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| author | David Monahan <david.monahan@arm.com> | 2023-03-22 16:48:58 +0000 |
|---|---|---|
| committer | David Monahan <david.monahan@arm.com> | 2023-03-22 16:48:58 +0000 |
| commit | ae050524109f1ce827962665436ef7430f2ac479 (patch) | |
| tree | a087fe0c77570971dd7979f2757426c24e91afc7 /23.02/classarmnn_1_1_neon_q_lstm_workload.xhtml | |
| parent | 8d2ca734165a068478df7cffa46185680b05cd20 (diff) | |
| download | armnn-ae050524109f1ce827962665436ef7430f2ac479.tar.gz | |
IVGCVSW-7255 Update Doxygen Documentation and publish on GitHub.
* Updating Doxygen documentation for 23.02 release.
Signed-off-by: David Monahan <david.monahan@arm.com>
Change-Id: I545574ff7664b4595d2fe6a91a3c35d2ad55df82
Diffstat (limited to '23.02/classarmnn_1_1_neon_q_lstm_workload.xhtml')
| -rw-r--r-- | 23.02/classarmnn_1_1_neon_q_lstm_workload.xhtml | 350 |
1 files changed, 289 insertions, 61 deletions
diff --git a/23.02/classarmnn_1_1_neon_q_lstm_workload.xhtml b/23.02/classarmnn_1_1_neon_q_lstm_workload.xhtml index b58546230e..4d3ea4ebef 100644 --- a/23.02/classarmnn_1_1_neon_q_lstm_workload.xhtml +++ b/23.02/classarmnn_1_1_neon_q_lstm_workload.xhtml @@ -8,7 +8,7 @@ <head> <meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> <meta http-equiv="X-UA-Compatible" content="IE=9"/> -<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="generator" content="Doxygen 1.8.17"/> <meta name="robots" content="NOINDEX, NOFOLLOW" /> <meta name="viewport" content="width=device-width, initial-scale=1"/> <title>ArmNN: NeonQLstmWorkload Class Reference</title> @@ -19,9 +19,6 @@ <script type="text/javascript" src="resize.js"></script> <script type="text/javascript" src="navtreedata.js"></script> <script type="text/javascript" src="navtree.js"></script> -<script type="text/javascript"> - $(document).ready(initResizable); -</script> <link href="search/search.css" rel="stylesheet" type="text/css"/> <script type="text/javascript" src="search/searchdata.js"></script> <script type="text/javascript" src="search/search.js"></script> @@ -30,7 +27,8 @@ extensions: ["tex2jax.js"], jax: ["input/TeX","output/HTML-CSS"], }); -</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +</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> @@ -51,18 +49,21 @@ </table> </div> <!-- end header part --> -<!-- Generated by Doxygen 1.8.13 --> +<!-- Generated by Doxygen 1.8.17 --> <script type="text/javascript"> +/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&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&dn=gpl-2.0.txt GPL-v2 */ $(function() { initMenu('',true,false,'search.php','Search'); $(document).ready(function() { init_search(); }); }); -</script> +/* @license-end */</script> <div id="main-nav"></div> </div><!-- top --> <div id="side-nav" class="ui-resizable side-nav-resizable"> @@ -76,7 +77,9 @@ $(function() { </div> </div> <script type="text/javascript"> -$(document).ready(function(){initNavTree('classarmnn_1_1_neon_q_lstm_workload.xhtml','');}); +/* @license magnet:?xt=urn:btih:cf05388f2679ee054f2beb29a391d25f4e673ac3&dn=gpl-2.0.txt GPL-v2 */ +$(document).ready(function(){initNavTree('classarmnn_1_1_neon_q_lstm_workload.xhtml',''); initResizable(); }); +/* @license-end */ </script> <div id="doc-content"> <!-- window showing the filter options --> @@ -111,13 +114,13 @@ Inheritance diagram for NeonQLstmWorkload:</div> <map id="NeonQLstmWorkload_map" name="NeonQLstmWorkload_map"> <area href="classarmnn_1_1_neon_base_workload.xhtml" alt="NeonBaseWorkload< QLstmQueueDescriptor >" shape="rect" coords="0,112,279,136"/> <area href="classarmnn_1_1_base_workload.xhtml" alt="BaseWorkload< QLstmQueueDescriptor >" shape="rect" coords="0,56,279,80"/> -<area href="classarmnn_1_1_i_workload.xhtml" title="Workload interface to enqueue a layer computation. " alt="IWorkload" shape="rect" coords="0,0,279,24"/> -</map> - </div></div> +<area href="classarmnn_1_1_i_workload.xhtml" title="Workload interface to enqueue a layer computation." alt="IWorkload" shape="rect" coords="0,0,279,24"/> + </map> +</div></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:a83c87b3dd014c18b6609c6fecf6c8368"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_neon_q_lstm_workload.xhtml#a83c87b3dd014c18b6609c6fecf6c8368">NeonQLstmWorkload</a> (const <a class="el" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml">QLstmQueueDescriptor</a> &descriptor, const <a class="el" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a> &<a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</td></tr> +<tr class="memitem:a83c87b3dd014c18b6609c6fecf6c8368"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_neon_q_lstm_workload.xhtml#a83c87b3dd014c18b6609c6fecf6c8368">NeonQLstmWorkload</a> (const <a class="el" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml">QLstmQueueDescriptor</a> &descriptor, const <a class="el" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a> &info)</td></tr> <tr class="separator:a83c87b3dd014c18b6609c6fecf6c8368"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ae071e8822437c78baea75c3aef3a263a"><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_neon_q_lstm_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">Execute</a> () const override</td></tr> <tr class="separator:ae071e8822437c78baea75c3aef3a263a"><td class="memSeparator" colspan="2"> </td></tr> @@ -144,6 +147,10 @@ Public Member Functions</h2></td></tr> <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="-"/> Public Member Functions inherited from <a class="el" href="classarmnn_1_1_i_workload.xhtml">IWorkload</a></td></tr> <tr class="memitem:a69c83c02ae8de866bc7a46c49e69c1ba inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.xhtml#a69c83c02ae8de866bc7a46c49e69c1ba">~IWorkload</a> ()</td></tr> <tr class="separator:a69c83c02ae8de866bc7a46c49e69c1ba inherit pub_methods_classarmnn_1_1_i_workload"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a00f887eb14b9ed163d795b31c4964965 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual arm::pipe::ProfilingGuid </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.xhtml#a00f887eb14b9ed163d795b31c4964965">GetGuid</a> () const =0</td></tr> +<tr class="separator:a00f887eb14b9ed163d795b31c4964965 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a9cc47a21a60b5e47247cde5e660e29ce inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual bool </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.xhtml#a9cc47a21a60b5e47247cde5e660e29ce">SupportsTensorHandleReplacement</a> () const =0</td></tr> +<tr class="separator:a9cc47a21a60b5e47247cde5e660e29ce inherit pub_methods_classarmnn_1_1_i_workload"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:ab81312bd5e64cbae2803de9f243bdb32 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.xhtml#ab81312bd5e64cbae2803de9f243bdb32">RegisterDebugCallback</a> (const <a class="el" href="namespacearmnn.xhtml#a15f3ad9b5e4e3d46b0a6dda246a7bc28">DebugCallbackFunction</a> &)</td></tr> <tr class="separator:ab81312bd5e64cbae2803de9f243bdb32 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memSeparator" colspan="2"> </td></tr> <tr class="memitem:a2d2834d1029217934f504e3e59579081 inherit pub_methods_classarmnn_1_1_i_workload"><td class="memItemLeft" align="right" valign="top">virtual <a class="el" href="classarmnn_1_1_optional.xhtml">armnn::Optional</a>< <a class="el" href="structarmnn_1_1_memory_requirements.xhtml">armnn::MemoryRequirements</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1_i_workload.xhtml#a2d2834d1029217934f504e3e59579081">GetMemoryRequirements</a> ()</td></tr> @@ -191,50 +198,227 @@ Additional Inherited Members</h2></td></tr> </div><div class="memdoc"> <p class="definition">Definition at line <a class="el" href="_neon_q_lstm_workload_8cpp_source.xhtml#l00017">17</a> of file <a class="el" href="_neon_q_lstm_workload_8cpp_source.xhtml">NeonQLstmWorkload.cpp</a>.</p> - -<p class="reference">References <a class="el" href="_profiling_8hpp_source.xhtml#l00227">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>, and <a class="el" href="_workload_data_8hpp_source.xhtml#l00066">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>.