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<div class="title">ConstTensorLayerVisitor.cpp</div>  </div>
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<a href="_const_tensor_layer_visitor_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_const_tensor_layer_visitor_8hpp.xhtml">ConstTensorLayerVisitor.hpp</a>&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_network_8hpp.xhtml">Network.hpp</a>&quot;</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;</div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="preprocessor">#include &lt;boost/test/unit_test.hpp&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;</div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;{</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;</div><div class="line"><a name="l00014"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_convolution2d_layer_visitor.xhtml#ac8b078bb166c52b45f04cae3e74557ad">   14</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_convolution2d_layer_visitor.xhtml#ac8b078bb166c52b45f04cae3e74557ad">TestConvolution2dLayerVisitor::CheckDescriptor</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a> &amp;convolution2dDescriptor)</div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;{</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>);</div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>);</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a>);</div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>);</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>);</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>);</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>);</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;}</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_depthwise_convolution2d_layer_visitor.xhtml#a8498083056c114343a16c556beea6057">   26</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_depthwise_convolution2d_layer_visitor.xhtml#a8498083056c114343a16c556beea6057">TestDepthwiseConvolution2dLayerVisitor::CheckDescriptor</a>(</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;        <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a>&amp; convolution2dDescriptor)</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;{</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>);</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>);</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a>);</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>);</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>);</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>);</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>);</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == convolution2dDescriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;}</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;</div><div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_fully_connected_layer_vistor.xhtml#ae48eafaa6a4bc4b7bde0a8824797c350">   39</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_fully_connected_layer_vistor.xhtml#ae48eafaa6a4bc4b7bde0a8824797c350">TestFullyConnectedLayerVistor::CheckDescriptor</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">FullyConnectedDescriptor</a>&amp; descriptor)</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;{</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> == descriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>);</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    BOOST_CHECK(m_Descriptor.m_TransposeWeightMatrix == descriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#a281fcaec86e17c97f7b8402633f6b55a">m_TransposeWeightMatrix</a>);</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;}</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;</div><div class="line"><a name="l00045"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_batch_normalization_layer_visitor.xhtml#abb0d5c2c24fc8c43d01e0fe503df2e93">   45</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_batch_normalization_layer_visitor.xhtml#abb0d5c2c24fc8c43d01e0fe503df2e93">TestBatchNormalizationLayerVisitor::CheckDescriptor</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml">BatchNormalizationDescriptor</a>&amp; descriptor)</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;{</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;    BOOST_CHECK(m_Descriptor.m_Eps == descriptor.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a>);</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;    BOOST_CHECK(m_Descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == descriptor.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;}</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;</div><div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_lstm_layer_visitor.xhtml#a7f36acbe9f04ed87e4bc8529f7ec0391">   51</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_lstm_layer_visitor.xhtml#a7f36acbe9f04ed87e4bc8529f7ec0391">TestLstmLayerVisitor::CheckDescriptor</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml">LstmDescriptor</a>&amp; descriptor)</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;{</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    BOOST_CHECK(m_Descriptor.m_ActivationFunc == descriptor.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a>);</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    BOOST_CHECK(m_Descriptor.m_ClippingThresCell == descriptor.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a>);</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    BOOST_CHECK(m_Descriptor.m_ClippingThresProj == descriptor.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">m_ClippingThresProj</a>);</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    BOOST_CHECK(m_Descriptor.m_CifgEnabled == descriptor.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>);</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    BOOST_CHECK(m_Descriptor.m_PeepholeEnabled == descriptor.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a>);</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    BOOST_CHECK(m_Descriptor.m_ProjectionEnabled == descriptor.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a>);</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;}</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;</div><div class="line"><a name="l00061"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_lstm_layer_visitor.xhtml#ac45b7720c3156ab1004a904da7d42b44">   61</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_lstm_layer_visitor.xhtml#ac45b7720c3156ab1004a904da7d42b44">TestLstmLayerVisitor::CheckConstTensorPtrs</a>(<span class="keyword">const</span> std::string&amp; name,</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;                                                <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>* expected,</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;                                                <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>* actual)</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;{</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    <span class="keywordflow">if</span> (expected == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    {</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;        BOOST_CHECK_MESSAGE(actual == <span class="keyword">nullptr</span>, name + <span class="stringliteral">&quot; actual should have been a nullptr&quot;</span>);</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    }</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    <span class="keywordflow">else</span></div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    {</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;        BOOST_CHECK_MESSAGE(actual != <span class="keyword">nullptr</span>, name + <span class="stringliteral">&quot; actual should have been set&quot;</span>);</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        <span class="keywordflow">if</span> (actual != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        {</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;            <a class="code" href="classarmnn_1_1_test_layer_visitor.xhtml#ab49c9a185af94e39ae9cd81aa8ec926c">CheckConstTensors</a>(*expected, *actual);</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;        }</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    }</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;}</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_lstm_layer_visitor.xhtml#a7607350d75bcb2ac402bba7494585f33">   79</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_lstm_layer_visitor.xhtml#a7607350d75bcb2ac402bba7494585f33">TestLstmLayerVisitor::CheckInputParameters</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_lstm_input_params.xhtml">LstmInputParams</a>&amp; inputParams)</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;{</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;ProjectionBias&quot;</span>, m_InputParams.m_ProjectionBias, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a>);</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;ProjectionWeights&quot;</span>, m_InputParams.m_ProjectionWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a>);</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;OutputGateBias&quot;</span>, m_InputParams.m_OutputGateBias, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a>);</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToInputWeights&quot;</span>,</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;        m_InputParams.m_InputToInputWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a>);</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToForgetWeights&quot;</span>,</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;        m_InputParams.m_InputToForgetWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a>);</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToCellWeights&quot;</span>, m_InputParams.m_InputToCellWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a>);</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    CheckConstTensorPtrs(</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;        <span class="stringliteral">&quot;InputToOutputWeights&quot;</span>, m_InputParams.m_InputToOutputWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a>);</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    CheckConstTensorPtrs(</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;        <span class="stringliteral">&quot;RecurrentToInputWeights&quot;</span>, m_InputParams.m_RecurrentToInputWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a>);</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    CheckConstTensorPtrs(</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;        <span class="stringliteral">&quot;RecurrentToForgetWeights&quot;</span>, m_InputParams.m_RecurrentToForgetWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a>);</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    CheckConstTensorPtrs(</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;        <span class="stringliteral">&quot;RecurrentToCellWeights&quot;</span>, m_InputParams.m_RecurrentToCellWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a>);</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;    CheckConstTensorPtrs(</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;        <span class="stringliteral">&quot;RecurrentToOutputWeights&quot;</span>, m_InputParams.m_RecurrentToOutputWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a>);</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    CheckConstTensorPtrs(</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;        <span class="stringliteral">&quot;CellToInputWeights&quot;</span>, m_InputParams.m_CellToInputWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a>);</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    CheckConstTensorPtrs(</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;        <span class="stringliteral">&quot;CellToForgetWeights&quot;</span>, m_InputParams.m_CellToForgetWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a>);</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;    CheckConstTensorPtrs(</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;        <span class="stringliteral">&quot;CellToOutputWeights&quot;</span>, m_InputParams.m_CellToOutputWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a>);</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputGateBias&quot;</span>, m_InputParams.m_InputGateBias, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a>);</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;ForgetGateBias&quot;</span>, m_InputParams.m_ForgetGateBias, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a>);</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;CellBias&quot;</span>, m_InputParams.m_CellBias, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a>);</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;}</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;</div><div class="line"><a name="l00110"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml#ac45b7720c3156ab1004a904da7d42b44">  110</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml#ac45b7720c3156ab1004a904da7d42b44">TestQLstmLayerVisitor::CheckConstTensorPtrs</a>(<span class="keyword">const</span> std::string&amp; name,</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;                                                 <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>* expected,</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;                                                 <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>* actual)</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;{</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;    <span class="keywordflow">if</span> (expected == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    {</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;        BOOST_CHECK_MESSAGE(actual == <span class="keyword">nullptr</span>, name + <span class="stringliteral">&quot; actual should have been a nullptr&quot;</span>);</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    }</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    <span class="keywordflow">else</span></div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    {</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;        BOOST_CHECK_MESSAGE(actual != <span class="keyword">nullptr</span>, name + <span class="stringliteral">&quot; actual should have been set&quot;</span>);</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;        <span class="keywordflow">if</span> (actual != