xhtml#l00102">MemoryGroupBase.h:102</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape &amp; tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor.</div></div>
<div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item.</div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
<div class="ttc" id="classarm__compute_1_1misc_1_1_i_cloneable_xhtml_a4d10e5012a872e7f78f2b539b673049d"><div class="ttname"><a href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">arm_compute::misc::ICloneable::clone</a></div><div class="ttdeci">virtual std::unique_ptr&lt; T &gt; clone() const =0</div><div class="ttdoc">Provide a clone of the current object of class T.</div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_ab2878b67ca384a699c1270900b31290b"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">arm_compute::Dimensions::begin</a></div><div class="ttdeci">std::array&lt; T, num_max_dimensions &gt;::iterator begin()</div><div class="ttdoc">Returns a read/write iterator that points to the first element in the dimension array.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00194">Dimensions.h:194</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a3f3e1a3200223e6a304a533b1016e749"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">arm_compute::ITensorInfo::quantization_info</a></div><div class="ttdeci">virtual QuantizationInfo quantization_info() const =0</div><div class="ttdoc">Get the quantization settings (scale and offset) of the tensor.</div></div>
<div class="ttc" id="_validate_8h_xhtml_a921b705e9e3e0fe928928447869e62a5"><div class="ttname"><a href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00161">Validate.h:161</a></div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a80a5f2d6e3a697c9aad893a3b4242615"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">arm_compute::Dimensions::num_dimensions</a></div><div class="ttdeci">unsigned int num_dimensions() const</div><div class="ttdoc">Returns the effective dimensionality of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00122">Dimensions.h:122</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a5827eb9cb394e74af87f74bd354fb45bafc54513dae613e117ffc4169e48bfce5"><div class="ttname"><a href="namespacearm__compute.xhtml#a5827eb9cb394e74af87f74bd354fb45bafc54513dae613e117ffc4169e48bfce5">arm_compute::ReductionOperation::MEAN_SUM</a></div><div class="ttdoc">Mean of sum.</div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_reshape_layer_xhtml_a83a344e60eb7db895953a942abf16628"><div class="ttname"><a href="classarm__compute_1_1_n_e_reshape_layer.xhtml#a83a344e60eb7db895953a942abf16628">arm_compute::NEReshapeLayer::configure</a></div><div class="ttdeci">void configure(const ITensor *input, ITensor *output)</div><div class="ttdoc">Initialise the kernel's inputs and outputs.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_reshape_layer_8cpp_source.xhtml#l00034">NEReshapeLayer.cpp:34</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_a9c54fb6cea3557692fe7c00c40bb40ad"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">arm_compute::TensorShape::set</a></div><div class="ttdeci">TensorShape &amp; set(size_t dimension, size_t value, bool apply_dim_correction=true)</div><div class="ttdoc">Accessor to set the value of one of the dimensions.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00078">TensorShape.h:78</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a4f4125dba5283887b34f889b1c615c0c"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">arm_compute::test::validation::info</a></div><div class="ttdeci">info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_ad7829ae79223ab87f9da4c0bd7d229ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#ad7829ae79223ab87f9da4c0bd7d229ba">arm_compute::ITensorInfo::num_channels</a></div><div class="ttdeci">virtual size_t num_channels() const =0</div><div class="ttdoc">The number of channels for each tensor element.</div></div>
</div><!-- fragment -->
<p class="reference">References <a class="el" href="_validate_8h_source.xhtml#l00161">ARM_COMPUTE_ERROR_ON_NULLPTR</a>, <a class="el" href="_helpers_8inl_source.xhtml#l00201">arm_compute::auto_init_if_empty()</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00194">Dimensions&lt; T &gt;::begin()</a>, <a class="el" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">ICloneable&lt; T &gt;::clone()</a>, <a class="el" href="_n_e_reshape_layer_8cpp_source.xhtml#l00034">NEReshapeLayer::configure()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">ITensorInfo::data_type()</a>, <a class="el" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">ITensor::info()</a>, <a class="el" href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">arm_compute::test::validation::info</a>, <a class="el" href="_memory_group_base_8h_source.xhtml#l00102">MemoryGroupBase&lt; TensorType &gt;::manage()</a>, <a class="el" href="namespacearm__compute.xhtml#a5827eb9cb394e74af87f74bd354fb45bafc54513dae613e117ffc4169e48bfce5">arm_compute::MEAN_SUM</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#ad7829ae79223ab87f9da4c0bd7d229ba">ITensorInfo::num_channels()</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00122">Dimensions&lt; T &gt;::num_dimensions()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">ITensorInfo::num_dimensions()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">ITensorInfo::quantization_info()</a>, <a class="el" href="_tensor_shape_8h_source.xhtml#l00110">TensorShape::remove_dimension()</a>, <a class="el" href="_tensor_shape_8h_source.xhtml#l00078">TensorShape::set()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">ITensorInfo::tensor_shape()</a>, and <a class="el" href="arm__compute_2core_2_helpers_8h_source.xhtml#l00764">arm_compute::wrap_around()</a>.</p>
