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| author | Nikhil Raj <nikhil.raj@arm.com> | 2022-06-17 13:24:58 +0100 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-06-17 13:24:58 +0100 |
| commit | d5d43d82c0137e08553e44345c609cdd1a7931c7 (patch) | |
| tree | f1509f7fa94db0373a2c127682dd3d0ccc1915bd /22.05.01/_ref_lstm_workload_8cpp_source.xhtml | |
| parent | 549b9600a6eaf0727fa084465a75f173edf8f381 (diff) | |
| download | armnn-d5d43d82c0137e08553e44345c609cdd1a7931c7.tar.gz | |
Update Doxygen for 22.05 patch release
* Pooling3D added to tfLite delegate
* Available in tag 22.05.01
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: I8d605bba4e87d30baa2c6d7b338c78a4400dc021
Diffstat (limited to '22.05.01/_ref_lstm_workload_8cpp_source.xhtml')
| -rw-r--r-- | 22.05.01/_ref_lstm_workload_8cpp_source.xhtml | 144 |
1 files changed, 144 insertions, 0 deletions
diff --git a/22.05.01/_ref_lstm_workload_8cpp_source.xhtml b/22.05.01/_ref_lstm_workload_8cpp_source.xhtml new file mode 100644 index 0000000000..73e383c1ac --- /dev/null +++ b/22.05.01/_ref_lstm_workload_8cpp_source.xhtml @@ -0,0 +1,144 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/backends/reference/workloads/RefLstmWorkload.cpp Source File</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">22.05.01</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_ref_lstm_workload_8cpp_source.xhtml','');}); +</script> +<div id="doc-content"> +<!-- window showing the filter options --> +<div id="MSearchSelectWindow" + onmouseover="return searchBox.OnSearchSelectShow()" + onmouseout="return searchBox.OnSearchSelectHide()" + onkeydown="return searchBox.OnSearchSelectKey(event)"> +</div> + +<!-- iframe showing the search results (closed by default) --> +<div id="MSearchResultsWindow"> +<iframe src="javascript:void(0)" frameborder="0" + name="MSearchResults" id="MSearchResults"> +</iframe> +</div> + +<div class="header"> + <div class="headertitle"> +<div class="title">RefLstmWorkload.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_ref_lstm_workload_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_ref_lstm_workload_8hpp.xhtml">RefLstmWorkload.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_activation_8hpp.xhtml">Activation.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_encoders_8hpp.xhtml">Encoders.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_decoders_8hpp.xhtml">Decoders.hpp</a>"</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include "<a class="code" href="_lstm_8hpp.xhtml">Lstm.hpp</a>"</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include "<a class="code" href="_lstm_utils_8hpp.xhtml">LstmUtils.hpp</a>"</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include "<a class="code" href="_ref_workload_utils_8hpp.xhtml">RefWorkloadUtils.hpp</a>"</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> {</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"><a class="line" href="classarmnn_1_1_ref_lstm_workload.xhtml#a236c28ffd299dcfa88d6c0260e69f000"> 17</a></span> <a class="code" href="classarmnn_1_1_ref_lstm_workload.xhtml#a236c28ffd299dcfa88d6c0260e69f000">RefLstmWorkload::RefLstmWorkload</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_lstm_queue_descriptor.xhtml">LstmQueueDescriptor</a> &descriptor, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a> &info)</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  : <a class="code" href="classarmnn_1_1_ref_base_workload.xhtml">RefBaseWorkload</a><<a class="code" href="structarmnn_1_1_lstm_queue_descriptor.xhtml">LstmQueueDescriptor</a>>(descriptor, info)</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  , m_InputToInputWeightsTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputToInputWeights))</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  , m_InputToForgetWeightsTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputToForgetWeights))</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  , m_InputToCellWeightsTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputToCellWeights))</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  , m_InputToOutputWeightsTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputToOutputWeights))</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  , m_RecurrentToInputWeightsTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_RecurrentToInputWeights))</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  , m_RecurrentToForgetWeightsTensor(<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_RecurrentToForgetWeights))</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  , m_RecurrentToCellWeightsTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_RecurrentToCellWeights))</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  , m_RecurrentToOutputWeightsTensor(<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_RecurrentToOutputWeights))</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  , m_CellToInputWeightsTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_CellToInputWeights))</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  , m_CellToForgetWeightsTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_CellToForgetWeights))</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  , m_CellToOutputWeightsTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_CellToOutputWeights))</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  , m_InputGateBiasTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputGateBias))</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  , m_ForgetGateBiasTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_ForgetGateBias))</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  , m_CellBiasTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_CellBias))</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  , m_OutputGateBiasTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_OutputGateBias))</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  , m_ProjectionWeightsTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_ProjectionWeights))</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  , m_ProjectionBiasTensor (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_ProjectionBias))</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  , m_InputLayerNormWeights (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputLayerNormWeights))</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  , m_ForgetLayerNormWeights (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_ForgetLayerNormWeights))</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  , m_CellLayerNormWeights (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_CellLayerNormWeights))</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  , m_OutputLayerNormWeights (<a class="code" href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_OutputLayerNormWeights))</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> </div><div class="line"><a name="l00042"></a><span class="lineno"><a class="line" href="classarmnn_1_1_ref_lstm_workload.xhtml#ae071e8822437c78baea75c3aef3a263a"> 42</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_ref_lstm_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">RefLstmWorkload::Execute</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="keyword"></span>{</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <a class="code" href="classarmnn_1_1_ref_lstm_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">Execute</a>(<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>, <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>);</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> }</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00047"></a><span class="lineno"><a class="line" href="classarmnn_1_1_ref_lstm_workload.xhtml#a03726736f93bb28e11835f093f630a07"> 47</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_ref_lstm_workload.xhtml#a03726736f93bb28e11835f093f630a07">RefLstmWorkload::ExecuteAsync</a>(<a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.xhtml">WorkingMemDescriptor</a> &workingMemDescriptor)</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="classarmnn_1_1_ref_lstm_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">Execute</a>(workingMemDescriptor.<a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>, workingMemDescriptor.<a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> }</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_ref_lstm_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">RefLstmWorkload::Execute</a>(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs)<span class="keyword"> const</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="keyword"></span>{</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="comment">// This is a porting of the LSTM::Eval() method in the Android code base</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="comment">// Refer to: android/frameworks/ml/nn/common/operations/LSTM.cpp</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputInfo = <a class="code" href="namespacearmnn.xhtml#af7ec4c0fa4375a45a70e4e31f3d8af47">GetTensorInfo</a>(inputs[0]);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& outputInfo = <a class="code" href="namespacearmnn.xhtml#af7ec4c0fa4375a45a70e4e31f3d8af47">GetTensorInfo</a>(outputs[0]);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& inputShape = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  std::unique_ptr<Encoder<float>> outputStateOut = MakeEncoder<float>(outputInfo, outputs[1]->Map());</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  std::unique_ptr<Encoder<float>> cellStateOut = MakeEncoder<float>(outputInfo, outputs[2]->Map());</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  std::unique_ptr<Encoder<float>> output = MakeEncoder<float>(outputInfo, outputs[3]->Map());</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>  std::unique_ptr<Decoder<float>> cellStateOutDecoder = MakeDecoder<float>(outputInfo, outputs[2]->Map());</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  std::unique_ptr<Decoder<float>> outputDecoder = MakeDecoder<float>(outputInfo, outputs[3]->Map());</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> </div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  std::unique_ptr<Decoder<float>> inputData = MakeDecoder<float>(inputInfo, inputs[0]->Map());</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  std::unique_ptr<Decoder<float>> outputStateIn = MakeDecoder<float>(inputInfo, inputs[1]->Map());</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  std::unique_ptr<Decoder<float>> cellStateIn = MakeDecoder<float>(inputInfo, inputs[2]->Map());</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="keyword">const</span> uint32_t nBatch = inputShape[0];</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">const</span> uint32_t nCell = m_InputToOutputWeightsTensor->GetShape()[0];</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> useCifg = <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_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> usePeephole = <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_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a>;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> useLayerNorm = <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_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</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>  <span class="comment">// Index the scratch buffers pointers to the global scratch buffer.