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;        {</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;            <a class="code" href="classarmnn_1_1_test_layer_visitor.xhtml#ab49c9a185af94e39ae9cd81aa8ec926c">CheckConstTensors</a>(*expected, *actual);</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;        }</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    }</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;}</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;</div><div class="line"><a name="l00128"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml#a65b6d017f0b0b5e1e8b0d2e4590d9afb">  128</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml#a65b6d017f0b0b5e1e8b0d2e4590d9afb">TestQLstmLayerVisitor::CheckDescriptor</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml">QLstmDescriptor</a>&amp; descriptor)</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;{</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    BOOST_CHECK(m_Descriptor.m_CellClip == descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ac81fb0e66dc623dc37c77f219f53a6d3">m_CellClip</a>);</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    BOOST_CHECK(m_Descriptor.m_ProjectionClip == descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa6a518b65088f34803b3214334bdff61">m_ProjectionClip</a>);</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    BOOST_CHECK(m_Descriptor.m_CifgEnabled == descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>);</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    BOOST_CHECK(m_Descriptor.m_PeepholeEnabled == descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a>);</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    BOOST_CHECK(m_Descriptor.m_ProjectionEnabled == descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a>);</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;}</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;</div><div class="line"><a name="l00137"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml#a7607350d75bcb2ac402bba7494585f33">  137</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml#a7607350d75bcb2ac402bba7494585f33">TestQLstmLayerVisitor::CheckInputParameters</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_lstm_input_params.xhtml">LstmInputParams</a>&amp; inputParams)</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;{</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToInputWeights&quot;</span>,</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;                         m_InputParams.m_InputToInputWeights,</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a>);</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToForgetWeights&quot;</span>,</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;                         m_InputParams.m_InputToForgetWeights,</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a>);</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToCellWeights&quot;</span>,</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;                         m_InputParams.m_InputToCellWeights,</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a>);</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToOutputWeights&quot;</span>,</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;                         m_InputParams.m_InputToOutputWeights,</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a>);</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;RecurrentToInputWeights&quot;</span>,</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;                         m_InputParams.m_RecurrentToInputWeights,</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a>);</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;RecurrentToForgetWeights&quot;</span>,</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;                         m_InputParams.m_RecurrentToForgetWeights,</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a>);</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;RecurrentToCellWeights&quot;</span>,</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;                         m_InputParams.m_RecurrentToCellWeights,</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a>);</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;RecurrentToOutputWeights&quot;</span>,</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;                         m_InputParams.m_RecurrentToOutputWeights,</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a>);</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;CellToInputWeights&quot;</span>,</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;                         m_InputParams.m_CellToInputWeights,</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a>);</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;CellToForgetWeights&quot;</span>,</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;                         m_InputParams.m_CellToForgetWeights,</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a>);</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;CellToOutputWeights&quot;</span>,</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;                         m_InputParams.m_CellToOutputWeights,</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a>);</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;ProjectionWeights&quot;</span>, m_InputParams.m_ProjectionWeights, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a>);</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;ProjectionBias&quot;</span>, m_InputParams.m_ProjectionBias, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a>);</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputGateBias&quot;</span>,  m_InputParams.m_InputGateBias,  inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a>);</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;ForgetGateBias&quot;</span>, m_InputParams.m_ForgetGateBias, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a>);</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;CellBias&quot;</span>,       m_InputParams.m_CellBias,       inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a>);</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;OutputGateBias&quot;</span>, m_InputParams.m_OutputGateBias, inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a>);</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputLayerNormWeights&quot;</span>,</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;                         m_InputParams.m_InputLayerNormWeights,</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a0cd848f65ec31778d708852f0042fe37">m_InputLayerNormWeights</a>);</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;ForgetLayerNormWeights&quot;</span>,</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;                         m_InputParams.m_ForgetLayerNormWeights,</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#af0f796fba1a2be9c56b4c9ee534577ee">m_ForgetLayerNormWeights</a>);</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;CellLayerNormWeights&quot;</span>,</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;                         m_InputParams.m_CellLayerNormWeights,</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ad0b8c32bb5381f4cc999093ba3b98b43">m_CellLayerNormWeights</a>);</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;OutputLayerNormWeights&quot;</span>,</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;                         m_InputParams.m_OutputLayerNormWeights,</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a9b18daea2e9f42386055326fd016519a">m_OutputLayerNormWeights</a>);</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;}</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;</div><div class="line"><a name="l00208"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_quantized_lstm_layer_visitor.xhtml#ac45b7720c3156ab1004a904da7d42b44">  208</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_quantized_lstm_layer_visitor.xhtml#ac45b7720c3156ab1004a904da7d42b44">TestQuantizedLstmLayerVisitor::CheckConstTensorPtrs</a>(<span class="keyword">const</span> std::string&amp; name,</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;                                                         <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>* expected,</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;                                                         <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>* actual)</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;{</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;    <span class="keywordflow">if</span> (expected == <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;    {</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;        BOOST_CHECK_MESSAGE(actual == <span class="keyword">nullptr</span>, name + <span class="stringliteral">&quot; actual should have been a nullptr&quot;</span>);</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    }</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;    <span class="keywordflow">else</span></div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;    {</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;        BOOST_CHECK_MESSAGE(actual != <span class="keyword">nullptr</span>, name + <span class="stringliteral">&quot; actual should have been set&quot;</span>);</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;        <span class="keywordflow">if</span> (actual != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;        {</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;            <a class="code" href="classarmnn_1_1_test_layer_visitor.xhtml#ab49c9a185af94e39ae9cd81aa8ec926c">CheckConstTensors</a>(*expected, *actual);</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;        }</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;    }</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;}</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;</div><div class="line"><a name="l00226"></a><span class="lineno"><a class="line" href="classarmnn_1_1_test_quantized_lstm_layer_visitor.xhtml#ac6627007bd7a0b3a00cc690307840039">  226</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_test_quantized_lstm_layer_visitor.xhtml#ac6627007bd7a0b3a00cc690307840039">TestQuantizedLstmLayerVisitor::CheckInputParameters</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml">QuantizedLstmInputParams</a>&amp; inputParams)</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;{</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToInputWeights&quot;</span>,</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;                         m_InputParams.m_InputToInputWeights,</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a>);</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToForgetWeights&quot;</span>,</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;                         m_InputParams.m_InputToForgetWeights,</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a>);</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToCellWeights&quot;</span>,</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;                         m_InputParams.m_InputToCellWeights,</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a>);</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputToOutputWeights&quot;</span>,</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;                         m_InputParams.m_InputToOutputWeights,</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a>);</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;RecurrentToInputWeights&quot;</span>,</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;                         m_InputParams.m_RecurrentToInputWeights,</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a>);</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;RecurrentToForgetWeights&quot;</span>,</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;                         m_InputParams.m_RecurrentToForgetWeights,</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a>);</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;RecurrentToCellWeights&quot;</span>,</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;                         