</div>
</div>
<a id="ad1717410afd0be936c6213a63c8005fb"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad1717410afd0be936c6213a63c8005fb">&#9670;&nbsp;</a></span>run()</h2>
<div class="memitem">
<div class="memproto">
<table class="mlabels">
<tr>
<td class="mlabels-left">
<table class="memname">
<tr>
<td class="memname">void run </td>
<td>(</td>
<td class="paramname"></td><td>)</td>
<td></td>
</tr>
</table>
</td>
<td class="mlabels-right">
<span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </td>
</tr>
</table>
</div><div class="memdoc">
<p>Run the kernels contained in the function. </p>
<p>For NEON kernels:</p><ul>
<li>Multi-threading is used for the kernels which are parallelisable.</li>
<li>By default std::thread::hardware_concurrency() threads are used.</li>
</ul>
<dl class="section note"><dt>Note</dt><dd><a class="el" href="classarm__compute_1_1_c_p_p_scheduler.xhtml#ae64eebaa07f4d2da6cc2ba538c3cb095">CPPScheduler::set_num_threads()</a> can be used to manually set the number of threads</dd></dl>
<p>For OpenCL kernels:</p><ul>
<li>All the kernels are enqueued on the queue associated with <a class="el" href="classarm__compute_1_1_c_l_scheduler.xhtml" title="Provides global access to a CL context and command queue.">CLScheduler</a>.</li>
<li>The queue is then flushed.</li>
</ul>
<dl class="section note"><dt>Note</dt><dd>The function will not block until the kernels are executed. It is the user's responsibility to wait. </dd>
<dd>
Will call <a class="el" href="classarm__compute_1_1_i_function.xhtml#a820f7291c24155a2980512fae45aac26" title="Prepare the function for executing.">prepare()</a> on first run if hasn't been done </dd></dl>
<p>Implements <a class="el" href="classarm__compute_1_1_i_function.xhtml#a18954417d3124a8095783ea13dc6d00b">IFunction</a>.</p>
<p class="definition">Definition at line <a class="el" href="_n_e_reduce_mean_8cpp_source.xhtml#l00141">141</a> of file <a class="el" href="_n_e_reduce_mean_8cpp_source.xhtml">NEReduceMean.cpp</a>.</p>
<div class="fragment"><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; <a class="code" href="classarm__compute_1_1_memory_group_resource_scope.xhtml">MemoryGroupResourceScope</a> scope_mg(_memory_group);</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; _reduction_ops; ++i)</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; {</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; _reduction_kernels[i].run();</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; }</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="keywordflow">if</span>(!_keep_dims)</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; {</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; _reshape.<a class="code" href="classarm__compute_1_1_i_n_e_simple_function_no_border.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; }</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_i_n_e_simple_function_no_border_xhtml_a92fe532c342ae2b07956a65520c05362"><div class="ttname"><a href="classarm__compute_1_1_i_n_e_simple_function_no_border.xhtml#a92fe532c342ae2b07956a65520c05362">arm_compute::INESimpleFunctionNoBorder::run</a></div><div class="ttdeci">void run() override final</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_i_n_e_simple_function_no_border_8cpp_source.xhtml#l00035">INESimpleFunctionNoBorder.cpp:35</a></div></div>
<div class="ttc" id="classarm__compute_1_1_memory_group_resource_scope_xhtml"><div class="ttname"><a href="classarm__compute_1_1_memory_group_resource_scope.xhtml">arm_compute::MemoryGroupResourceScope</a></div><div class="ttdoc">Memory group resources scope handling class.</div><div class="ttdef"><b>Definition:</b> <a href="_i_memory_group_8h_source.xhtml#l00046">IMemoryGroup.h:46</a></div></div>
</div><!-- fragment -->
<p class="reference">References <a class="el" href="_i_n_e_simple_function_no_border_8cpp_source.xhtml#l00035">INESimpleFunctionNoBorder::run()</a>.</p>
</div>
</div>
<a id="a4399d123b93fac32d66025caa251cdfe"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a4399d123b93fac32d66025caa251cdfe">&#9670;&nbsp;</a></span>validate()</h2>
<div class="memitem">
<div class="memproto">
<table class="mlabels">
<tr>
<td class="mlabels-left">
<table class="memname">
<tr>
<td class="memname"><a class="el" href="classarm__compute_1_1_status.xhtml">Status</a> validate </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *&#160;</td>
<td class="paramname"><em>input</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp;&#160;</td>
<td class="paramname"><em>reduction_axis</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">bool&#160;</td>
<td class="paramname"><em>keep_dims</em>, </td>
</tr>
<tr>
<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *&#160;</td>
<td class="paramname"><em>output</em>&#160;</td>
</tr>
<tr>
<td></td>
<td>)</td>
<td></td><td></td>
</tr>
</table>
</td>
<td class="mlabels-right">
<span class="mlabels"><span class="mlabel">static</span></span> </td>
</tr>
</table>
</div><div class="memdoc">
<p>Static function to check if given info will lead to a valid configuration of <a class="el" href="classarm__compute_1_1_n_e_reduce_mean.xhtml">NEReduceMean</a>. </p>
<dl class="params"><dt>Parameters</dt><dd>
<table class="params">