</p> -<div class="fragment"><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  : NeonBaseWorkload<QLstmQueueDescriptor>(descriptor, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> {</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="comment">// Report Profiling Details</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>(<span class="stringliteral">"NeonQLstmWorkload_Construct"</span>,</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  descriptor.m_Parameters,</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>,</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  this->GetGuid());</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  arm_compute::LSTMParams<arm_compute::ITensor> qLstmParams;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="comment">// Mandatory params</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  m_InputToForgetWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  BuildArmComputeTensor(*m_InputToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  m_InputToCellWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  BuildArmComputeTensor(*m_InputToCellWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  m_InputToOutputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  BuildArmComputeTensor(*m_InputToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> </div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  m_RecurrentToForgetWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  BuildArmComputeTensor(*m_RecurrentToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  m_RecurrentToCellWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  BuildArmComputeTensor(*m_RecurrentToCellWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  m_RecurrentToOutputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  BuildArmComputeTensor(*m_RecurrentToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  m_ForgetGateBiasTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  BuildArmComputeTensor(*m_ForgetGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  m_CellBiasTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  BuildArmComputeTensor(*m_CellBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> </div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  m_OutputGateBiasTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  BuildArmComputeTensor(*m_OutputGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">// Create tensors for optional params if they are enabled</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a>)</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  {</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  m_CellToInputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  {</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// In ACL this is categorised as a CIFG param and not a Peephole param</span></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  BuildArmComputeTensor(*m_CellToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">m_CellToInputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  }</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  m_CellToForgetWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  BuildArmComputeTensor(*m_CellToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">m_CellToForgetWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  m_CellToOutputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  BuildArmComputeTensor(*m_CellToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">m_CellToOutputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// Set Peephole params</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  qLstmParams.set_peephole_params(m_CellToForgetWeightsTensor.get(),</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  m_CellToOutputWeightsTensor.get());</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  }</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a>)</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  {</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  m_ProjectionWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  BuildArmComputeTensor(*m_ProjectionWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">m_ProjectionWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  m_ProjectionBiasTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  {</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  BuildArmComputeTensor(*m_ProjectionBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  }</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="comment">// Set projection params</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  qLstmParams.set_projection_params(</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  m_ProjectionWeightsTensor.get(),</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a> != <span class="keyword">nullptr</span> ? m_ProjectionBiasTensor.get() : <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  }</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> </div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a>)</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  {</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  m_InputLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  {</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  BuildArmComputeTensor(*m_InputLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">m_InputLayerNormWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  }</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> </div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  m_ForgetLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  BuildArmComputeTensor(*m_ForgetLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ad9442e26aa79f896da5f404ab825a9c8">m_ForgetLayerNormWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  m_CellLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  BuildArmComputeTensor(*m_CellLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aeef6f1ac3efad8ec8b0a7118652b64c9">m_CellLayerNormWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  m_OutputLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  BuildArmComputeTensor(*m_OutputLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a0e0f66bd03c88f3d2dc666f581d3cf12">m_OutputLayerNormWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="comment">// Set layer norm params</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  qLstmParams.set_layer_normalization_params(</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">m_InputLayerNormWeights</a> != <span class="keyword">nullptr</span> ? m_InputLayerNormWeightsTensor.get() : <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  m_ForgetLayerNormWeightsTensor.get(),</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  m_CellLayerNormWeightsTensor.get(),</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  m_OutputLayerNormWeightsTensor.get());</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  }</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  {</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  m_InputToInputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  BuildArmComputeTensor(*m_InputToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">m_InputToInputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  m_RecurrentToInputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  BuildArmComputeTensor(*m_RecurrentToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">m_RecurrentToInputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  m_InputGateBiasTensor = std::make_unique<arm_compute::Tensor>();</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  BuildArmComputeTensor(*m_InputGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">m_InputGateBias</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="comment">// Set CIFG params</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  qLstmParams.set_cifg_params(</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  m_InputToInputWeightsTensor.get(),</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  m_RecurrentToInputWeightsTensor.get(),</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">m_CellToInputWeights</a> != <span class="keyword">nullptr</span> ? m_CellToInputWeightsTensor.get() : <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  m_InputGateBiasTensor.get());</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  }</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="comment">// Input/Output tensors</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">const</span> arm_compute::ITensor& input = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0])->GetTensor();</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  arm_compute::ITensor& outputStateIn = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[1])->GetTensor();</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keyword">const</span> arm_compute::ITensor& cellStateIn = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[2])->GetTensor();</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  arm_compute::ITensor& outputStateOut = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0])->GetTensor();</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  arm_compute::ITensor& cellStateOut = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[1])->GetTensor();</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  arm_compute::ITensor& output = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[2])->GetTensor();</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="comment">// Set scalar descriptor params</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  qLstmParams.set_cell_clip_params(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ac81fb0e66dc623dc37c77f219f53a6d3">m_CellClip</a>);</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  qLstmParams.set_projection_clip_params(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa6a518b65088f34803b3214334bdff61">m_ProjectionClip</a>);</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  