m_InputParams.m_RecurrentToCellWeights,</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a>);</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;RecurrentToOutputWeights&quot;</span>,</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;                         m_InputParams.m_RecurrentToOutputWeights,</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;                         inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a>);</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;    CheckConstTensorPtrs(<span class="stringliteral">&quot;InputGateBias&quot;</span>,  m_InputParams.m_InputGateBias,  inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a>);</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160; 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   <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 2;</div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 3;</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 1;</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 5;</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160; 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inputToOutputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l00748"></a><span class="lineno">  748</span>&#160;    std::vector&lt;unsigned int&gt; inputToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l00749"></a><span class="lineno">  749</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToOutputWeights(</div><div class="line"><a name="l00750"></a><span class="lineno">  750</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), inputToOutputWeightsData);</div><div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160;</div><div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;    std::vector&lt;float&gt; recurrentToForgetWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160; 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           4, outputGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), outputGateBiasData);</div><div class="line"><a name="l00853"></a><span class="lineno">  853</span>&#160;</div><div class="line"><a name="l00854"></a><span class="lineno">  854</span>&#160;    std::vector&lt;float&gt; inputToInputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l00855"></a><span class="lineno">  855</span>&#160;    std::vector&lt;unsigned int&gt; inputToInputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l00856"></a><span class="lineno">  856</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToInputWeights(</div><div class="line"><a name="l00857"></a><span class="lineno">  857</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToInputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), inputToInputWeightsData);</div><div class="line"><a name="l00858"></a><span class="lineno">  858</span>&#160;</div><div class="line"><a name="l00859"></a><span class="lineno">  859</span>&#160; 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   std::vector&lt;unsigned int&gt; recurrentToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l00928"></a><span class="lineno">  928</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToOutputWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l00929"></a><span class="lineno">  929</span>&#160;            4, recurrentToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), recurrentToOutputWeightsData);</div><div class="line"><a name="l00930"></a><span class="lineno">  930</span>&#160;</div><div class="line"><a name="l00931"></a><span class="lineno">  931</span>&#160;    std::vector&lt;float&gt; forgetGateBiasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l00932"></a><span class="lineno">  932</span>&#160;    std::vector&lt;unsigned int&gt; forgetGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l00933"></a><span class="lineno">  933</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l00934"></a><span class="lineno">  934</span>&#160;            4, forgetGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), forgetGateBiasData);</div><div class="line"><a name="l00935"></a><span class="lineno">  935</span>&#160;</div><div class="line"><a name="l00936"></a><span class="lineno">  936</span>&#160;    std::vector&lt;float&gt; cellBiasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l00937"></a><span class="lineno">  937</span>&#160;    std::vector&lt;unsigned int&gt; cellBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l00938"></a><span class="lineno">  938</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l00939"></a><span class="lineno">  939</span>&#160;            4, cellBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), cellBiasData);</div><div class="line"><a name="l00940"></a><span class="lineno">  940</span>&#160;</div><div class="line"><a name="l00941"></a><span class="lineno">  941</span>&#160;    std::vector&lt;float&gt; outputGateBiasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l00942"></a><span class="lineno">  942</span>&#160;    std::vector&lt;unsigned int&gt; outputGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l00943"></a><span class="lineno">  943</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> outputGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l00944"></a><span class="lineno">  944</span>&#160;            4, outputGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), outputGateBiasData);</div><div class="line"><a name="l00945"></a><span class="lineno">  945</span>&#160;</div><div class="line"><a name="l00946"></a><span class="lineno">  946</span>&#160;    std::vector&lt;float&gt; inputToInputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l00947"></a><span class="lineno">  947</span>&#160;    std::vector&lt;unsigned int&gt; inputToInputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l00948"></a><span class="lineno">  948</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToInputWeights(</div><div class="line"><a name="l00949"></a><span class="lineno">  949</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToInputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), inputToInputWeightsData);</div><div class="line"><a name="l00950"></a><span class="lineno">  950</span>&#160;</div><div class="line"><a name="l00951"></a><span class="lineno">  951</span>&#160;    std::vector&lt;float&gt; recurrentToInputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l00952"></a><span class="lineno">  952</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToInputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l00953"></a><span class="lineno">  953</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToInputWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l00954"></a><span class="lineno">  954</span>&#160;            4, recurrentToInputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), recurrentToInputWeightsData);</div><div class="line"><a name="l00955"></a><span class="lineno">  955</span>&#160;</div><div class="line"><a name="l00956"></a><span class="lineno">  956</span>&#160; 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           <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), inputToForgetWeightsData);</div><div class="line"><a name="l00998"></a><span class="lineno">  998</span>&#160;</div><div class="line"><a name="l00999"></a><span class="lineno">  999</span>&#160;    std::vector&lt;float&gt; inputToCellWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>&#160;    std::vector&lt;unsigned int&gt; inputToCellWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToCellWeights(</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToCellWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), inputToCellWeightsData);</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>&#160;</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>&#160; 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           4, outputGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), outputGateBiasData);</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>&#160;</div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>&#160;    std::vector&lt;float&gt; cellToForgetWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>&#160;    std::vector&lt;unsigned int&gt; cellToForgetWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellToForgetWeights(</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, cellToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), cellToForgetWeightsData);</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>&#160;</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>&#160; 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   <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>&#160;            4, cellBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), cellBiasData);</div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>&#160;</div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>&#160;    std::vector&lt;float&gt; outputGateBiasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>&#160;    std::vector&lt;unsigned int&gt; outputGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> outputGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>&#160;            4, outputGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), outputGateBiasData);</div><div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>&#160;</div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>&#160;    std::vector&lt;float&gt; cellToInputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>&#160;    std::vector&lt;unsigned int&gt; cellToInputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellToInputWeights(</div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, cellToInputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), cellToInputWeightsData);</div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>&#160;</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>&#160; 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inputToOutputWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>&#160;    std::vector&lt;unsigned int&gt; inputToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToOutputWeights(</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), inputToOutputWeightsData);</div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>&#160;</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>&#160;    std::vector&lt;float&gt; recurrentToForgetWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>&#160; 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           4, outputGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), outputGateBiasData);</div><div class="line"><a name="l01239"></a><span class="lineno"> 1239</span>&#160;</div><div class="line"><a name="l01240"></a><span class="lineno"> 1240</span>&#160;    std::vector&lt;float&gt; cellToForgetWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>&#160;    std::vector&lt;unsigned int&gt; cellToForgetWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellToForgetWeights(</div><div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, cellToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), cellToForgetWeightsData);</div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>&#160;</div><div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>&#160; 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   std::vector&lt;float&gt; recurrentToCellWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToCellWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToCellWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>&#160;            4, recurrentToCellWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), recurrentToCellWeightsData);</div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>&#160;</div><div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>&#160;    std::vector&lt;float&gt; 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           <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, projectionBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), projectionBiasData);</div><div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>&#160;</div><div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>&#160;    std::vector&lt;float&gt; projectionWeightsData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};</div><div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>&#160;    std::vector&lt;unsigned int&gt; projectionWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> projectionWeights(</div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, projectionWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), projectionWeightsData);</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>&#160;</div><div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>&#160; 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           4, recurrentToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToOutputWeightsData);</div><div class="line"><a name="l01483"></a><span class="lineno"> 1483</span>&#160;</div><div class="line"><a name="l01484"></a><span class="lineno"> 1484</span>&#160;    std::vector&lt;int32_t&gt; forgetGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>&#160;    std::vector&lt;unsigned int&gt; forgetGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>&#160;            4, forgetGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), forgetGateBiasData);</div><div class="line"><a name="l01488"></a><span class="lineno"> 1488</span>&#160;</div><div class="line"><a name="l01489"></a><span class="lineno"> 1489</span>&#160; 