<tr><td class="paramdir">[in]</td><td class="paramname">input</td><td>Source tensor. Data type supported: QASYMM8/F16/F32 </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">reduction_axis</td><td>Reduction axis vector. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">keep_dims</td><td>If positive, retains reduced dimensions with length 1. </td></tr>
<tr><td class="paramdir">[in]</td><td class="paramname">output</td><td>Destination tensor. Data type supported: Same as <code>input</code> </td></tr>
</table>
</dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>A status </dd></dl>
<p class="definition">Definition at line <a class="el" href="_n_e_reduce_mean_8cpp_source.xhtml#l00037">37</a> of file <a class="el" href="_n_e_reduce_mean_8cpp_source.xhtml">NEReduceMean.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;{</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(keep_dims);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>(input);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <a class="code" href="_c_p_p_2_validate_8h.xhtml#ad2633f3560322e1f8d926949dec1b730">ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED</a>(input);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(input, 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(reduction_axis.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>() &gt; input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>());</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; <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> out_shape = input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>();</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> reduction_ops = reduction_axis.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>();</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> input_dims = input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>();</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> axis_local = reduction_axis;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="comment">// Convert negative axis</span></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> i = 0; i &lt; reduction_ops; ++i)</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; axis_local[i] = <a class="code" href="namespacearm__compute.xhtml#aeb6881009f40f57d430752441ec5c4f4">wrap_around</a>(axis_local[i], input_dims);</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;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; std::sort(axis_local.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">begin</a>(), axis_local.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">begin</a>() + reduction_ops);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; reduction_ops; ++i)</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; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(axis_local[i] &gt; 3);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(static_cast&lt;unsigned int&gt;(axis_local[i]) &gt; input-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() - 1);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <span class="keywordflow">if</span>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>() &gt; 0 &amp;&amp; keep_dims)</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; {</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(output-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(axis_local[i]) != 1);</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">if</span>(keep_dims)</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; out_shape.set(axis_local[i], 1);</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="keywordflow">else</span></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; out_shape.remove_dimension(axis_local[i] - i);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; }</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; }</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> out_info = input-&gt;<a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()-&gt;set_tensor_shape(out_shape);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <a class="code" href="_validate_8h.xhtml#a27e4638546c88b8916f967e6e54480a9">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES</a>(output, &amp;out_info);</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; <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a1f4e725b8e1ea36b30e09dc08ae6961d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">arm_compute::ITensorInfo::num_dimensions</a></div><div class="ttdeci">virtual size_t num_dimensions() const =0</div><div class="ttdoc">The number of dimensions of the tensor (rank)</div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a178f0d3d87f959e00a743328d95359d2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">arm_compute::ITensorInfo::dimension</a></div><div class="ttdeci">virtual size_t dimension(size_t index) const =0</div><div class="ttdoc">Return the size of the requested dimension.</div></div>
<div class="ttc" id="_validate_8h_xhtml_ae7eed178dac535c6e727061b1f5bc6eb"><div class="ttname"><a href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00791">Validate.h:791</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel</div></div>
<div class="ttc" id="classarm__compute_1_1_status_xhtml"><div class="ttname"><a href="classarm__compute_1_1_status.xhtml">arm_compute::Status</a></div><div class="ttdoc">Status class.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00052">Error.h:52</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a206d6e247e0957ac3dee45d27756fc25"><div class="ttname"><a href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00244">Error.h:244</a></div></div>