qLstmParams.set_hidden_state_params(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4556cbd764d4848d8ad0637a9eed580d">m_HiddenStateZeroPoint</a>,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#af8f724af7210b52529216feefa993c98">m_HiddenStateScale</a>);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  qLstmParams.set_matmul_scale_params(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a09e1f097944f61cc901240f9300364cf">m_InputIntermediateScale</a>,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#afec7f36158448f723b426a9527acb189">m_ForgetIntermediateScale</a>,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a0477ee1b44ace6090119178eea78cb0b">m_CellIntermediateScale</a>,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa43409f9b457352c95c89f20ce5d844d">m_OutputIntermediateScale</a>);</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> </div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">// QLSTM NEON configure</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  m_QLstmLayer.configure(&input,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  m_InputToForgetWeightsTensor.get(),</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  m_InputToCellWeightsTensor.get(),</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  m_InputToOutputWeightsTensor.get(),</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  m_RecurrentToForgetWeightsTensor.get(),</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  m_RecurrentToCellWeightsTensor.get(),</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  m_RecurrentToOutputWeightsTensor.get(),</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  m_ForgetGateBiasTensor.get(),</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  m_CellBiasTensor.get(),</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  m_OutputGateBiasTensor.get(),</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  &cellStateIn,</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  &outputStateIn,</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  &cellStateOut,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  &outputStateOut,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  &output,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  qLstmParams);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> </div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="comment">// Initialise ACL tensor data for mandatory params</span></div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a>);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputToCellWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a>);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a>);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> </div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_RecurrentToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a>);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_RecurrentToCellWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a>);</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_RecurrentToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a>);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> </div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_ForgetGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a>);</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_CellBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a>);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_OutputGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a>);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> </div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="comment">// Initialise ACL tensor data for optional params</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  {</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">m_InputToInputWeights</a>);</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_RecurrentToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">m_RecurrentToInputWeights</a>);</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">m_InputGateBias</a>);</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  }</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> </div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a>)</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  {</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_ProjectionWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">m_ProjectionWeights</a>);</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  {</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_ProjectionBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a>);</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  }</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  }</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> </div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a>)</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  {</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  {</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_CellToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">m_CellToInputWeights</a>);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  }</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span> </div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_CellToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">m_CellToForgetWeights</a>);</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_CellToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">m_CellToOutputWeights</a>);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  }</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a>)</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  {</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  {</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">m_InputLayerNormWeights</a>);</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  }</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> </div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_ForgetLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ad9442e26aa79f896da5f404ab825a9c8">m_ForgetLayerNormWeights</a>);</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_CellLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aeef6f1ac3efad8ec8b0a7118652b64c9">m_CellLayerNormWeights</a>);</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_OutputLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a0e0f66bd03c88f3d2dc666f581d3cf12">m_OutputLayerNormWeights</a>);</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  }</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> </div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="comment">// QLSTM NEON prepare</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  m_QLstmLayer.prepare();</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> </div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  FreeUnusedTensors();</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> }</div><div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_aeef6f1ac3efad8ec8b0a7118652b64c9"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aeef6f1ac3efad8ec8b0a7118652b64c9">armnn::QLstmQueueDescriptor::m_CellLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00603">WorkloadData.hpp:603</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a3ead2ef8da00b2709d561d85996fc513"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">armnn::QLstmQueueDescriptor::m_ProjectionWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00599">WorkloadData.hpp:599</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a29fa293fffbf9c6f00cd75db1dc0a52a"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">armnn::QLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00596">WorkloadData.hpp:596</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a17ba1c8bcc71a55a95b2a3913f8cb203"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">armnn::QLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00587">WorkloadData.hpp:587</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::QLstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01367">Descriptors.hpp:1367</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_af8f724af7210b52529216feefa993c98"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#af8f724af7210b52529216feefa993c98">armnn::QLstmDescriptor::m_HiddenStateScale</a></div><div class="ttdeci">float m_HiddenStateScale</div><div class="ttdoc">Hidden State quantization scale. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01383">Descriptors.hpp:1383</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_ab160eba2493d5fe52185c0986dcb190c"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">armnn::QLstmQueueDescriptor::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00584">WorkloadData.hpp:584</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_aa09f7bdb9fd0d06b6386e412a4e72dd6"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">armnn::QLstmQueueDescriptor::m_CellToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00594">WorkloadData.hpp:594</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_aa43409f9b457352c95c89f20ce5d844d"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa43409f9b457352c95c89f20ce5d844d">armnn::QLstmDescriptor::m_OutputIntermediateScale</a></div><div class="ttdeci">float m_OutputIntermediateScale</div><div class="ttdoc">Output intermediate quantization scale. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01379">Descriptors.hpp:1379</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a951b7c90b862138071a298065f16be61"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">armnn::QLstmQueueDescriptor::m_CellToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00592">WorkloadData.hpp:592</a></div></div> -<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00066">WorkloadData.hpp:66</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_ad9442e26aa79f896da5f404ab825a9c8"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ad9442e26aa79f896da5f404ab825a9c8">armnn::QLstmQueueDescriptor::m_ForgetLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00602">WorkloadData.hpp:602</a></div></div> -<div class="ttc" id="classarmnn_1_1_const_tensor_handle_xhtml_a66e8f43a5b42b500871ed96e15419567"><div class="ttname"><a href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">armnn::ConstTensorHandle::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_8hpp_source.xhtml#l00040">TensorHandle.hpp:40</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_a4a8ec49f130084445d44297549254780"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">armnn::QLstmDescriptor::m_LayerNormEnabled</a></div><div class="ttdeci">bool m_LayerNormEnabled</div><div class="ttdoc">Enable/disable layer normalization. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01371">Descriptors.hpp:1371</a></div></div> -<div class="ttc" id="classarmnn_1_1_base_workload_xhtml_afb8d2c8817c75de9d01a4c0e0d5c160b"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">armnn::BaseWorkload< QLstmQueueDescriptor >::m_Data</a></div><div class="ttdeci">QLstmQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00083">Workload.hpp:83</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_aa6a518b65088f34803b3214334bdff61"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa6a518b65088f34803b3214334bdff61">armnn::QLstmDescriptor::m_ProjectionClip</a></div><div class="ttdeci">float m_ProjectionClip</div><div class="ttdoc">Clipping threshold value for the projection. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01363">Descriptors.hpp:1363</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_aab77f54a037658ca9b2bf9cc8a1fadf1"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">armnn::QLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00585">WorkloadData.hpp:585</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_a09e1f097944f61cc901240f9300364cf"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a09e1f097944f61cc901240f9300364cf">armnn::QLstmDescriptor::m_InputIntermediateScale</a></div><div class="ttdeci">float m_InputIntermediateScale</div><div class="ttdoc">Input intermediate quantization scale. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01373">Descriptors.hpp:1373</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a6e9593869b82984de198fed27f72cdcf"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">armnn::QLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00597">WorkloadData.hpp:597</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a1dbad32cad5c0437e1272f59fedf52ea"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">armnn::QLstmQueueDescriptor::m_InputLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00601">WorkloadData.hpp:601</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_a611208865d55ea576cc89ac86d7c19b7"><div class="ttname"><a href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">armnn::InitializeArmComputeTensorData</a></div><div class="ttdeci">void InitializeArmComputeTensorData(arm_compute::Tensor &tensor, TensorInfo tensorInfo, const ITensorHandle *handle)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00060">NeonWorkloadUtils.hpp:60</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_afec7f36158448f723b426a9527acb189"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#afec7f36158448f723b426a9527acb189">armnn::QLstmDescriptor::m_ForgetIntermediateScale</a></div><div class="ttdeci">float m_ForgetIntermediateScale</div><div class="ttdoc">Forget intermediate quantization scale. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01375">Descriptors.hpp:1375</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a841439e3b8dc157a7368b19c9ecb7d03"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">armnn::QLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00586">WorkloadData.hpp:586</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_ac81fb0e66dc623dc37c77f219f53a6d3"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#ac81fb0e66dc623dc37c77f219f53a6d3">armnn::QLstmDescriptor::m_CellClip</a></div><div class="ttdeci">float m_CellClip</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01361">Descriptors.hpp:1361</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a20c10fcb26657477377d07b7b1e13120"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">armnn::QLstmQueueDescriptor::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00593">WorkloadData.hpp:593</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_ac668b31de6fb0f19d4c793d5ed3c3316"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">armnn::QLstmQueueDescriptor::m_ProjectionBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00600">WorkloadData.hpp:600</a></div></div> -<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00027">WorkloadData.hpp:27</a></div></div> -<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_ac18c8b8b2039267d8282e91b4162d8aa"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">armnn::QLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00590">WorkloadData.hpp:590</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::QLstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01369">Descriptors.hpp:1369</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a44eb7524badcca9b2073359e3814c98b"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">armnn::QLstmQueueDescriptor::m_InputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00595">WorkloadData.hpp:595</a></div></div> -<div class="ttc" id="_profiling_8hpp_xhtml_a786492a3881a4c760ab1eec2149f4aba"><div class="ttname"><a href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a></div><div class="ttdeci">#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00227">Profiling.hpp:227</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a5ff4158b1b363b898d0da04c42d37ce0"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">armnn::QLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00598">WorkloadData.hpp:598</a></div></div> -<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00026">WorkloadData.hpp:26</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a0e0f66bd03c88f3d2dc666f581d3cf12"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a0e0f66bd03c88f3d2dc666f581d3cf12">armnn::QLstmQueueDescriptor::m_OutputLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00604">WorkloadData.hpp:604</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_a0477ee1b44ace6090119178eea78cb0b"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a0477ee1b44ace6090119178eea78cb0b">armnn::QLstmDescriptor::m_CellIntermediateScale</a></div><div class="ttdeci">float m_CellIntermediateScale</div><div class="ttdoc">Cell intermediate quantization scale. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01377">Descriptors.hpp:1377</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a4c27716f61bb68e8ea0bd4e8389ba01a"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">armnn::QLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00591">WorkloadData.hpp:591</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_a299587d4f3fca029492700f3e2585bd8"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">armnn::QLstmQueueDescriptor::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00588">WorkloadData.hpp:588</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::QLstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable CIFG (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01365">Descriptors.hpp:1365</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml_adf8571dd1867ee91082bd005f94f2610"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">armnn::QLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00589">WorkloadData.hpp:589</a></div></div> -<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_a4556cbd764d4848d8ad0637a9eed580d"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4556cbd764d4848d8ad0637a9eed580d">armnn::QLstmDescriptor::m_HiddenStateZeroPoint</a></div><div class="ttdeci">int32_t m_HiddenStateZeroPoint</div><div class="ttdoc">Hidden State zero point. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01381">Descriptors.hpp:1381</a></div></div> +<div class="fragment"><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  : NeonBaseWorkload<QLstmQueueDescriptor>(descriptor, info)</div> +<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> {</div> +<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="comment">// Report Profiling Details</span></div> +<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>(<span class="stringliteral">"NeonQLstmWorkload_Construct"</span>,</div> +<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  descriptor.m_Parameters,</div> +<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  info,</div> +<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  this->GetGuid());</div> +<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  </div> +<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  arm_compute::LSTMParams<arm_compute::ITensor> qLstmParams;</div> +<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  </div> +<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="comment">// Mandatory params</span></div> +<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  m_InputToForgetWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  BuildArmComputeTensor(*m_InputToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  </div> +<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  m_InputToCellWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  BuildArmComputeTensor(*m_InputToCellWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  </div> +<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  m_InputToOutputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  BuildArmComputeTensor(*m_InputToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  </div> +<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  m_RecurrentToForgetWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  BuildArmComputeTensor(*m_RecurrentToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  </div> +<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  m_RecurrentToCellWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  BuildArmComputeTensor(*m_RecurrentToCellWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  </div> +<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  m_RecurrentToOutputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  BuildArmComputeTensor(*m_RecurrentToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  </div> +<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  m_ForgetGateBiasTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  BuildArmComputeTensor(*m_ForgetGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  </div> +<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  m_CellBiasTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  BuildArmComputeTensor(*m_CellBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  </div> +<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  m_OutputGateBiasTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  BuildArmComputeTensor(*m_OutputGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  </div> +<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">// Create tensors for optional params if they are enabled</span></div> +<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a>)</div> +<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  {</div> +<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  m_CellToInputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  </div> +<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div> +<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  {</div> +<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">// In ACL this is categorised as a CIFG param and not a Peephole param</span></div> +<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  BuildArmComputeTensor(*m_CellToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">m_CellToInputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  }</div> +<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  </div> +<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  m_CellToForgetWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  BuildArmComputeTensor(*m_CellToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">m_CellToForgetWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  </div> +<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  m_CellToOutputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  BuildArmComputeTensor(*m_CellToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">m_CellToOutputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  </div> +<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// Set Peephole params</span></div> +<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  qLstmParams.set_peephole_params(m_CellToForgetWeightsTensor.get(),</div> +<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  m_CellToOutputWeightsTensor.get());</div> +<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  }</div> +<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  </div> +<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a>)</div> +<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  {</div> +<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  m_ProjectionWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  BuildArmComputeTensor(*m_ProjectionWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">m_ProjectionWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  </div> +<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  m_ProjectionBiasTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a> != <span class="keyword">nullptr</span>)</div> +<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  {</div> +<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  BuildArmComputeTensor(*m_ProjectionBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  }</div> +<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  </div> +<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="comment">// Set projection params</span></div> +<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  qLstmParams.set_projection_params(</div> +<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  m_ProjectionWeightsTensor.get(),</div> +<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a> != <span class="keyword">nullptr</span> ? m_ProjectionBiasTensor.get() : <span class="keyword">nullptr</span>);</div> +<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  }</div> +<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  </div> +<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a>)</div> +<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  {</div> +<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  m_InputLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  </div> +<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div> +<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  {</div> +<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  BuildArmComputeTensor(*m_InputLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">m_InputLayerNormWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  }</div> +<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  </div> +<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  m_ForgetLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  BuildArmComputeTensor(*m_ForgetLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ad9442e26aa79f896da5f404ab825a9c8">m_ForgetLayerNormWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  </div> +<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  m_CellLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  BuildArmComputeTensor(*m_CellLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aeef6f1ac3efad8ec8b0a7118652b64c9">m_CellLayerNormWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  </div> +<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  m_OutputLayerNormWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  BuildArmComputeTensor(*m_OutputLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a0e0f66bd03c88f3d2dc666f581d3cf12">m_OutputLayerNormWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  </div> +<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="comment">// Set layer norm params</span></div> +<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  qLstmParams.set_layer_normalization_params(</div> +<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">m_InputLayerNormWeights</a> != <span class="keyword">nullptr</span> ? m_InputLayerNormWeightsTensor.get() : <span class="keyword">nullptr</span>,</div> +<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  m_ForgetLayerNormWeightsTensor.get(),</div> +<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  m_CellLayerNormWeightsTensor.get(),</div> +<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  m_OutputLayerNormWeightsTensor.get());</div> +<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  }</div> +<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  </div> +<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div> +<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  {</div> +<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  m_InputToInputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  BuildArmComputeTensor(*m_InputToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">m_InputToInputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  </div> +<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  m_RecurrentToInputWeightsTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  BuildArmComputeTensor(*m_RecurrentToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">m_RecurrentToInputWeights</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  </div> +<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  m_InputGateBiasTensor = std::make_unique<arm_compute::Tensor>();</div> +<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  BuildArmComputeTensor(*m_InputGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">m_InputGateBias</a>-><a class="code" href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>());</div> +<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  </div> +<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="comment">// Set CIFG params</span></div> +<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  qLstmParams.set_cifg_params(</div> +<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  m_InputToInputWeightsTensor.get(),</div> +<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  m_RecurrentToInputWeightsTensor.get(),</div> +<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">m_CellToInputWeights</a> != <span class="keyword">nullptr</span> ? m_CellToInputWeightsTensor.get() : <span class="keyword">nullptr</span>,</div> +<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  m_InputGateBiasTensor.get());</div> +<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  }</div> +<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  </div> +<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="comment">// Input/Output tensors</span></div> +<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="keyword">const</span> arm_compute::ITensor& input = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0])->GetTensor();</div> +<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  arm_compute::ITensor& outputStateIn = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[1])->GetTensor();</div> +<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keyword">const</span> arm_compute::ITensor& cellStateIn = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[2])->GetTensor();</div> +<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  </div> +<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  arm_compute::ITensor& outputStateOut = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0])->GetTensor();</div> +<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  arm_compute::ITensor& cellStateOut = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[1])->GetTensor();</div> +<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  arm_compute::ITensor& output = <span class="keyword">static_cast<</span>IAclTensorHandle*<span class="keyword">></span>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[2])->GetTensor();</div> +<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  </div> +<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="comment">// Set scalar descriptor params</span></div> +<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  qLstmParams.set_cell_clip_params(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ac81fb0e66dc623dc37c77f219f53a6d3">m_CellClip</a>);</div> +<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  qLstmParams.set_projection_clip_params(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa6a518b65088f34803b3214334bdff61">m_ProjectionClip</a>);</div> +<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  qLstmParams.set_hidden_state_params(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4556cbd764d4848d8ad0637a9eed580d">m_HiddenStateZeroPoint</a>,</div> +<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#af8f724af7210b52529216feefa993c98">m_HiddenStateScale</a>);</div> +<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  qLstmParams.set_matmul_scale_params(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a09e1f097944f61cc901240f9300364cf">m_InputIntermediateScale</a>,</div> +<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#afec7f36158448f723b426a9527acb189">m_ForgetIntermediateScale</a>,</div> +<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a0477ee1b44ace6090119178eea78cb0b">m_CellIntermediateScale</a>,</div> +<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa43409f9b457352c95c89f20ce5d844d">m_OutputIntermediateScale</a>);</div> +<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  </div> +<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">// QLSTM NEON configure</span></div> +<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  m_QLstmLayer.configure(&input,</div> +<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  m_InputToForgetWeightsTensor.get(),</div> +<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  m_InputToCellWeightsTensor.get(),</div> +<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  m_InputToOutputWeightsTensor.get(),</div> +<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  m_RecurrentToForgetWeightsTensor.get(),</div> +<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  m_RecurrentToCellWeightsTensor.get(),</div> +<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  m_RecurrentToOutputWeightsTensor.get(),</div> +<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  m_ForgetGateBiasTensor.get(),</div> +<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  m_CellBiasTensor.get(),</div> +<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  m_OutputGateBiasTensor.get(),</div> +<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  &cellStateIn,</div> +<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  &outputStateIn,</div> +<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  &cellStateOut,</div> +<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  &outputStateOut,</div> +<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  &output,</div> +<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  qLstmParams);</div> +<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  </div> +<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="comment">// Initialise ACL tensor data for mandatory params</span></div> +<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a>);</div> +<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputToCellWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a>);</div> +<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a>);</div> +<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  </div> +<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_RecurrentToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a>);</div> +<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_RecurrentToCellWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a>);</div> +<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_RecurrentToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a>);</div> +<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  </div> +<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_ForgetGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a>);</div> +<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_CellBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a>);</div> +<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_OutputGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a>);</div> +<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  </div> +<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="comment">// Initialise ACL tensor data for optional params</span></div> +<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div> +<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  {</div> +<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">m_InputToInputWeights</a>);</div> +<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_RecurrentToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">m_RecurrentToInputWeights</a>);</div> +<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputGateBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">m_InputGateBias</a>);</div> +<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  }</div> +<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  </div> +<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a>)</div> +<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  {</div> +<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_ProjectionWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">m_ProjectionWeights</a>);</div> +<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  </div> +<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a> != <span class="keyword">nullptr</span>)</div> +<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  {</div> +<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_ProjectionBiasTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a>);</div> +<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  }</div> +<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  }</div> +<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  </div> +<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a>)</div> +<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  {</div> +<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div> +<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  {</div> +<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_CellToInputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">m_CellToInputWeights</a>);</div> +<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  }</div> +<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  </div> +<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_CellToForgetWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">m_CellToForgetWeights</a>);</div> +<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_CellToOutputWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">m_CellToOutputWeights</a>);</div> +<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  }</div> +<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  </div> +<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a>)</div> +<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  {</div> +<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>)</div> +<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  {</div> +<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_InputLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">m_InputLayerNormWeights</a>);</div> +<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  }</div> +<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  </div> +<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_ForgetLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ad9442e26aa79f896da5f404ab825a9c8">m_ForgetLayerNormWeights</a>);</div> +<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_CellLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aeef6f1ac3efad8ec8b0a7118652b64c9">m_CellLayerNormWeights</a>);</div> +<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <a class="code" href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">InitializeArmComputeTensorData</a>(*m_OutputLayerNormWeightsTensor, <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a0e0f66bd03c88f3d2dc666f581d3cf12">m_OutputLayerNormWeights</a>);</div> +<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  }</div> +<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  </div> +<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="comment">// QLSTM NEON prepare</span></div> +<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  m_QLstmLayer.prepare();</div> +<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  </div> +<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  FreeUnusedTensors();</div> +<div class="line"><a name="l00235"></a><span class="lineno"> 235</span> }</div> </div><!-- fragment --> +<p class="reference">References <a class="el" href="_profiling_8hpp_source.xhtml#l00227">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>, <a class="el" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::info</a>, and <a class="el" href="_workload_data_8hpp_source.xhtml#l00066">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>.</p> + </div> </div> <h2 class="groupheader">Member Function Documentation</h2> @@ -264,11 +448,13 @@ Additional Inherited Members</h2></td></tr> <p>Implements <a class="el" href="classarmnn_1_1_i_workload.xhtml#a72ae00e6604850c8798c5e0d825ee7e4">IWorkload</a>.</p> <p class="definition">Definition at line <a class="el" href="_neon_q_lstm_workload_8cpp_source.xhtml#l00237">237</a> of file <a class="el" href="_neon_q_lstm_workload_8cpp_source.xhtml">NeonQLstmWorkload.cpp</a>.</p> - -<p class="reference">References <a class="el" href="_neon_workload_utils_8hpp_source.xhtml#l00024">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>, and <a class="el" href="_workload_8hpp_source.xhtml#l00061">BaseWorkload< QLstmQueueDescriptor >::GetGuid()</a>.</p> -<div class="fragment"><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> {</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <a class="code" href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>(<span class="stringliteral">"NeonQuantizedLstmWorkload_Execute"</span>, this-><a class="code" href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">GetGuid</a>());</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  m_QLstmLayer.run();</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> }</div><div class="ttc" id="classarmnn_1_1_base_workload_xhtml_aaff95a48875d8fb4a616352906660ca9"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">armnn::BaseWorkload< QLstmQueueDescriptor >::GetGuid</a></div><div class="ttdeci">arm::pipe::ProfilingGuid GetGuid() const final</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00061">Workload.hpp:61</a></div></div> -<div class="ttc" id="_neon_workload_utils_8hpp_xhtml_a9165e41bcaf1b90f9ff91ef681e88c4f"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00024">NeonWorkloadUtils.hpp:24</a></div></div> +<div class="fragment"><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> {</div> +<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <a class="code" href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>(<span class="stringliteral">"NeonQuantizedLstmWorkload_Execute"</span>, this-><a class="code" href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">GetGuid</a>());</div> +<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  m_QLstmLayer.run();</div> +<div class="line"><a name="l00241"></a><span class="lineno"> 241</span> }</div> </div><!-- fragment --> +<p class="reference">References <a class="el" href="_neon_workload_utils_8hpp_source.xhtml#l00024">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>, and <a class="el" href="_workload_8hpp_source.xhtml#l00061">BaseWorkload< QLstmQueueDescriptor >::GetGuid()</a>.</p> + </div> </div> <hr/>The documentation for this class was generated from the following files:<ul> @@ -277,13 +463,55 @@ Additional Inherited Members</h2></td></tr> </ul> </div><!-- contents --> </div><!-- doc-content --> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_ac81fb0e66dc623dc37c77f219f53a6d3"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#ac81fb0e66dc623dc37c77f219f53a6d3">armnn::QLstmDescriptor::m_CellClip</a></div><div class="ttdeci">float m_CellClip</div><div class="ttdoc">Clipping threshold value for the cell state.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01361">Descriptors.hpp:1361</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_a4a8ec49f130084445d44297549254780"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">armnn::QLstmDescriptor::m_LayerNormEnabled</a></div><div class="ttdeci">bool m_LayerNormEnabled</div><div class="ttdoc">Enable/disable layer normalization.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01371">Descriptors.hpp:1371</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_aa6a518b65088f34803b3214334bdff61"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa6a518b65088f34803b3214334bdff61">armnn::QLstmDescriptor::m_ProjectionClip</a></div><div class="ttdeci">float m_ProjectionClip</div><div class="ttdoc">Clipping threshold value for the projection.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01363">Descriptors.hpp:1363</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_adf8571dd1867ee91082bd005f94f2610"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">armnn::QLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00589">WorkloadData.hpp:589</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_workload_xhtml_aaff95a48875d8fb4a616352906660ca9"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">armnn::BaseWorkload< QLstmQueueDescriptor >::GetGuid</a></div><div class="ttdeci">arm::pipe::ProfilingGuid GetGuid() const final</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00061">Workload.hpp:61</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_afec7f36158448f723b426a9527acb189"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#afec7f36158448f723b426a9527acb189">armnn::QLstmDescriptor::m_ForgetIntermediateScale</a></div><div class="ttdeci">float m_ForgetIntermediateScale</div><div class="ttdoc">Forget intermediate quantization scale.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01375">Descriptors.hpp:1375</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a5ff4158b1b363b898d0da04c42d37ce0"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">armnn::QLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00598">WorkloadData.hpp:598</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a17ba1c8bcc71a55a95b2a3913f8cb203"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">armnn::QLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00587">WorkloadData.hpp:587</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_base_workload_xhtml_afb8d2c8817c75de9d01a4c0e0d5c160b"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">armnn::BaseWorkload< QLstmQueueDescriptor >::m_Data</a></div><div class="ttdeci">QLstmQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00083">Workload.hpp:83</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_a0477ee1b44ace6090119178eea78cb0b"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a0477ee1b44ace6090119178eea78cb0b">armnn::QLstmDescriptor::m_CellIntermediateScale</a></div><div class="ttdeci">float m_CellIntermediateScale</div><div class="ttdoc">Cell intermediate quantization scale.