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   params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a>       = &amp;inputToCellWeights;</div><div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a>     = &amp;inputToOutputWeights;</div><div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &amp;recurrentToForgetWeights;</div><div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a>   = &amp;recurrentToCellWeights;</div><div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>&#160; 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           4, recurrentToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToOutputWeightsData);</div><div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>&#160;</div><div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>&#160;    std::vector&lt;int32_t&gt; forgetGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01558"></a><span class="lineno"> 1558</span>&#160;    std::vector&lt;unsigned int&gt; forgetGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>&#160;            4, forgetGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), forgetGateBiasData);</div><div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>&#160;</div><div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>&#160; 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           4, recurrentToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToOutputWeightsData);</div><div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>&#160;</div><div class="line"><a name="l01629"></a><span class="lineno"> 1629</span>&#160;    std::vector&lt;int32_t&gt; forgetGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01630"></a><span class="lineno"> 1630</span>&#160;    std::vector&lt;unsigned int&gt; forgetGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01632"></a><span class="lineno"> 1632</span>&#160;            4, forgetGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), forgetGateBiasData);</div><div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>&#160;</div><div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>&#160; 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   <a class="code" href="classarmnn_1_1_network_impl.xhtml">NetworkImpl</a> net;</div><div class="line"><a name="l01681"></a><span class="lineno"> 1681</span>&#160;</div><div class="line"><a name="l01682"></a><span class="lineno"> 1682</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <span class="keyword">const</span> layer = net.<a class="code" href="classarmnn_1_1_network_impl.xhtml#a2acbae0b9e98c94b843677484775c86a">AddQLstmLayer</a>(descriptor, params);</div><div class="line"><a name="l01683"></a><span class="lineno"> 1683</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a8c9198a992b02e61a6777329d487dde3">Accept</a>(visitor);</div><div class="line"><a name="l01684"></a><span class="lineno"> 1684</span>&#160;}</div><div class="line"><a name="l01685"></a><span class="lineno"> 1685</span>&#160;</div><div class="line"><a name="l01686"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a41beaa9f565de590a91640a87eee0fd1"> 1686</a></span>&#160;<a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CheckQLstmLayerCifgDisabledPeepholeEnabled)</div><div class="line"><a name="l01687"></a><span class="lineno"> 1687</span>&#160;{</div><div class="line"><a name="l01688"></a><span class="lineno"> 1688</span>&#160; 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   <span class="comment">// Basic params</span></div><div class="line"><a name="l01695"></a><span class="lineno"> 1695</span>&#160;    std::vector&lt;uint8_t&gt; inputToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01696"></a><span class="lineno"> 1696</span>&#160;    std::vector&lt;unsigned int&gt; inputToForgetWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01697"></a><span class="lineno"> 1697</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToForgetWeights(</div><div class="line"><a name="l01698"></a><span class="lineno"> 1698</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), inputToForgetWeightsData);</div><div class="line"><a name="l01699"></a><span class="lineno"> 1699</span>&#160;</div><div class="line"><a name="l01700"></a><span class="lineno"> 1700</span>&#160; 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recurrentToForgetWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01712"></a><span class="lineno"> 1712</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToForgetWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01713"></a><span class="lineno"> 1713</span>&#160;            4, recurrentToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToForgetWeightsData);</div><div class="line"><a name="l01714"></a><span class="lineno"> 1714</span>&#160;</div><div class="line"><a name="l01715"></a><span class="lineno"> 1715</span>&#160;    std::vector&lt;uint8_t&gt; recurrentToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01716"></a><span class="lineno"> 1716</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToCellWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01717"></a><span class="lineno"> 1717</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToCellWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01718"></a><span class="lineno"> 1718</span>&#160;            4, recurrentToCellWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToCellWeightsData);</div><div class="line"><a name="l01719"></a><span class="lineno"> 1719</span>&#160;</div><div class="line"><a name="l01720"></a><span class="lineno"> 1720</span>&#160;    std::vector&lt;uint8_t&gt; recurrentToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01721"></a><span class="lineno"> 1721</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01722"></a><span class="lineno"> 1722</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToOutputWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01723"></a><span class="lineno"> 1723</span>&#160;            4, recurrentToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToOutputWeightsData);</div><div class="line"><a name="l01724"></a><span class="lineno"> 1724</span>&#160;</div><div class="line"><a name="l01725"></a><span class="lineno"> 1725</span>&#160;    std::vector&lt;int32_t&gt; forgetGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01726"></a><span class="lineno"> 1726</span>&#160;    std::vector&lt;unsigned int&gt; forgetGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01727"></a><span class="lineno"> 1727</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01728"></a><span class="lineno"> 1728</span>&#160;            4, forgetGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), forgetGateBiasData);</div><div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>&#160;</div><div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>&#160; 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           <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, cellToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>), cellToForgetWeightsData);</div><div class="line"><a name="l01766"></a><span class="lineno"> 1766</span>&#160;</div><div class="line"><a name="l01767"></a><span class="lineno"> 1767</span>&#160;    std::vector&lt;int16_t&gt; cellToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01768"></a><span class="lineno"> 1768</span>&#160;    std::vector&lt;unsigned int&gt; cellToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01769"></a><span class="lineno"> 1769</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellToOutputWeights(</div><div class="line"><a name="l01770"></a><span class="lineno"> 1770</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, cellToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>), cellToOutputWeightsData);</div><div class="line"><a name="l01771"></a><span class="lineno"> 1771</span>&#160;</div><div class="line"><a name="l01772"></a><span class="lineno"> 1772</span>&#160; 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   params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &amp;recurrentToForgetWeights;</div><div class="line"><a name="l01779"></a><span class="lineno"> 1779</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a>   = &amp;recurrentToCellWeights;</div><div class="line"><a name="l01780"></a><span class="lineno"> 1780</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &amp;recurrentToOutputWeights;</div><div class="line"><a name="l01781"></a><span class="lineno"> 1781</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a>           = &amp;forgetGateBias;</div><div class="line"><a name="l01782"></a><span class="lineno"> 1782</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a>                 = &amp;cellBias;</div><div class="line"><a name="l01783"></a><span class="lineno"> 1783</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a>           = &amp;outputGateBias;</div><div class="line"><a name="l01784"></a><span class="lineno"> 1784</span>&#160;</div><div class="line"><a name="l01785"></a><span class="lineno"> 1785</span>&#160;    <span class="comment">// CIFG disabled params</span></div><div class="line"><a name="l01786"></a><span class="lineno"> 1786</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a>     = &amp;inputToInputWeights;</div><div class="line"><a name="l01787"></a><span class="lineno"> 1787</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &amp;recurrentToInputWeights;</div><div class="line"><a name="l01788"></a><span class="lineno"> 1788</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a>           = &amp;inputGateBias;</div><div class="line"><a name="l01789"></a><span class="lineno"> 1789</span>&#160;</div><div class="line"><a name="l01790"></a><span class="lineno"> 1790</span>&#160;    <span class="comment">// Peephole enabled, CIFG disabled params</span></div><div class="line"><a name="l01791"></a><span class="lineno"> 1791</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a484bafa2f8453a7c5a4a00b92a61b006">m_CellToInputWeights</a>  = &amp;cellToInputWeights;</div><div class="line"><a name="l01792"></a><span class="lineno"> 1792</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a> = &amp;cellToForgetWeights;</div><div class="line"><a name="l01793"></a><span class="lineno"> 1793</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a> = &amp;cellToOutputWeights;</div><div class="line"><a name="l01794"></a><span class="lineno"> 1794</span>&#160;</div><div class="line"><a name="l01795"></a><span class="lineno"> 1795</span>&#160; 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           4, recurrentToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToOutputWeightsData);</div><div class="line"><a name="l01841"></a><span class="lineno"> 1841</span>&#160;</div><div class="line"><a name="l01842"></a><span class="lineno"> 1842</span>&#160;    std::vector&lt;int32_t&gt; forgetGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01843"></a><span class="lineno"> 1843</span>&#160;    std::vector&lt;unsigned int&gt; forgetGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01844"></a><span class="lineno"> 1844</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01845"></a><span class="lineno"> 1845</span>&#160;            4, forgetGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), forgetGateBiasData);</div><div class="line"><a name="l01846"></a><span class="lineno"> 1846</span>&#160;</div><div class="line"><a name="l01847"></a><span class="lineno"> 1847</span>&#160; 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cellToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01865"></a><span class="lineno"> 1865</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellToOutputWeights(</div><div class="line"><a name="l01866"></a><span class="lineno"> 1866</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, cellToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>), cellToOutputWeightsData);</div><div class="line"><a name="l01867"></a><span class="lineno"> 1867</span>&#160;</div><div class="line"><a name="l01868"></a><span class="lineno"> 1868</span>&#160;    <a class="code" href="structarmnn_1_1_lstm_input_params.xhtml">LstmInputParams</a> params;</div><div class="line"><a name="l01869"></a><span class="lineno"> 1869</span>&#160;</div><div class="line"><a name="l01870"></a><span class="lineno"> 1870</span>&#160;    <span class="comment">// Basic params</span></div><div class="line"><a name="l01871"></a><span class="lineno"> 1871</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a>     = &amp;inputToForgetWeights;</div><div class="line"><a name="l01872"></a><span class="lineno"> 1872</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a>       = &amp;inputToCellWeights;</div><div class="line"><a name="l01873"></a><span class="lineno"> 1873</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a>     = &amp;inputToOutputWeights;</div><div class="line"><a name="l01874"></a><span class="lineno"> 1874</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &amp;recurrentToForgetWeights;</div><div class="line"><a name="l01875"></a><span class="lineno"> 1875</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a>   = &amp;recurrentToCellWeights;</div><div class="line"><a name="l01876"></a><span class="lineno"> 1876</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &amp;recurrentToOutputWeights;</div><div class="line"><a name="l01877"></a><span class="lineno"> 1877</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a>           = &amp;forgetGateBias;</div><div class="line"><a name="l01878"></a><span class="lineno"> 1878</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a>                 = &amp;cellBias;</div><div class="line"><a name="l01879"></a><span class="lineno"> 1879</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a>           = &amp;outputGateBias;</div><div class="line"><a name="l01880"></a><span class="lineno"> 1880</span>&#160;</div><div class="line"><a name="l01881"></a><span class="lineno"> 1881</span>&#160;    <span class="comment">// Peephole enabled and CIFG enabled params</span></div><div class="line"><a name="l01882"></a><span class="lineno"> 1882</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a35b112e30c3eb153806a2a8c16d178e3">m_CellToForgetWeights</a> = &amp;cellToForgetWeights;</div><div class="line"><a name="l01883"></a><span class="lineno"> 1883</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#afe204ca375b74e9a72640c9227918d0a">m_CellToOutputWeights</a> = &amp;cellToOutputWeights;</div><div class="line"><a name="l01884"></a><span class="lineno"> 1884</span>&#160;</div><div class="line"><a name="l01885"></a><span class="lineno"> 1885</span>&#160;    <a class="code" href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml">TestQLstmLayerVisitor</a> visitor(descriptor, params);</div><div class="line"><a name="l01886"></a><span class="lineno"> 1886</span>&#160;</div><div class="line"><a name="l01887"></a><span class="lineno"> 1887</span>&#160;    <a class="code" href="classarmnn_1_1_network_impl.xhtml">NetworkImpl</a> net;</div><div class="line"><a name="l01888"></a><span class="lineno"> 1888</span>&#160;</div><div class="line"><a name="l01889"></a><span class="lineno"> 1889</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <span class="keyword">const</span> layer = net.