<div class="ttc" id="_c_p_p_2_validate_8h_xhtml_ad2633f3560322e1f8d926949dec1b730"><div class="ttname"><a href="_c_p_p_2_validate_8h.xhtml#ad2633f3560322e1f8d926949dec1b730">ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(tensor)</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_2_validate_8h_source.xhtml#l00071">Validate.h:71</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_aeb6881009f40f57d430752441ec5c4f4"><div class="ttname"><a href="namespacearm__compute.xhtml#aeb6881009f40f57d430752441ec5c4f4">arm_compute::wrap_around</a></div><div class="ttdeci">T wrap_around(T x, T m)</div><div class="ttdoc">Wrap-around a number within the range 0 &lt;= x &lt; m.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00764">Helpers.h:764</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00160">Error.h:160</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_a27e4638546c88b8916f967e6e54480a9"><div class="ttname"><a href="_validate_8h.xhtml#a27e4638546c88b8916f967e6e54480a9">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00443">Validate.h:443</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape &amp; tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor.</div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::DataType::QASYMM8</a></div><div class="ttdoc">quantized, asymmetric fixed-point 8-bit number</div></div>
<div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item.</div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
<div class="ttc" id="classarm__compute_1_1misc_1_1_i_cloneable_xhtml_a4d10e5012a872e7f78f2b539b673049d"><div class="ttname"><a href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">arm_compute::misc::ICloneable::clone</a></div><div class="ttdeci">virtual std::unique_ptr&lt; T &gt; clone() const =0</div><div class="ttdoc">Provide a clone of the current object of class T.</div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_ab2878b67ca384a699c1270900b31290b"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#ab2878b67ca384a699c1270900b31290b">arm_compute::Dimensions::begin</a></div><div class="ttdeci">std::array&lt; T, num_max_dimensions &gt;::iterator begin()</div><div class="ttdoc">Returns a read/write iterator that points to the first element in the dimension array.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00194">Dimensions.h:194</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_aff911654521523937ff24372a870b89f"><div class="ttname"><a href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00163">Validate.h:163</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a18064e0011c3869d884653e9e7c47b66"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">arm_compute::ITensorInfo::total_size</a></div><div class="ttdeci">virtual size_t total_size() const =0</div><div class="ttdoc">Returns the total size of the tensor in bytes.</div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a80a5f2d6e3a697c9aad893a3b4242615"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">arm_compute::Dimensions::num_dimensions</a></div><div class="ttdeci">unsigned int num_dimensions() const</div><div class="ttdoc">Returns the effective dimensionality of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00122">Dimensions.h:122</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div>
</div><!-- fragment -->
<p class="reference">References <a class="el" href="_error_8h_source.xhtml#l00244">ARM_COMPUTE_RETURN_ERROR_ON</a>, <a class="el" href="_c_p_p_2_validate_8h_source.xhtml#l00071">ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED</a>, <a class="el" href="_validate_8h_source.xhtml#l00791">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>, <a class="el" href="_validate_8h_source.xhtml#l00443">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES</a>, <a class="el" href="_validate_8h_source.xhtml#l00163">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>, <a class="el" href="_error_8h_source.xhtml#l00160">ARM_COMPUTE_UNUSED</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00194">Dimensions&lt; T &gt;::begin()</a>, <a class="el" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">ICloneable&lt; T &gt;::clone()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">ITensorInfo::dimension()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::F16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="_dimensions_8h_source.xhtml#l00122">Dimensions&lt; T &gt;::num_dimensions()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">ITensorInfo::num_dimensions()</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::QASYMM8</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">ITensorInfo::tensor_shape()</a>, <a class="el" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">ITensorInfo::total_size()</a>, and <a class="el" href="arm__compute_2core_2_helpers_8h_source.xhtml#l00764">arm_compute::wrap_around()</a>.</p>
</div>
</div>
<hr/>The documentation for this class was generated from the following files:<ul>
<li>arm_compute/runtime/NEON/functions/<a class="el" href="_n_e_reduce_mean_8h_source.xhtml">NEReduceMean.h</a></li>
<li>src/runtime/NEON/functions/<a class="el" href="_n_e_reduce_mean_8cpp_source.xhtml">NEReduceMean.cpp</a></li>
</ul>
</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="namespacearm__compute.xhtml">arm_compute</a></li><li class="navelem"><a class="el" href="classarm__compute_1_1_n_e_reduce_mean.xhtml">NEReduceMean</a></li>
<li class="footer">Generated on Mon Sep 2 2019 11:47:38 for Compute Library by
<a href="http://www.doxygen.org/index.html">
<img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.15 </li>
</ul>
</div>
</body>
</html>