</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  std::unique_ptr<Encoder<float>> inputGateScratch = MakeEncoder<float>(outputInfo, outputs[0]->Map());</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  std::unique_ptr<Encoder<float>> cellScratch = MakeEncoder<float>(outputInfo, outputs[0]->Map());</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  std::unique_ptr<Encoder<float>> forgetGateScratch = MakeEncoder<float>(outputInfo, outputs[0]->Map());</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  std::unique_ptr<Encoder<float>> outputGateScratch = MakeEncoder<float>(outputInfo, outputs[0]->Map());</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>  std::unique_ptr<Decoder<float>> inputGateScratchDecoder =</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  MakeDecoder<float>(outputInfo, outputs[0]->Map());</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  std::unique_ptr<Decoder<float>> cellScratchDecoder =</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  MakeDecoder<float>(outputInfo, outputs[0]->Map());</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  std::unique_ptr<Decoder<float>> forgetGateScratchDecoder =</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  MakeDecoder<float>(outputInfo, outputs[0]->Map());</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  std::unique_ptr<Decoder<float>> outputGateScratchDecoder =</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  MakeDecoder<float>(outputInfo, outputs[0]->Map());</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> (useCifg)</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>  *cellScratch += (0 * nCell * nBatch);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  *forgetGateScratch += (1 * nCell * nBatch);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  *outputGateScratch += (2 * nCell * nBatch);</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>  *cellScratchDecoder += (0 * nCell * nBatch);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  *forgetGateScratchDecoder += (1 * nCell * nBatch);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  *outputGateScratchDecoder += (2 * nCell * nBatch);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  }</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordflow">else</span></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>  *inputGateScratch += (0 * nCell * nBatch);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  *cellScratch += (1 * nCell * nBatch);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  *forgetGateScratch += (2 * nCell * nBatch);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  *outputGateScratch += (3 * nCell * nBatch);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  *inputGateScratchDecoder += (0 * nCell * nBatch);</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  *cellScratchDecoder += (1 * nCell * nBatch);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  *forgetGateScratchDecoder += (2 * nCell * nBatch);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  *outputGateScratchDecoder += (3 * nCell * nBatch);</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  }</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  std::unique_ptr<Decoder<float>> inputToInputWeightsTensor;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  std::unique_ptr<Decoder<float>> inputToForgetWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  m_InputToForgetWeightsTensor->GetTensorInfo(), m_InputToForgetWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  std::unique_ptr<Decoder<float>> inputToCellWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  m_InputToCellWeightsTensor->GetTensorInfo(), m_InputToCellWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  std::unique_ptr<Decoder<float>> inputToOutputWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  m_InputToOutputWeightsTensor->GetTensorInfo(), m_InputToOutputWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</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>  std::unique_ptr<Decoder<float>> recurrentToInputWeightsTensor;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  std::unique_ptr<Decoder<float>> recurrentToForgetWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  m_RecurrentToForgetWeightsTensor->GetTensorInfo(), m_RecurrentToForgetWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  std::unique_ptr<Decoder<float>> recurrentToCellWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  m_RecurrentToCellWeightsTensor->GetTensorInfo(), m_RecurrentToCellWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  std::unique_ptr<Decoder<float>> recurrentToOutputWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  m_RecurrentToOutputWeightsTensor->GetTensorInfo(), m_RecurrentToOutputWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  std::unique_ptr<Decoder<float>> inputGateBiasTensor;</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  std::unique_ptr<Decoder<float>> forgetGateBiasTensor = MakeDecoder<float>(</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  m_ForgetGateBiasTensor->GetTensorInfo(), m_ForgetGateBiasTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  std::unique_ptr<Decoder<float>> cellBiasTensor = MakeDecoder<float>(</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  m_CellBiasTensor->GetTensorInfo(), m_CellBiasTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  std::unique_ptr<Decoder<float>> outputGateBiasTensor = MakeDecoder<float>(</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  m_OutputGateBiasTensor->GetTensorInfo(), m_OutputGateBiasTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> </div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  std::unique_ptr<Decoder<float>> cellToInputWeightsTensor;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  std::unique_ptr<Decoder<float>> cellToForgetWeightsTensor;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  std::unique_ptr<Decoder<float>> cellToOutputWeightsTensor;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> </div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  