<a class="code" href="classarmnn_1_1_network_impl.xhtml#a2acbae0b9e98c94b843677484775c86a">AddQLstmLayer</a>(descriptor, params);</div><div class="line"><a name="l01890"></a><span class="lineno"> 1890</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a8c9198a992b02e61a6777329d487dde3">Accept</a>(visitor);</div><div class="line"><a name="l01891"></a><span class="lineno"> 1891</span>&#160;}</div><div class="line"><a name="l01892"></a><span class="lineno"> 1892</span>&#160;</div><div class="line"><a name="l01893"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a0f40756a484811159503716f60d6734e"> 1893</a></span>&#160;<a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CheckQLstmLayerProjectionEnabled)</div><div class="line"><a name="l01894"></a><span class="lineno"> 1894</span>&#160;{</div><div class="line"><a name="l01895"></a><span class="lineno"> 1895</span>&#160;    <a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml">QLstmDescriptor</a> descriptor;</div><div class="line"><a name="l01896"></a><span class="lineno"> 1896</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa6a518b65088f34803b3214334bdff61">m_ProjectionClip</a> = 0.5f;</div><div class="line"><a name="l01897"></a><span class="lineno"> 1897</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ac81fb0e66dc623dc37c77f219f53a6d3">m_CellClip</a> = 0.3f;</div><div class="line"><a name="l01898"></a><span class="lineno"> 1898</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01899"></a><span class="lineno"> 1899</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01900"></a><span class="lineno"> 1900</span>&#160;</div><div class="line"><a name="l01901"></a><span class="lineno"> 1901</span>&#160;    <span class="comment">// Basic params ONLY</span></div><div class="line"><a name="l01902"></a><span class="lineno"> 1902</span>&#160;    std::vector&lt;uint8_t&gt; inputToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01903"></a><span class="lineno"> 1903</span>&#160;    std::vector&lt;unsigned int&gt; inputToForgetWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01904"></a><span class="lineno"> 1904</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToForgetWeights(</div><div class="line"><a name="l01905"></a><span class="lineno"> 1905</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), inputToForgetWeightsData);</div><div class="line"><a name="l01906"></a><span class="lineno"> 1906</span>&#160;</div><div class="line"><a name="l01907"></a><span class="lineno"> 1907</span>&#160;    std::vector&lt;uint8_t&gt; inputToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01908"></a><span class="lineno"> 1908</span>&#160;    std::vector&lt;unsigned int&gt; inputToCellWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01909"></a><span class="lineno"> 1909</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToCellWeights(</div><div class="line"><a name="l01910"></a><span class="lineno"> 1910</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToCellWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), inputToCellWeightsData);</div><div class="line"><a name="l01911"></a><span class="lineno"> 1911</span>&#160;</div><div class="line"><a name="l01912"></a><span class="lineno"> 1912</span>&#160;    std::vector&lt;uint8_t&gt; inputToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01913"></a><span class="lineno"> 1913</span>&#160;    std::vector&lt;unsigned int&gt; inputToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01914"></a><span class="lineno"> 1914</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToOutputWeights(</div><div class="line"><a name="l01915"></a><span class="lineno"> 1915</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), inputToOutputWeightsData);</div><div class="line"><a name="l01916"></a><span class="lineno"> 1916</span>&#160;</div><div class="line"><a name="l01917"></a><span class="lineno"> 1917</span>&#160;    std::vector&lt;uint8_t&gt; recurrentToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01918"></a><span class="lineno"> 1918</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToForgetWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01919"></a><span class="lineno"> 1919</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToForgetWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01920"></a><span class="lineno"> 1920</span>&#160;            4, recurrentToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToForgetWeightsData);</div><div class="line"><a name="l01921"></a><span class="lineno"> 1921</span>&#160;</div><div class="line"><a name="l01922"></a><span class="lineno"> 1922</span>&#160;    std::vector&lt;uint8_t&gt; recurrentToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01923"></a><span class="lineno"> 1923</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToCellWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01924"></a><span class="lineno"> 1924</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToCellWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01925"></a><span class="lineno"> 1925</span>&#160;            4, recurrentToCellWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToCellWeightsData);</div><div class="line"><a name="l01926"></a><span class="lineno"> 1926</span>&#160;</div><div class="line"><a name="l01927"></a><span class="lineno"> 1927</span>&#160;    std::vector&lt;uint8_t&gt; recurrentToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01928"></a><span class="lineno"> 1928</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01929"></a><span class="lineno"> 1929</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToOutputWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01930"></a><span class="lineno"> 1930</span>&#160;            4, recurrentToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToOutputWeightsData);</div><div class="line"><a name="l01931"></a><span class="lineno"> 1931</span>&#160;</div><div class="line"><a name="l01932"></a><span class="lineno"> 1932</span>&#160;    std::vector&lt;int32_t&gt; forgetGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01933"></a><span class="lineno"> 1933</span>&#160;    std::vector&lt;unsigned int&gt; forgetGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01934"></a><span class="lineno"> 1934</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01935"></a><span class="lineno"> 1935</span>&#160;            4, forgetGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), forgetGateBiasData);</div><div class="line"><a name="l01936"></a><span class="lineno"> 1936</span>&#160;</div><div class="line"><a name="l01937"></a><span class="lineno"> 1937</span>&#160;    std::vector&lt;int32_t&gt; cellBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01938"></a><span class="lineno"> 1938</span>&#160;    std::vector&lt;unsigned int&gt; cellBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01939"></a><span class="lineno"> 1939</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01940"></a><span class="lineno"> 1940</span>&#160;            4, cellBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), cellBiasData);</div><div class="line"><a name="l01941"></a><span class="lineno"> 1941</span>&#160;</div><div class="line"><a name="l01942"></a><span class="lineno"> 1942</span>&#160;    std::vector&lt;int32_t&gt; outputGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01943"></a><span class="lineno"> 1943</span>&#160;    std::vector&lt;unsigned int&gt; outputGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01944"></a><span class="lineno"> 1944</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> outputGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01945"></a><span class="lineno"> 1945</span>&#160;            4, outputGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), outputGateBiasData);</div><div class="line"><a name="l01946"></a><span class="lineno"> 1946</span>&#160;</div><div class="line"><a name="l01947"></a><span class="lineno"> 1947</span>&#160;    <span class="comment">// Projection enabled params</span></div><div class="line"><a name="l01948"></a><span class="lineno"> 1948</span>&#160;    std::vector&lt;uint8_t&gt; projectionWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01949"></a><span class="lineno"> 1949</span>&#160;    std::vector&lt;unsigned int&gt; projectionWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01950"></a><span class="lineno"> 1950</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> projectionWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01951"></a><span class="lineno"> 1951</span>&#160;            4, projectionWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), projectionWeightsData);</div><div class="line"><a name="l01952"></a><span class="lineno"> 1952</span>&#160;</div><div class="line"><a name="l01953"></a><span class="lineno"> 1953</span>&#160;    std::vector&lt;int32_t&gt; projectionBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01954"></a><span class="lineno"> 1954</span>&#160;    std::vector&lt;unsigned int&gt; projectionBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01955"></a><span class="lineno"> 1955</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> projectionBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l01956"></a><span class="lineno"> 1956</span>&#160;            4, projectionBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), projectionBiasData);</div><div class="line"><a name="l01957"></a><span class="lineno"> 1957</span>&#160;</div><div class="line"><a name="l01958"></a><span class="lineno"> 1958</span>&#160;    <a class="code" href="structarmnn_1_1_lstm_input_params.xhtml">LstmInputParams</a> params;</div><div class="line"><a name="l01959"></a><span class="lineno"> 1959</span>&#160;</div><div class="line"><a name="l01960"></a><span class="lineno"> 1960</span>&#160;    <span class="comment">// Basic params</span></div><div class="line"><a name="l01961"></a><span class="lineno"> 1961</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a>     = &amp;inputToForgetWeights;</div><div class="line"><a name="l01962"></a><span class="lineno"> 1962</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a>       = &amp;inputToCellWeights;</div><div class="line"><a name="l01963"></a><span class="lineno"> 1963</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a>     = &amp;inputToOutputWeights;</div><div class="line"><a name="l01964"></a><span class="lineno"> 1964</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &amp;recurrentToForgetWeights;</div><div class="line"><a name="l01965"></a><span class="lineno"> 1965</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a>   = &amp;recurrentToCellWeights;</div><div class="line"><a name="l01966"></a><span class="lineno"> 1966</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &amp;recurrentToOutputWeights;</div><div class="line"><a name="l01967"></a><span class="lineno"> 1967</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a>           = &amp;forgetGateBias;</div><div class="line"><a name="l01968"></a><span class="lineno"> 1968</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a>                 = &amp;cellBias;</div><div class="line"><a name="l01969"></a><span class="lineno"> 1969</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a>           = &amp;outputGateBias;</div><div class="line"><a name="l01970"></a><span class="lineno"> 1970</span>&#160;</div><div class="line"><a name="l01971"></a><span class="lineno"> 1971</span>&#160;    <span class="comment">// Projection enabled params</span></div><div class="line"><a name="l01972"></a><span class="lineno"> 1972</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#ab03e6e1514f74427916c892f473fe04c">m_ProjectionWeights</a> = &amp;projectionWeights;</div><div class="line"><a name="l01973"></a><span class="lineno"> 1973</span>&#160;    params.