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01377">Descriptors.hpp:1377</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_aa43409f9b457352c95c89f20ce5d844d"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa43409f9b457352c95c89f20ce5d844d">armnn::QLstmDescriptor::m_OutputIntermediateScale</a></div><div class="ttdeci">float m_OutputIntermediateScale</div><div class="ttdoc">Output intermediate quantization scale.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01379">Descriptors.hpp:1379</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_ac668b31de6fb0f19d4c793d5ed3c3316"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">armnn::QLstmQueueDescriptor::m_ProjectionBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00600">WorkloadData.hpp:600</a></div></div> +<div class="ttc" id="anamespacearmnn_xhtml_a611208865d55ea576cc89ac86d7c19b7"><div class="ttname"><a href="namespacearmnn.xhtml#a611208865d55ea576cc89ac86d7c19b7">armnn::InitializeArmComputeTensorData</a></div><div class="ttdeci">void InitializeArmComputeTensorData(arm_compute::Tensor &tensor, TensorInfo tensorInfo, const ITensorHandle *handle)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00060">NeonWorkloadUtils.hpp:60</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a6e9593869b82984de198fed27f72cdcf"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">armnn::QLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00597">WorkloadData.hpp:597</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a29fa293fffbf9c6f00cd75db1dc0a52a"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">armnn::QLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00596">WorkloadData.hpp:596</a></div></div> +<div class="ttc" id="a_neon_workload_utils_8hpp_xhtml_a9165e41bcaf1b90f9ff91ef681e88c4f"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00024">NeonWorkloadUtils.hpp:24</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_aab77f54a037658ca9b2bf9cc8a1fadf1"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">armnn::QLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00585">WorkloadData.hpp:585</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_ad9442e26aa79f896da5f404ab825a9c8"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ad9442e26aa79f896da5f404ab825a9c8">armnn::QLstmQueueDescriptor::m_ForgetLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00602">WorkloadData.hpp:602</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a951b7c90b862138071a298065f16be61"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">armnn::QLstmQueueDescriptor::m_CellToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00592">WorkloadData.hpp:592</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a3ead2ef8da00b2709d561d85996fc513"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">armnn::QLstmQueueDescriptor::m_ProjectionWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00599">WorkloadData.hpp:599</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a299587d4f3fca029492700f3e2585bd8"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">armnn::QLstmQueueDescriptor::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00588">WorkloadData.hpp:588</a></div></div> +<div class="ttc" id="aclassarmnn_1_1_const_tensor_handle_xhtml_a66e8f43a5b42b500871ed96e15419567"><div class="ttname"><a href="classarmnn_1_1_const_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">armnn::ConstTensorHandle::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_8hpp_source.xhtml#l00040">TensorHandle.hpp:40</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_af8f724af7210b52529216feefa993c98"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#af8f724af7210b52529216feefa993c98">armnn::QLstmDescriptor::m_HiddenStateScale</a></div><div class="ttdeci">float m_HiddenStateScale</div><div class="ttdoc">Hidden State quantization scale.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01383">Descriptors.hpp:1383</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_a4556cbd764d4848d8ad0637a9eed580d"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4556cbd764d4848d8ad0637a9eed580d">armnn::QLstmDescriptor::m_HiddenStateZeroPoint</a></div><div class="ttdeci">int32_t m_HiddenStateZeroPoint</div><div class="ttdoc">Hidden State zero point.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01381">Descriptors.hpp:1381</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_aa09f7bdb9fd0d06b6386e412a4e72dd6"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">armnn::QLstmQueueDescriptor::m_CellToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00594">WorkloadData.hpp:594</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a0e0f66bd03c88f3d2dc666f581d3cf12"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a0e0f66bd03c88f3d2dc666f581d3cf12">armnn::QLstmQueueDescriptor::m_OutputLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00604">WorkloadData.hpp:604</a></div></div> +<div class="ttc" id="astructarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00066">WorkloadData.hpp:66</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_aeef6f1ac3efad8ec8b0a7118652b64c9"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#aeef6f1ac3efad8ec8b0a7118652b64c9">armnn::QLstmQueueDescriptor::m_CellLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00603">WorkloadData.hpp:603</a></div></div> +<div class="ttc" id="a_profiling_8hpp_xhtml_a786492a3881a4c760ab1eec2149f4aba"><div class="ttname"><a href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a></div><div class="ttdeci">#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00227">Profiling.hpp:227</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a841439e3b8dc157a7368b19c9ecb7d03"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">armnn::QLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00586">WorkloadData.hpp:586</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_a09e1f097944f61cc901240f9300364cf"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a09e1f097944f61cc901240f9300364cf">armnn::QLstmDescriptor::m_InputIntermediateScale</a></div><div class="ttdeci">float m_InputIntermediateScale</div><div class="ttdoc">Input intermediate quantization scale.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01373">Descriptors.hpp:1373</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a4c27716f61bb68e8ea0bd4e8389ba01a"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">armnn::QLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00591">WorkloadData.hpp:591</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::QLstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable CIFG (coupled input & forget gate).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01365">Descriptors.hpp:1365</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a20c10fcb26657477377d07b7b1e13120"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">armnn::QLstmQueueDescriptor::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00593">WorkloadData.hpp:593</a></div></div> +<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00027">WorkloadData.hpp:27</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::QLstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01367">Descriptors.hpp:1367</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_ab160eba2493d5fe52185c0986dcb190c"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">armnn::QLstmQueueDescriptor::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00584">WorkloadData.hpp:584</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_ac18c8b8b2039267d8282e91b4162d8aa"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">armnn::QLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00590">WorkloadData.hpp:590</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a44eb7524badcca9b2073359e3814c98b"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">armnn::QLstmQueueDescriptor::m_InputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00595">WorkloadData.hpp:595</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::QLstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01369">Descriptors.hpp:1369</a></div></div> +<div class="ttc" id="astructarmnn_1_1_q_lstm_queue_descriptor_xhtml_a1dbad32cad5c0437e1272f59fedf52ea"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">armnn::QLstmQueueDescriptor::m_InputLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00601">WorkloadData.hpp:601</a></div></div> +<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00026">WorkloadData.hpp:26</a></div></div> <!-- start footer part --> <div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> <ul> <li class="navelem"><a class="el" href="namespacearmnn.xhtml">armnn</a></li><li class="navelem"><a class="el" href="classarmnn_1_1_neon_q_lstm_workload.xhtml">NeonQLstmWorkload</a></li> - <li class="footer">Generated on Fri Feb 24 2023 10:24:31 for ArmNN by + <li class="footer">Generated on Wed Mar 22 2023 15:53:07 for ArmNN by <a href="http://www.doxygen.org/index.html"> - <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.17 </li> </ul> </div> </body> |