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<a href="#pub-methods">Public Member Functions</a> &#124;
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<div class="title">RefL2NormalizationWorkload Class Reference</div> </div>
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<p><code>#include &lt;<a class="el" href="_ref_l2_normalization_workload_8hpp_source.html">RefL2NormalizationWorkload.hpp</a>&gt;</code></p>
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Inheritance diagram for RefL2NormalizationWorkload:</div>
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<img src="classarmnn_1_1_ref_l2_normalization_workload.png" usemap="#RefL2NormalizationWorkload_map" alt=""/>
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<area href="classarmnn_1_1_base_workload.html" alt="BaseWorkload&lt; L2NormalizationQueueDescriptor &gt;" shape="rect" coords="0,56,304,80"/>
<area href="classarmnn_1_1_i_workload.html" title="Workload interface to enqueue a layer computation. " alt="IWorkload" shape="rect" coords="0,0,304,24"/>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:a722973639581b632387fc8d36f106aca"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_ref_l2_normalization_workload.html#a722973639581b632387fc8d36f106aca">RefL2NormalizationWorkload</a> (const <a class="el" href="structarmnn_1_1_l2_normalization_queue_descriptor.html">L2NormalizationQueueDescriptor</a> &amp;descriptor, const <a class="el" href="structarmnn_1_1_workload_info.html">WorkloadInfo</a> &amp;<a class="el" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</td></tr>
<tr class="separator:a722973639581b632387fc8d36f106aca"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae071e8822437c78baea75c3aef3a263a"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_ref_l2_normalization_workload.html#ae071e8822437c78baea75c3aef3a263a">Execute</a> () const override</td></tr>
<tr class="separator:ae071e8822437c78baea75c3aef3a263a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classarmnn_1_1_base_workload"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarmnn_1_1_base_workload')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarmnn_1_1_base_workload.html">BaseWorkload&lt; L2NormalizationQueueDescriptor &gt;</a></td></tr>
<tr class="memitem:af2ef420610280dc5a661cd3d4836d5a2 inherit pub_methods_classarmnn_1_1_base_workload"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_base_workload.html#af2ef420610280dc5a661cd3d4836d5a2">BaseWorkload</a> (const <a class="el" href="structarmnn_1_1_l2_normalization_queue_descriptor.html">L2NormalizationQueueDescriptor</a> &amp;descriptor, const <a class="el" href="structarmnn_1_1_workload_info.html">WorkloadInfo</a> &amp;info)</td></tr>
<tr class="separator:af2ef420610280dc5a661cd3d4836d5a2 inherit pub_methods_classarmnn_1_1_base_workload"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a81627f96ba06d76e147f7d392a8117ed inherit pub_methods_classarmnn_1_1_base_workload"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_base_workload.html#a81627f96ba06d76e147f7d392a8117ed">PostAllocationConfigure</a> () override</td></tr>
<tr class="separator:a81627f96ba06d76e147f7d392a8117ed inherit pub_methods_classarmnn_1_1_base_workload"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a965cf380c7adf547d0f14b3f6d1da249 inherit pub_methods_classarmnn_1_1_base_workload"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="structarmnn_1_1_l2_normalization_queue_descriptor.html">L2NormalizationQueueDescriptor</a> &amp;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_base_workload.html#a965cf380c7adf547d0f14b3f6d1da249">GetData</a> () const</td></tr>
<tr class="separator:a965cf380c7adf547d0f14b3f6d1da249 inherit pub_methods_classarmnn_1_1_base_workload"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a29c2c6dd77c6fe10674fc6876751cbce inherit pub_methods_classarmnn_1_1_base_workload"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarmnn_1_1profiling_1_1_profiling_guid.html">profiling::ProfilingGuid</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_base_workload.html#a29c2c6dd77c6fe10674fc6876751cbce">GetGuid</a> () const final</td></tr>
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<tr class="inherit_header pub_methods_classarmnn_1_1_i_workload"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classarmnn_1_1_i_workload')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classarmnn_1_1_i_workload.html">IWorkload</a></td></tr>
<tr class="memitem:a69c83c02ae8de866bc7a46c49e69c1ba inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.html#a69c83c02ae8de866bc7a46c49e69c1ba">~IWorkload</a> ()</td></tr>
<tr class="separator:a69c83c02ae8de866bc7a46c49e69c1ba inherit pub_methods_classarmnn_1_1_i_workload"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab81312bd5e64cbae2803de9f243bdb32 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.html#ab81312bd5e64cbae2803de9f243bdb32">RegisterDebugCallback</a> (const <a class="el" href="namespacearmnn.html#a15f3ad9b5e4e3d46b0a6dda246a7bc28">DebugCallbackFunction</a> &amp;)</td></tr>