std::unique_ptr<Decoder<float>> projectionWeightsTensor;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  std::unique_ptr<Decoder<float>> projectionBiasTensor;</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>  std::unique_ptr<Decoder<float>> inputLayerNormWeights;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  std::unique_ptr<Decoder<float>> forgetLayerNormWeights;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  std::unique_ptr<Decoder<float>> cellLayerNormWeights;</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  std::unique_ptr<Decoder<float>> outputLayerNormWeights;</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& inputToOutputWeightsShape = m_InputToOutputWeightsTensor->GetShape();</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& recurrentToOutputWeightsShape = m_RecurrentToOutputWeightsTensor->GetShape();</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keywordflow">if</span> (useLayerNorm)</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="keywordflow">if</span> (!useCifg)</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  {</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  inputLayerNormWeights = MakeDecoder<float>(</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  m_InputLayerNormWeights->GetTensorInfo(), m_InputLayerNormWeights->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  }</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  forgetLayerNormWeights = MakeDecoder<float>(</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  m_ForgetLayerNormWeights->GetTensorInfo(), m_ForgetLayerNormWeights->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  cellLayerNormWeights = MakeDecoder<float>(</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  m_CellLayerNormWeights->GetTensorInfo(), m_CellLayerNormWeights->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  outputLayerNormWeights = MakeDecoder<float>(</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  m_OutputLayerNormWeights->GetTensorInfo(), m_OutputLayerNormWeights->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  }</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> </div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keywordflow">if</span> (!useCifg)</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  {</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  inputToInputWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  m_InputToInputWeightsTensor->GetTensorInfo(), m_InputToInputWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  inputGateBiasTensor = MakeDecoder<float>(</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  m_InputGateBiasTensor->GetTensorInfo(), m_InputGateBiasTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  recurrentToInputWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  m_RecurrentToInputWeightsTensor->GetTensorInfo(), m_RecurrentToInputWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  }</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>  <span class="keywordflow">if</span> (usePeephole)</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  {</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  cellToForgetWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  m_CellToForgetWeightsTensor->GetTensorInfo(), m_CellToForgetWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  cellToOutputWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  m_CellToOutputWeightsTensor->GetTensorInfo(), m_CellToOutputWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  }</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="keywordflow">if</span> (!useCifg && usePeephole)</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  {</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  cellToInputWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  m_CellToInputWeightsTensor->GetTensorInfo(), m_CellToInputWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  }</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div><div class="line"><a name="l00196"></a><span class="lineno"> 196</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_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a>)</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>  projectionWeightsTensor = MakeDecoder<float>(</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  m_ProjectionWeightsTensor->GetTensorInfo(), m_ProjectionWeightsTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keywordflow">if</span> (m_ProjectionBiasTensor)</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>  projectionBiasTensor = MakeDecoder<float>(</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  m_ProjectionBiasTensor->GetTensorInfo(), m_ProjectionBiasTensor->GetConstTensor<<span class="keywordtype">void</span>>());</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  }</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>  <a class="code" href="namespacearmnn.xhtml#a952423703fa6b92f18d19df3995633b4">LstmImpl</a>(<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>,</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  inputInfo,</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  outputInfo,</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  inputToOutputWeightsShape,</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  recurrentToOutputWeightsShape,</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  inputData,</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  outputStateIn,</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  cellStateIn,</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  outputStateOut,</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  cellStateOut,</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  output,</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  