<a class="code" href="structarmnn_1_1_lstm_input_params.xhtml#a44b0e6b16708df7f0d2bbab141688aaa">m_ProjectionBias</a>    = &amp;projectionBias;</div><div class="line"><a name="l01974"></a><span class="lineno"> 1974</span>&#160;</div><div class="line"><a name="l01975"></a><span class="lineno"> 1975</span>&#160;    <a class="code" href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml">TestQLstmLayerVisitor</a> visitor(descriptor, params);</div><div class="line"><a name="l01976"></a><span class="lineno"> 1976</span>&#160;</div><div class="line"><a name="l01977"></a><span class="lineno"> 1977</span>&#160;    <a class="code" href="classarmnn_1_1_network_impl.xhtml">NetworkImpl</a> net;</div><div class="line"><a name="l01978"></a><span class="lineno"> 1978</span>&#160;</div><div class="line"><a name="l01979"></a><span class="lineno"> 1979</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <span class="keyword">const</span> layer = net.<a class="code" href="classarmnn_1_1_network_impl.xhtml#a2acbae0b9e98c94b843677484775c86a">AddQLstmLayer</a>(descriptor, params);</div><div class="line"><a name="l01980"></a><span class="lineno"> 1980</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a8c9198a992b02e61a6777329d487dde3">Accept</a>(visitor);</div><div class="line"><a name="l01981"></a><span class="lineno"> 1981</span>&#160;}</div><div class="line"><a name="l01982"></a><span class="lineno"> 1982</span>&#160;</div><div class="line"><a name="l01983"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a3bfa5a466675be46ba44528fea57e161"> 1983</a></span>&#160;<a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CheckQLstmLayerCifgDisabledLayerNormEnabled)</div><div class="line"><a name="l01984"></a><span class="lineno"> 1984</span>&#160;{</div><div class="line"><a name="l01985"></a><span class="lineno"> 1985</span>&#160;    <a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml">QLstmDescriptor</a> descriptor;</div><div class="line"><a name="l01986"></a><span class="lineno"> 1986</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#aa6a518b65088f34803b3214334bdff61">m_ProjectionClip</a> = 0.5f;</div><div class="line"><a name="l01987"></a><span class="lineno"> 1987</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ac81fb0e66dc623dc37c77f219f53a6d3">m_CellClip</a> = 0.3f;</div><div class="line"><a name="l01988"></a><span class="lineno"> 1988</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01989"></a><span class="lineno"> 1989</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01990"></a><span class="lineno"> 1990</span>&#160;</div><div class="line"><a name="l01991"></a><span class="lineno"> 1991</span>&#160;    <span class="comment">// Basic params</span></div><div class="line"><a name="l01992"></a><span class="lineno"> 1992</span>&#160;    std::vector&lt;uint8_t&gt; inputToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01993"></a><span class="lineno"> 1993</span>&#160;    std::vector&lt;unsigned int&gt; inputToForgetWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01994"></a><span class="lineno"> 1994</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToForgetWeights(</div><div class="line"><a name="l01995"></a><span class="lineno"> 1995</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), inputToForgetWeightsData);</div><div class="line"><a name="l01996"></a><span class="lineno"> 1996</span>&#160;</div><div class="line"><a name="l01997"></a><span class="lineno"> 1997</span>&#160;    std::vector&lt;uint8_t&gt; inputToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l01998"></a><span class="lineno"> 1998</span>&#160;    std::vector&lt;unsigned int&gt; inputToCellWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l01999"></a><span class="lineno"> 1999</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToCellWeights(</div><div class="line"><a name="l02000"></a><span class="lineno"> 2000</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToCellWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), inputToCellWeightsData);</div><div class="line"><a name="l02001"></a><span class="lineno"> 2001</span>&#160;</div><div class="line"><a name="l02002"></a><span class="lineno"> 2002</span>&#160;    std::vector&lt;uint8_t&gt; inputToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02003"></a><span class="lineno"> 2003</span>&#160;    std::vector&lt;unsigned int&gt; inputToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02004"></a><span class="lineno"> 2004</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToOutputWeights(</div><div class="line"><a name="l02005"></a><span class="lineno"> 2005</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), inputToOutputWeightsData);</div><div class="line"><a name="l02006"></a><span class="lineno"> 2006</span>&#160;</div><div class="line"><a name="l02007"></a><span class="lineno"> 2007</span>&#160;    std::vector&lt;uint8_t&gt; recurrentToForgetWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02008"></a><span class="lineno"> 2008</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToForgetWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02009"></a><span class="lineno"> 2009</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToForgetWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02010"></a><span class="lineno"> 2010</span>&#160;            4, recurrentToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToForgetWeightsData);</div><div class="line"><a name="l02011"></a><span class="lineno"> 2011</span>&#160;</div><div class="line"><a name="l02012"></a><span class="lineno"> 2012</span>&#160;    std::vector&lt;uint8_t&gt; recurrentToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02013"></a><span class="lineno"> 2013</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToCellWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02014"></a><span class="lineno"> 2014</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToCellWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02015"></a><span class="lineno"> 2015</span>&#160;            4, recurrentToCellWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToCellWeightsData);</div><div class="line"><a name="l02016"></a><span class="lineno"> 2016</span>&#160;</div><div class="line"><a name="l02017"></a><span class="lineno"> 2017</span>&#160;    std::vector&lt;uint8_t&gt; recurrentToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02018"></a><span class="lineno"> 2018</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02019"></a><span class="lineno"> 2019</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToOutputWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02020"></a><span class="lineno"> 2020</span>&#160;            4, recurrentToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToOutputWeightsData);</div><div class="line"><a name="l02021"></a><span class="lineno"> 2021</span>&#160;</div><div class="line"><a name="l02022"></a><span class="lineno"> 2022</span>&#160;    std::vector&lt;int32_t&gt; forgetGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02023"></a><span class="lineno"> 2023</span>&#160;    std::vector&lt;unsigned int&gt; forgetGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02024"></a><span class="lineno"> 2024</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02025"></a><span class="lineno"> 2025</span>&#160;            4, forgetGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), forgetGateBiasData);</div><div class="line"><a name="l02026"></a><span class="lineno"> 2026</span>&#160;</div><div class="line"><a name="l02027"></a><span class="lineno"> 2027</span>&#160;    std::vector&lt;int32_t&gt; cellBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02028"></a><span class="lineno"> 2028</span>&#160;    std::vector&lt;unsigned int&gt; cellBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02029"></a><span class="lineno"> 2029</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02030"></a><span class="lineno"> 2030</span>&#160;            4, cellBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), cellBiasData);</div><div class="line"><a name="l02031"></a><span class="lineno"> 2031</span>&#160;</div><div class="line"><a name="l02032"></a><span class="lineno"> 2032</span>&#160;    std::vector&lt;int32_t&gt; outputGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02033"></a><span class="lineno"> 2033</span>&#160;    std::vector&lt;unsigned int&gt; outputGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02034"></a><span class="lineno"> 2034</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> outputGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02035"></a><span class="lineno"> 2035</span>&#160;            4, outputGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), outputGateBiasData);</div><div class="line"><a name="l02036"></a><span class="lineno"> 2036</span>&#160;</div><div class="line"><a name="l02037"></a><span class="lineno"> 2037</span>&#160;    <span class="comment">// CIFG disabled params</span></div><div class="line"><a name="l02038"></a><span class="lineno"> 2038</span>&#160;    std::vector&lt;uint8_t&gt; inputToInputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02039"></a><span class="lineno"> 2039</span>&#160; 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recurrentToInputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02045"></a><span class="lineno"> 2045</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToInputWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02046"></a><span class="lineno"> 2046</span>&#160;            4, recurrentToInputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToInputWeightsData);</div><div class="line"><a name="l02047"></a><span class="lineno"> 2047</span>&#160;</div><div class="line"><a name="l02048"></a><span class="lineno"> 2048</span>&#160;    std::vector&lt;int32_t&gt; inputGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02049"></a><span class="lineno"> 2049</span>&#160;    std::vector&lt;unsigned int&gt; inputGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02050"></a><span class="lineno"> 2050</span>&#160; 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           <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, forgetLayerNormWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>), forgetLayerNormWeightsData);</div><div class="line"><a name="l02063"></a><span class="lineno"> 2063</span>&#160;</div><div class="line"><a name="l02064"></a><span class="lineno"> 2064</span>&#160;    std::vector&lt;int16_t&gt; cellLayerNormWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02065"></a><span class="lineno"> 2065</span>&#160;    std::vector&lt;unsigned int&gt; cellLayerNormWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02066"></a><span class="lineno"> 2066</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellLayerNormWeights(</div><div class="line"><a name="l02067"></a><span class="lineno"> 2067</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, cellLayerNormWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>), cellLayerNormWeightsData);</div><div class="line"><a name="l02068"></a><span class="lineno"> 2068</span>&#160;</div><div class="line"><a name="l02069"></a><span class="lineno"> 2069</span>&#160; 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inputToCellWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02121"></a><span class="lineno"> 2121</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToCellWeights(</div><div class="line"><a name="l02122"></a><span class="lineno"> 2122</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputToCellWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), inputToCellWeightsData);</div><div class="line"><a name="l02123"></a><span class="lineno"> 2123</span>&#160;</div><div class="line"><a name="l02124"></a><span class="lineno"> 2124</span>&#160;    std::vector&lt;uint8_t&gt; inputToOutputWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02125"></a><span class="lineno"> 2125</span>&#160;    std::vector&lt;unsigned int&gt; inputToOutputWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02126"></a><span class="lineno"> 2126</span>&#160; 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           4, recurrentToForgetWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToForgetWeightsData);</div><div class="line"><a name="l02139"></a><span class="lineno"> 2139</span>&#160;</div><div class="line"><a name="l02140"></a><span class="lineno"> 2140</span>&#160;    std::vector&lt;uint8_t&gt; recurrentToCellWeightsData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02141"></a><span class="lineno"> 2141</span>&#160;    std::vector&lt;unsigned int&gt; recurrentToCellWeightsDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02142"></a><span class="lineno"> 2142</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToCellWeights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02143"></a><span class="lineno"> 2143</span>&#160;            4, recurrentToCellWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>), recurrentToCellWeightsData);</div><div class="line"><a name="l02144"></a><span class="lineno"> 2144</span>&#160;</div><div class="line"><a name="l02145"></a><span class="lineno"> 2145</span>&#160; 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           4, outputGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), outputGateBiasData);</div><div class="line"><a name="l02170"></a><span class="lineno"> 2170</span>&#160;</div><div class="line"><a