<tr class="separator:ab81312bd5e64cbae2803de9f243bdb32 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="inherited"></a>
Additional Inherited Members</h2></td></tr>
<tr class="inherit_header pro_attribs_classarmnn_1_1_base_workload"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classarmnn_1_1_base_workload')"><img src="closed.png" alt="-"/>&#160;Protected Attributes inherited from <a class="el" href="classarmnn_1_1_base_workload.html">BaseWorkload&lt; L2NormalizationQueueDescriptor &gt;</a></td></tr>
<tr class="memitem:a0a487c549c63319505095b855ea3c195 inherit pro_attribs_classarmnn_1_1_base_workload"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="structarmnn_1_1_l2_normalization_queue_descriptor.html">L2NormalizationQueueDescriptor</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">m_Data</a></td></tr>
<tr class="separator:a0a487c549c63319505095b855ea3c195 inherit pro_attribs_classarmnn_1_1_base_workload"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a902044db290170b8467ed4697b7fed24 inherit pro_attribs_classarmnn_1_1_base_workload"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classarmnn_1_1profiling_1_1_profiling_guid.html">profiling::ProfilingGuid</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_base_workload.html#a902044db290170b8467ed4697b7fed24">m_Guid</a></td></tr>
<tr class="separator:a902044db290170b8467ed4697b7fed24 inherit pro_attribs_classarmnn_1_1_base_workload"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock">
<p class="definition">Definition at line <a class="el" href="_ref_l2_normalization_workload_8hpp_source.html#l00014">14</a> of file <a class="el" href="_ref_l2_normalization_workload_8hpp_source.html">RefL2NormalizationWorkload.hpp</a>.</p>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="a722973639581b632387fc8d36f106aca"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a722973639581b632387fc8d36f106aca">&#9670;&nbsp;</a></span>RefL2NormalizationWorkload()</h2>
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<td class="memname"><a class="el" href="classarmnn_1_1_ref_l2_normalization_workload.html">RefL2NormalizationWorkload</a> </td>
<td>(</td>
<td class="paramtype">const <a class="el" href="structarmnn_1_1_l2_normalization_queue_descriptor.html">L2NormalizationQueueDescriptor</a> &amp;&#160;</td>
<td class="paramname"><em>descriptor</em>, </td>
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<td class="paramkey"></td>
<td></td>
<td class="paramtype">const <a class="el" href="structarmnn_1_1_workload_info.html">WorkloadInfo</a> &amp;&#160;</td>
<td class="paramname"><em>info</em>&#160;</td>
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<td>)</td>
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<span class="mlabels"><span class="mlabel">explicit</span></span> </td>
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<p class="definition">Definition at line <a class="el" href="_ref_l2_normalization_workload_8cpp_source.html#l00023">23</a> of file <a class="el" href="_ref_l2_normalization_workload_8cpp_source.html">RefL2NormalizationWorkload.cpp</a>.</p>
<div class="fragment"><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; : <a class="code" href="classarmnn_1_1_base_workload.html">BaseWorkload&lt;L2NormalizationQueueDescriptor&gt;</a>(descriptor, <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>) {}</div><div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_workload_html"><div class="ttname"><a href="classarmnn_1_1_base_workload.html">armnn::BaseWorkload&lt; L2NormalizationQueueDescriptor &gt;</a></div></div>
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<h2 class="groupheader">Member Function Documentation</h2>
<a id="ae071e8822437c78baea75c3aef3a263a"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ae071e8822437c78baea75c3aef3a263a">&#9670;&nbsp;</a></span>Execute()</h2>
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<td class="memname">void Execute </td>
<td>(</td>
<td class="paramname"></td><td>)</td>
<td> const</td>
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<span class="mlabels"><span class="mlabel">override</span><span class="mlabel">virtual</span></span> </td>
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</div><div class="memdoc">
<p>Implements <a class="el" href="classarmnn_1_1_i_workload.html#a72ae00e6604850c8798c5e0d825ee7e4">IWorkload</a>.</p>
<p class="definition">Definition at line <a class="el" href="_ref_l2_normalization_workload_8cpp_source.html#l00028">28</a> of file <a class="el" href="_ref_l2_normalization_workload_8cpp_source.html">RefL2NormalizationWorkload.cpp</a>.</p>