cellStateOutDecoder,</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  outputDecoder,</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  inputToInputWeightsTensor,</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  inputToForgetWeightsTensor,</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  inputToCellWeightsTensor,</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  inputToOutputWeightsTensor,</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  recurrentToInputWeightsTensor,</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  recurrentToForgetWeightsTensor,</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  recurrentToCellWeightsTensor,</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  recurrentToOutputWeightsTensor,</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  cellToInputWeightsTensor,</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  cellToForgetWeightsTensor,</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  cellToOutputWeightsTensor,</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  inputGateBiasTensor,</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  forgetGateBiasTensor,</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  cellBiasTensor,</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  outputGateBiasTensor,</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  projectionWeightsTensor,</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  projectionBiasTensor,</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  inputLayerNormWeights,</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  forgetLayerNormWeights,</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  cellLayerNormWeights,</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  outputLayerNormWeights,</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  inputGateScratch,</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  cellScratch,</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  forgetGateScratch,</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  outputGateScratch,</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  inputGateScratchDecoder,</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  cellScratchDecoder,</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  forgetGateScratchDecoder,</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  outputGateScratchDecoder,</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  m_LayerNormEpsilon);</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> }</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> </div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> } <span class="comment">//namespace armnn</span></div><div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::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#l01131">Descriptors.hpp:1131</a></div></div> +<div class="ttc" id="_activation_8hpp_xhtml"><div class="ttname"><a href="_activation_8hpp.xhtml">Activation.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00191">Tensor.hpp:191</a></div></div> +<div class="ttc" id="_ref_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_ref_workload_utils_8hpp.xhtml">RefWorkloadUtils.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a952423703fa6b92f18d19df3995633b4"><div class="ttname"><a href="namespacearmnn.xhtml#a952423703fa6b92f18d19df3995633b4">armnn::LstmImpl</a></div><div class="ttdeci">void LstmImpl(const LstmDescriptor &descriptor, const TensorInfo &inputInfo, const TensorInfo &outputInfo, const TensorShape &inputToOutputWeightsShape, const TensorShape &recurrentToOutputWeightsShape, std::unique_ptr< Decoder< float >> &inputData, std::unique_ptr< Decoder< float >> &outputStateIn, std::unique_ptr< Decoder< float >> &cellStateIn, std::unique_ptr< Encoder< float >> &outputStateOut, std::unique_ptr< Encoder< float >> &cellStateOut, std::unique_ptr< Encoder< float >> &output, std::unique_ptr< Decoder< float >> &cellStateOutDecoder, std::unique_ptr< Decoder< float >> &outputDecoder, std::unique_ptr< Decoder< float >> &inputToInputWeightsTensor, std::unique_ptr< Decoder< float >> &inputToForgetWeightsTensor, std::unique_ptr< Decoder< float >> &inputToCellWeightsTensor, std::unique_ptr< Decoder< float >> &inputToOutputWeightsTensor, std::unique_ptr< Decoder< float >> &recurrentToInputWeightsTensor, std::unique_ptr< Decoder< float >> &recurrentToForgetWeightsTensor, std::unique_ptr< Decoder< float >> &recurrentToCellWeightsTensor, std::unique_ptr< Decoder< float >> &recurrentToOutputWeightsTensor, std::unique_ptr< Decoder< float >> &cellToInputWeightsTensor, std::unique_ptr< Decoder< float >> &cellToForgetWeightsTensor, std::unique_ptr< Decoder< float >> &cellToOutputWeightsTensor, std::unique_ptr< Decoder< float >> &inputGateBiasTensor, std::unique_ptr< Decoder< float >> &forgetGateBiasTensor, std::unique_ptr< Decoder< float >> &cellBiasTensor, std::unique_ptr< Decoder< float >> &outputGateBiasTensor, std::unique_ptr< Decoder< float >> &projectionWeightsTensor, std::unique_ptr< Decoder< float >> &projectionBiasTensor, std::unique_ptr< Decoder< float >> &inputLayerNormWeights, std::unique_ptr< Decoder< float >> &forgetLayerNormWeights, std::unique_ptr< Decoder< float >> &cellLayerNormWeights, std::unique_ptr< Decoder< float >> &outputLayerNormWeights, std::unique_ptr< Encoder< float >> &inputGateScratch, std::unique_ptr< Encoder< float >> &cellScratch, std::unique_ptr< Encoder< float >> &forgetGateScratch, std::unique_ptr< Encoder< float >> &outputGateScratch, std::unique_ptr< Decoder< float >> &inputGateScratchDecoder, std::unique_ptr< Decoder< float >> &cellScratchDecoder, std::unique_ptr< Decoder< float >> &forgetGateScratchDecoder, std::unique_ptr< Decoder< float >> &outputGateScratchDecoder, float layerNormEpsilon)</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_8cpp_source.xhtml#l00013">Lstm.cpp:13</a></div></div> +<div