name="l02171"></a><span class="lineno"> 2171</span>&#160;    <a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml">QuantizedLstmInputParams</a> params;</div><div class="line"><a name="l02172"></a><span class="lineno"> 2172</span>&#160;</div><div class="line"><a name="l02173"></a><span class="lineno"> 2173</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &amp;inputToInputWeights;</div><div class="line"><a name="l02174"></a><span class="lineno"> 2174</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &amp;inputToForgetWeights;</div><div class="line"><a name="l02175"></a><span class="lineno"> 2175</span>&#160; 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           4, recurrentToOutputWeightsDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>), recurrentToOutputWeightsData);</div><div class="line"><a name="l02239"></a><span class="lineno"> 2239</span>&#160;</div><div class="line"><a name="l02240"></a><span class="lineno"> 2240</span>&#160;</div><div class="line"><a name="l02241"></a><span class="lineno"> 2241</span>&#160;    std::vector&lt;int32_t&gt; inputGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02242"></a><span class="lineno"> 2242</span>&#160;    std::vector&lt;unsigned int&gt; inputGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02243"></a><span class="lineno"> 2243</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputGateBias(</div><div class="line"><a name="l02244"></a><span class="lineno"> 2244</span>&#160;            <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(4, inputGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), inputGateBiasData);</div><div class="line"><a name="l02245"></a><span class="lineno"> 2245</span>&#160;</div><div class="line"><a name="l02246"></a><span class="lineno"> 2246</span>&#160;    std::vector&lt;int32_t&gt; forgetGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02247"></a><span class="lineno"> 2247</span>&#160;    std::vector&lt;unsigned int&gt; forgetGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02248"></a><span class="lineno"> 2248</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02249"></a><span class="lineno"> 2249</span>&#160;            4, forgetGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), forgetGateBiasData);</div><div class="line"><a name="l02250"></a><span class="lineno"> 2250</span>&#160;</div><div class="line"><a name="l02251"></a><span class="lineno"> 2251</span>&#160;    std::vector&lt;int32_t&gt; cellBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02252"></a><span class="lineno"> 2252</span>&#160;    std::vector&lt;unsigned int&gt; cellBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02253"></a><span class="lineno"> 2253</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02254"></a><span class="lineno"> 2254</span>&#160;            4, cellBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), cellBiasData);</div><div class="line"><a name="l02255"></a><span class="lineno"> 2255</span>&#160;</div><div class="line"><a name="l02256"></a><span class="lineno"> 2256</span>&#160;    std::vector&lt;int32_t&gt; outputGateBiasData = {1, 2, 3, 4, 5, 6, 7, 8, 9};</div><div class="line"><a name="l02257"></a><span class="lineno"> 2257</span>&#160;    std::vector&lt;unsigned int&gt; outputGateBiasDimensions = {1, 1, 3, 3};</div><div class="line"><a name="l02258"></a><span class="lineno"> 2258</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> outputGateBias(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(</div><div class="line"><a name="l02259"></a><span class="lineno"> 2259</span>&#160;            4, outputGateBiasDimensions.data(), <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>), outputGateBiasData);</div><div class="line"><a name="l02260"></a><span class="lineno"> 2260</span>&#160;</div><div class="line"><a name="l02261"></a><span class="lineno"> 2261</span>&#160;    <a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml">QuantizedLstmInputParams</a> params;</div><div class="line"><a name="l02262"></a><span class="lineno"> 2262</span>&#160;</div><div class="line"><a name="l02263"></a><span class="lineno"> 2263</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &amp;inputToInputWeights;</div><div class="line"><a name="l02264"></a><span class="lineno"> 2264</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &amp;inputToForgetWeights;</div><div class="line"><a name="l02265"></a><span class="lineno"> 2265</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &amp;inputToCellWeights;</div><div class="line"><a name="l02266"></a><span class="lineno"> 2266</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &amp;inputToOutputWeights;</div><div class="line"><a name="l02267"></a><span class="lineno"> 2267</span>&#160;</div><div class="line"><a name="l02268"></a><span class="lineno"> 2268</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &amp;recurrentToInputWeights;</div><div class="line"><a name="l02269"></a><span class="lineno"> 2269</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &amp;recurrentToForgetWeights;</div><div class="line"><a name="l02270"></a><span class="lineno"> 2270</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &amp;recurrentToCellWeights;</div><div class="line"><a name="l02271"></a><span class="lineno"> 2271</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &amp;recurrentToOutputWeights;</div><div class="line"><a name="l02272"></a><span class="lineno"> 2272</span>&#160;</div><div class="line"><a name="l02273"></a><span class="lineno"> 2273</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &amp;inputGateBias;</div><div class="line"><a name="l02274"></a><span class="lineno"> 2274</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &amp;forgetGateBias;</div><div class="line"><a name="l02275"></a><span class="lineno"> 2275</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &amp;cellBias;</div><div class="line"><a name="l02276"></a><span class="lineno"> 2276</span>&#160;    params.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &amp;outputGateBias;</div><div class="line"><a name="l02277"></a><span class="lineno"> 2277</span>&#160;</div><div class="line"><a name="l02278"></a><span class="lineno"> 2278</span>&#160;    <a class="code" href="classarmnn_1_1_test_quantized_lstm_layer_visitor.xhtml">TestQuantizedLstmLayerVisitor</a> visitor(params, layerName);</div><div class="line"><a name="l02279"></a><span class="lineno"> 2279</span>&#160;</div><div class="line"><a name="l02280"></a><span class="lineno"> 2280</span>&#160;    <a class="code" href="classarmnn_1_1_network_impl.xhtml">NetworkImpl</a> net;</div><div class="line"><a name="l02281"></a><span class="lineno"> 2281</span>&#160;</div><div class="line"><a name="l02282"></a><span class="lineno"> 2282</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* <span class="keyword">const</span> layer = net.<a class="code" href="classarmnn_1_1_network_impl.xhtml#a40067b05f30a3ab65568c826df7a8ea7">AddQuantizedLstmLayer</a>(params, layerName);</div><div class="line"><a name="l02283"></a><span class="lineno"> 2283</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a8c9198a992b02e61a6777329d487dde3">Accept</a>(visitor);</div><div class="line"><a name="l02284"></a><span class="lineno"> 2284</span>&#160;}</div><div class="line"><a name="l02285"></a><span class="lineno"> 2285</span>&#160;</div><div class="line"><a name="l02286"></a><span class="lineno"> 2286</span>&#160;<a class="code" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="line"><a name="l02287"></a><span class="lineno"> 2287</span>&#160;</div><div class="line"><a name="l02288"></a><span class="lineno"> 2288</span>&#160;} <span class="comment">// namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_test_batch_normalization_layer_visitor_xhtml_abb0d5c2c24fc8c43d01e0fe503df2e93"><div class="ttname"><a href="classarmnn_1_1_test_batch_normalization_layer_visitor.xhtml#abb0d5c2c24fc8c43d01e0fe503df2e93">armnn::TestBatchNormalizationLayerVisitor::CheckDescriptor</a></div><div class="ttdeci">void CheckDescriptor(const BatchNormalizationDescriptor &amp;descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00045">ConstTensorLayerVisitor.cpp:45</a></div></div>
<div class="ttc" id="_output_shape_of_squeeze_8cpp_xhtml_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div>
<div class="ttc" id="classarmnn_1_1_test_q_lstm_layer_visitor_xhtml_a65b6d017f0b0b5e1e8b0d2e4590d9afb"><div class="ttname"><a href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml#a65b6d017f0b0b5e1e8b0d2e4590d9afb">armnn::TestQLstmLayerVisitor::CheckDescriptor</a></div><div class="ttdeci">void CheckDescriptor(const QLstmDescriptor &amp;descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00128">ConstTensorLayerVisitor.cpp:128</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::Convolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00444">Descriptors.hpp:444</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00454">Descriptors.hpp:454</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_lstm_layer_visitor_xhtml_ac45b7720c3156ab1004a904da7d42b44"><div class="ttname"><a href="classarmnn_1_1_test_lstm_layer_visitor.xhtml#ac45b7720c3156ab1004a904da7d42b44">armnn::TestLstmLayerVisitor::CheckConstTensorPtrs</a></div><div class="ttdeci">void CheckConstTensorPtrs(const std::string &amp;name, const ConstTensor *expected, const ConstTensor *actual)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00061">ConstTensorLayerVisitor.cpp:61</a></div></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#l00945">Descriptors.hpp:945</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00456">Descriptors.hpp:456</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_ab03e6e1514f74427916c892f473fe04c"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#ab03e6e1514f74427916c892f473fe04c">armnn::LstmInputParams::m_ProjectionWeights</a></div><div class="ttdeci">const ConstTensor * m_ProjectionWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00055">LstmParams.hpp:55</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_fully_connected_layer_vistor_xhtml"><div class="ttname"><a href="classarmnn_1_1_test_fully_connected_layer_vistor.xhtml">armnn::TestFullyConnectedLayerVistor</a></div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8hpp_source.xhtml#l00089">ConstTensorLayerVisitor.hpp:89</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a49e11acda22742cbaf6f1b259ead0d84"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">armnn::QuantizedLstmInputParams::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00035">QuantizedLstmParams.hpp:35</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_batch_normalization_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_test_batch_normalization_layer_visitor.xhtml">armnn::TestBatchNormalizationLayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8hpp_source.xhtml#l00125">ConstTensorLayerVisitor.hpp:125</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00062">INetwork.hpp:62</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a4a9d678146f572808a361dbdc5489f38"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">armnn::LstmInputParams::m_CellBias</a></div><div class="ttdeci">const ConstTensor * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00053">LstmParams.hpp:53</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00506">Descriptors.hpp:506</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a4a9d678146f572808a361dbdc5489f38"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">armnn::QuantizedLstmInputParams::m_CellBias</a></div><div class="ttdeci">const ConstTensor * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00045">QuantizedLstmParams.hpp:45</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a56b81ca8ba4b4937e0787e4951f043fc"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">armnn::QuantizedLstmInputParams::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00041">QuantizedLstmParams.hpp:41</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::DepthwiseConvolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00496">Descriptors.hpp:496</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_ae3ef3b97542241d331a38613ae189f3e"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#ae3ef3b97542241d331a38613ae189f3e">armnn::NetworkImpl::AddFullyConnectedLayer</a></div><div class="ttdeci">IConnectableLayer * AddFullyConnectedLayer(const FullyConnectedDescriptor &amp;fullyConnectedDescriptor, const ConstTensor &amp;weights, const Optional&lt; ConstTensor &gt; &amp;biases, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01733">Network.cpp:1733</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a86e88bef0df4df96df752b4b8955a3af"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">armnn::LstmDescriptor::m_ClippingThresProj</a></div><div class="ttdeci">float m_ClippingThresProj</div><div class="ttdoc">Clipping threshold value for the projection. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00939">Descriptors.hpp:939</a></div></div>