<p class="reference">References <a class="el" href="_profiling_8hpp_source.html#l00170">ARMNN_SCOPED_PROFILING_EVENT</a>, <a class="el" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::CpuRef</a>, <a class="el" href="_tensor_8hpp_source.html#l00043">TensorShape::GetNumDimensions()</a>, <a class="el" href="_ref_workload_utils_8hpp_source.html#l00025">armnn::GetTensorInfo()</a>, <a class="el" href="_workload_8hpp_source.html#l00046">BaseWorkload&lt; L2NormalizationQueueDescriptor &gt;::m_Data</a>, <a class="el" href="_descriptors_8hpp_source.html#l00606">L2NormalizationDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00604">L2NormalizationDescriptor::m_Eps</a>, <a class="el" href="_workload_data_8hpp_source.html#l00030">QueueDescriptor::m_Inputs</a>, <a class="el" href="_workload_data_8hpp_source.html#l00031">QueueDescriptor::m_Outputs</a>, and <a class="el" href="_workload_data_8hpp_source.html#l00049">QueueDescriptorWithParameters&lt; LayerDescriptor &gt;::m_Parameters</a>.</p>
<div class="fragment"><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;{</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <a class="code" href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a>(<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">Compute::CpuRef</a>, <span class="stringliteral">&quot;RefL2NormalizationWorkload_Execute&quot;</span>);</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; inputInfo = <a class="code" href="namespacearmnn.html#a93d269806f34407695dc10f510001c30">GetTensorInfo</a>(<a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0]);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; outputInfo = <a class="code" href="namespacearmnn.html#a93d269806f34407695dc10f510001c30">GetTensorInfo</a>(<a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]);</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; <span class="keyword">auto</span> inputDecoder = MakeDecoder&lt;float&gt;(inputInfo, <a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0]-&gt;Map());</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="keyword">auto</span> outputEncoder = MakeEncoder&lt;float&gt;(outputInfo, <a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]-&gt;Map());</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; <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">DataLayoutIndexed</a> dataLayout(<a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_l2_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; shape = inputInfo.GetShape();</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> paddedShapeArray[4];</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> idxShift = 4 - boost::numeric_cast&lt;<span class="keywordtype">int</span>&gt;(shape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batches = (idxShift == 0) ? shape[0] : 1;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; paddedShapeArray[0] = batches;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> channelsIdx = boost::numeric_cast&lt;<span class="keywordtype">int</span>&gt;(dataLayout.GetChannelsIndex());</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = (channelsIdx - idxShift &gt;= 0)</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; ? shape[boost::numeric_cast&lt;unsigned int&gt;(channelsIdx - idxShift)]</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; : 1;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; paddedShapeArray[channelsIdx] = channels;</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="keyword">const</span> <span class="keywordtype">int</span> heightIdx = boost::numeric_cast&lt;<span class="keywordtype">int</span>&gt;(dataLayout.GetHeightIndex());</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = (heightIdx - idxShift &gt;= 0)</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; ? shape[boost::numeric_cast&lt;unsigned int&gt;(heightIdx - idxShift)]</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; : 1;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; paddedShapeArray[heightIdx] = height;</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; <span class="keyword">const</span> <span class="keywordtype">int</span> widthIdx = boost::numeric_cast&lt;<span class="keywordtype">int</span>&gt;(dataLayout.GetWidthIndex());</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = (widthIdx - idxShift &gt;= 0)</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; ? shape[boost::numeric_cast&lt;unsigned int&gt;(widthIdx - idxShift)]</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; : 1;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; paddedShapeArray[widthIdx] = width;</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; paddedShape = <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>(4, paddedShapeArray);</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 0; n &lt; batches; ++n)</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">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> c = 0; c &lt; channels; ++c)</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; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> h = 0; h &lt; height; ++h)</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; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> w = 0; w &lt; width; ++w)</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; {</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="keywordtype">float</span> reduction = 0.0;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> d = 0; d &lt; channels; ++d)</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> inputIndex = dataLayout.GetIndex(paddedShape, n, d, h, w);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; (*inputDecoder)[inputIndex];</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <span class="keyword">const</span> <span class="keywordtype">float</span> value = inputDecoder-&gt;Get();</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; reduction += value * value;</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;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index = dataLayout.GetIndex(paddedShape, n, c, h, w);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160;</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="keywordtype">float</span> <a class="code" href="structarmnn_1_1maximum.html">maximum</a> = reduction &lt; <a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_l2_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">m_Eps</a> ? <a class="code" href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_l2_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">m_Eps</a> : reduction;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <span class="keyword">const</span> <span class="keywordtype">float</span> scale = 1.0f / sqrtf(maximum);</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; (*inputDecoder)[index];</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; (*outputEncoder)[index];</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; outputEncoder-&gt;Set(inputDecoder-&gt;Get() * scale);</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; }</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; }</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="ttc" id="_profiling_8hpp_html_a5ccc65e2c464ac05ce311fdae7ede03a"><div class="ttname"><a href="_profiling_8hpp.html#a5ccc65e2c464ac05ce311fdae7ede03a">ARMNN_SCOPED_PROFILING_EVENT</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.html#l00170">Profiling.hpp:170</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00043">Tensor.hpp:43</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_html_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00049">WorkloadData.hpp:49</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
<div class="ttc" id="structarmnn_1_1_l2_normalization_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::L2NormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00606">Descriptors.hpp:606</a></div></div>
<div class="ttc" id="classarmnn_1_1_base_workload_html_a0a487c549c63319505095b855ea3c195"><div class="ttname"><a href="classarmnn_1_1_base_workload.html#a0a487c549c63319505095b855ea3c195">armnn::BaseWorkload&lt; L2NormalizationQueueDescriptor &gt;::m_Data</a></div><div class="ttdeci">const L2NormalizationQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.html#l00046">Workload.hpp:46</a></div></div>
<div class="ttc" id="structarmnn_1_1maximum_html"><div class="ttname"><a href="structarmnn_1_1maximum.html">armnn::maximum</a></div><div class="ttdef"><b>Definition:</b> <a href="_maximum_8hpp_source.html#l00013">Maximum.hpp:13</a></div></div>
<div class="ttc" id="namespacearmnn_html_ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64"><div class="ttname"><a href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a></div><div class="ttdoc">CPU Execution: Reference C++ kernels. </div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_html_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00031">WorkloadData.hpp:31</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_html_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00030">WorkloadData.hpp:30</a></div></div>
<div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00017">DataLayoutIndexed.hpp:17</a></div></div>
<div class="ttc" id="namespacearmnn_html_a93d269806f34407695dc10f510001c30"><div class="ttname"><a href="namespacearmnn.html#a93d269806f34407695dc10f510001c30">armnn::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo(const ITensorHandle *tensorHandle)</div><div class="ttdoc">float32 helpers </div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_utils_8hpp_source.html#l00025">RefWorkloadUtils.hpp:25</a></div></div>
<div class="ttc" id="structarmnn_1_1_l2_normalization_descriptor_html_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">armnn::L2NormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Used to avoid dividing by zero. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00604">Descriptors.hpp:604</a></div></div>
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