class="ttc" id="classarmnn_1_1_ref_lstm_workload_xhtml_a236c28ffd299dcfa88d6c0260e69f000"><div class="ttname"><a href="classarmnn_1_1_ref_lstm_workload.xhtml#a236c28ffd299dcfa88d6c0260e69f000">armnn::RefLstmWorkload::RefLstmWorkload</a></div><div class="ttdeci">RefLstmWorkload(const LstmQueueDescriptor &descriptor, const WorkloadInfo &info)</div><div class="ttdef"><b>Definition:</b> <a href="_ref_lstm_workload_8cpp_source.xhtml#l00017">RefLstmWorkload.cpp:17</a></div></div> +<div class="ttc" id="_lstm_utils_8cpp_xhtml_a8618ae0c77638e01069fdb0063cabb3f"><div class="ttname"><a href="_lstm_utils_8cpp.xhtml#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a></div><div class="ttdeci">std::unique_ptr< armnn::ScopedTensorHandle > AssignScopedTensorHandle(const armnn::ConstTensorHandle *ptr)</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_utils_8cpp_source.xhtml#l00299">LstmUtils.cpp:299</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.xhtml#l00006">01_00_quick_start.dox:6</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="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="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00066">WorkloadData.hpp:66</a></div></div> +<div class="ttc" id="_encoders_8hpp_xhtml"><div class="ttname"><a href="_encoders_8hpp.xhtml">Encoders.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1experimental_1_1_working_mem_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_descriptor.xhtml">armnn::experimental::WorkingMemDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_descriptor_8hpp_source.xhtml#l00018">WorkingMemDescriptor.hpp:18</a></div></div> +<div class="ttc" id="structarmnn_1_1experimental_1_1_working_mem_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::experimental::WorkingMemDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_descriptor_8hpp_source.xhtml#l00020">WorkingMemDescriptor.hpp:20</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_queue_descriptor.xhtml">armnn::LstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00432">WorkloadData.hpp:432</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< LstmQueueDescriptor >::m_Data</a></div><div class="ttdeci">LstmQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_8hpp_source.xhtml#l00081">Workload.hpp:81</a></div></div> +<div class="ttc" id="_ref_lstm_workload_8hpp_xhtml"><div class="ttname"><a href="_ref_lstm_workload_8hpp.xhtml">RefLstmWorkload.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_ref_lstm_workload_xhtml_a03726736f93bb28e11835f093f630a07"><div class="ttname"><a href="classarmnn_1_1_ref_lstm_workload.xhtml#a03726736f93bb28e11835f093f630a07">armnn::RefLstmWorkload::ExecuteAsync</a></div><div class="ttdeci">void ExecuteAsync(WorkingMemDescriptor &workingMemDescriptor) override</div><div class="ttdef"><b>Definition:</b> <a href="_ref_lstm_workload_8cpp_source.xhtml#l00047">RefLstmWorkload.cpp:47</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::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#l01129">Descriptors.hpp:1129</a></div></div> +<div class="ttc" id="classarmnn_1_1_ref_base_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_ref_base_workload.xhtml">armnn::RefBaseWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_ref_base_workload_8hpp_source.xhtml#l00013">RefBaseWorkload.hpp:13</a></div></div> +<div class="ttc" id="_decoders_8hpp_xhtml"><div class="ttname"><a href="_decoders_8hpp.xhtml">Decoders.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_ref_lstm_workload_xhtml_ae071e8822437c78baea75c3aef3a263a"><div class="ttname"><a href="classarmnn_1_1_ref_lstm_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">armnn::RefLstmWorkload::Execute</a></div><div class="ttdeci">void Execute() const override</div><div class="ttdef"><b>Definition:</b> <a href="_ref_lstm_workload_8cpp_source.xhtml#l00042">RefLstmWorkload.cpp:42</a></div></div> +<div class="ttc" id="_lstm_8hpp_xhtml"><div class="ttname"><a href="_lstm_8hpp.xhtml">Lstm.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::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#l01127">Descriptors.hpp:1127</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="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00027">WorkloadData.hpp:27</a></div></div> +<div class="ttc" id="structarmnn_1_1experimental_1_1_working_mem_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::experimental::WorkingMemDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_descriptor_8hpp_source.xhtml#l00021">WorkingMemDescriptor.hpp:21</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a4a8ec49f130084445d44297549254780"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">armnn::LstmDescriptor::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#l01133">Descriptors.hpp:1133</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00026">WorkloadData.hpp:26</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_af7ec4c0fa4375a45a70e4e31f3d8af47"><div class="ttname"><a href="namespacearmnn.xhtml#af7ec4c0fa4375a45a70e4e31f3d8af47">armnn::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)</div><div class="ttdoc">float32 helpers </div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_utils_8hpp_source.xhtml#l00026">RefWorkloadUtils.hpp:26</a></div></div> +<div class="ttc" id="_lstm_utils_8hpp_xhtml"><div class="ttname"><a href="_lstm_utils_8hpp.xhtml">LstmUtils.hpp</a></div></div> +</div><!-- fragment --></div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_efae4012d0e357ebeaba7d02491d70e5.xhtml">reference</a></li><li class="navelem"><a class="el" href="dir_d2f3b8e2e64df3181ebe92efcc0a3012.xhtml">workloads</a></li><li class="navelem"><a class="el" href="_ref_lstm_workload_8cpp.xhtml">RefLstmWorkload.cpp</a></li> + <li class="footer">Generated on Fri Jun 17 2022 13:20:24 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + </ul> +</div> +</body> +</html> |