<div class="ttc" id="classarmnn_1_1_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00270">Optional.hpp:270</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_afe204ca375b74e9a72640c9227918d0a"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#afe204ca375b74e9a72640c9227918d0a">armnn::LstmInputParams::m_CellToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_CellToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00050">LstmParams.hpp:50</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_ae83131e16df1cace69395a5f99bc5ecb"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">armnn::QuantizedLstmInputParams::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00039">QuantizedLstmParams.hpp:39</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00508">Descriptors.hpp:508</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="structarmnn_1_1_fully_connected_descriptor_xhtml_a281fcaec86e17c97f7b8402633f6b55a"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml#a281fcaec86e17c97f7b8402633f6b55a">armnn::FullyConnectedDescriptor::m_TransposeWeightMatrix</a></div><div class="ttdeci">bool m_TransposeWeightMatrix</div><div class="ttdoc">Enable/disable transpose weight matrix. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00404">Descriptors.hpp:404</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_fully_connected_layer_vistor_xhtml_ae48eafaa6a4bc4b7bde0a8824797c350"><div class="ttname"><a href="classarmnn_1_1_test_fully_connected_layer_vistor.xhtml#ae48eafaa6a4bc4b7bde0a8824797c350">armnn::TestFullyConnectedLayerVistor::CheckDescriptor</a></div><div class="ttdeci">void CheckDescriptor(const FullyConnectedDescriptor &amp;descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00039">ConstTensorLayerVisitor.cpp:39</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#l01193">Descriptors.hpp:1193</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_depthwise_convolution2d_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_test_depthwise_convolution2d_layer_visitor.xhtml">armnn::TestDepthwiseConvolution2dLayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8hpp_source.xhtml#l00052">ConstTensorLayerVisitor.hpp:52</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00408">Descriptors.hpp:408</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_ace7a1f1f1041b412b7d8ef82b95ff352"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">armnn::QuantizedLstmInputParams::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensor * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00044">QuantizedLstmParams.hpp:44</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::DepthwiseConvolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00490">Descriptors.hpp:490</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a40067b05f30a3ab65568c826df7a8ea7"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a40067b05f30a3ab65568c826df7a8ea7">armnn::NetworkImpl::AddQuantizedLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddQuantizedLstmLayer(const QuantizedLstmInputParams &amp;params, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02319">Network.cpp:2319</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a484bafa2f8453a7c5a4a00b92a61b006"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a484bafa2f8453a7c5a4a00b92a61b006">armnn::LstmInputParams::m_CellToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_CellToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00048">LstmParams.hpp:48</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a1aa567f46c30960851c02847dc7b4215"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a1aa567f46c30960851c02847dc7b4215">armnn::NetworkImpl::AddConstantLayer</a></div><div class="ttdeci">IConnectableLayer * AddConstantLayer(const ConstTensor &amp;input, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02027">Network.cpp:2027</a></div></div>
<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_xhtml_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">armnn::BatchNormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Value to add to the variance. Used to avoid dividing by zero. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00639">Descriptors.hpp:639</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a9e081a9b94defb30d1558dc912507e0e"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">armnn::LstmInputParams::m_InputGateBias</a></div><div class="ttdeci">const ConstTensor * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00051">LstmParams.hpp:51</a></div></div>
<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::BatchNormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00641">Descriptors.hpp:641</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a9e081a9b94defb30d1558dc912507e0e"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">armnn::QuantizedLstmInputParams::m_InputGateBias</a></div><div class="ttdeci">const ConstTensor * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00043">QuantizedLstmParams.hpp:43</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a1759754ccb88ecc9af44f3aae6e244ee"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">armnn::LstmInputParams::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00046">LstmParams.hpp:46</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_lstm_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_test_lstm_layer_visitor.xhtml">armnn::TestLstmLayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8hpp_source.xhtml#l00192">ConstTensorLayerVisitor.hpp:192</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::Convolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00440">Descriptors.hpp:440</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_af0f796fba1a2be9c56b4c9ee534577ee"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#af0f796fba1a2be9c56b4c9ee534577ee">armnn::LstmInputParams::m_ForgetLayerNormWeights</a></div><div class="ttdeci">const ConstTensor * m_ForgetLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00058">LstmParams.hpp:58</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a35b112e30c3eb153806a2a8c16d178e3"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a35b112e30c3eb153806a2a8c16d178e3">armnn::LstmInputParams::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00049">LstmParams.hpp:49</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__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml">armnn::QuantizedLstmInputParams</a></div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00013">QuantizedLstmParams.hpp:13</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a58f85a122022527a525318473f93d4ef"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a58f85a122022527a525318473f93d4ef">armnn::NetworkImpl::AddDepthwiseConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddDepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor &amp;convolution2dDescriptor, const ConstTensor &amp;weights, const Optional&lt; ConstTensor &gt; &amp;biases, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01840">Network.cpp:1840</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_impl_xhtml"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml">armnn::NetworkImpl</a></div><div class="ttdoc">Private implementation of INetwork. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00031">Network.hpp:31</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a8c0f6d48705f40c5590dde09be262222"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">armnn::LstmInputParams::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensor * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00054">LstmParams.hpp:54</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_layer_visitor_xhtml_ab49c9a185af94e39ae9cd81aa8ec926c"><div class="ttname"><a href="classarmnn_1_1_test_layer_visitor.xhtml#ab49c9a185af94e39ae9cd81aa8ec926c">armnn::TestLayerVisitor::CheckConstTensors</a></div><div class="ttdeci">void CheckConstTensors(const ConstTensor &amp;expected, const ConstTensor &amp;actual)</div><div class="ttdef"><b>Definition:</b> <a href="_test_layer_visitor_8cpp_source.xhtml#l00033">TestLayerVisitor.cpp:33</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_affcee5f4ab5994a21bee3b78b4e43de3"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">armnn::QuantizedLstmInputParams::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00033">QuantizedLstmParams.hpp:33</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::Convolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00442">Descriptors.hpp:442</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00446">Descriptors.hpp:446</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a2acbae0b9e98c94b843677484775c86a"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a2acbae0b9e98c94b843677484775c86a">armnn::NetworkImpl::AddQLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddQLstmLayer(const QLstmDescriptor &amp;descriptor, const LstmInputParams &amp;params, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02357">Network.cpp:2357</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a0cd848f65ec31778d708852f0042fe37"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a0cd848f65ec31778d708852f0042fe37">armnn::LstmInputParams::m_InputLayerNormWeights</a></div><div class="ttdeci">const ConstTensor * m_InputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00057">LstmParams.hpp:57</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::DepthwiseConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00498">Descriptors.hpp:498</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_q_lstm_layer_visitor_xhtml_a7607350d75bcb2ac402bba7494585f33"><div class="ttname"><a href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml#a7607350d75bcb2ac402bba7494585f33">armnn::TestQLstmLayerVisitor::CheckInputParameters</a></div><div class="ttdeci">void CheckInputParameters(const LstmInputParams &amp;inputParams)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00137">ConstTensorLayerVisitor.cpp:137</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#l01197">Descriptors.hpp:1197</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a56b81ca8ba4b4937e0787e4951f043fc"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">armnn::LstmInputParams::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00047">LstmParams.hpp:47</a></div></div>
<div class="ttc" id="_const_tensor_layer_visitor_8hpp_xhtml"><div class="ttname"><a href="_const_tensor_layer_visitor_8hpp.xhtml">ConstTensorLayerVisitor.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml">armnn::LstmDescriptor</a></div><div class="ttdoc">An LstmDescriptor for the LstmLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00911">Descriptors.hpp:911</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::DepthwiseConvolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00494">Descriptors.hpp:494</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_lstm_layer_visitor_xhtml_a7f36acbe9f04ed87e4bc8529f7ec0391"><div class="ttname"><a href="classarmnn_1_1_test_lstm_layer_visitor.xhtml#a7f36acbe9f04ed87e4bc8529f7ec0391">armnn::TestLstmLayerVisitor::CheckDescriptor</a></div><div class="ttdeci">void CheckDescriptor(const LstmDescriptor &amp;descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00051">ConstTensorLayerVisitor.cpp:51</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a44b0e6b16708df7f0d2bbab141688aaa"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a44b0e6b16708df7f0d2bbab141688aaa">armnn::LstmInputParams::m_ProjectionBias</a></div><div class="ttdeci">const ConstTensor * m_ProjectionBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00056">LstmParams.hpp:56</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a31da1ead6794dd64571afdd0b6efc771"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">armnn::QuantizedLstmInputParams::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00034">QuantizedLstmParams.hpp:34</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#l01189">Descriptors.hpp:1189</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml">armnn::FullyConnectedDescriptor</a></div><div class="ttdoc">A FullyConnectedDescriptor for the FullyConnectedLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00389">Descriptors.hpp:389</a></div></div>
<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::FullyConnectedDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00402">Descriptors.hpp:402</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml">armnn::LstmInputParams</a></div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00013">LstmParams.hpp:13</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a8c0f6d48705f40c5590dde09be262222"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">armnn::QuantizedLstmInputParams::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensor * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00046">QuantizedLstmParams.hpp:46</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#l00943">Descriptors.hpp:943</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_convolution2d_layer_visitor_xhtml_ac8b078bb166c52b45f04cae3e74557ad"><div class="ttname"><a href="classarmnn_1_1_test_convolution2d_layer_visitor.xhtml#ac8b078bb166c52b45f04cae3e74557ad">armnn::TestConvolution2dLayerVisitor::CheckDescriptor</a></div><div class="ttdeci">void CheckDescriptor(const Convolution2dDescriptor &amp;convolution2dDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00014">ConstTensorLayerVisitor.cpp:14</a></div></div>
<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml">armnn::QLstmDescriptor</a></div><div class="ttdoc">A QLstmDescriptor for the QLstmLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01153">Descriptors.hpp:1153</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_lstm_layer_visitor_xhtml_a7607350d75bcb2ac402bba7494585f33"><div class="ttname"><a href="classarmnn_1_1_test_lstm_layer_visitor.xhtml#a7607350d75bcb2ac402bba7494585f33">armnn::TestLstmLayerVisitor::CheckInputParameters</a></div><div class="ttdeci">void CheckInputParameters(const LstmInputParams &amp;inputParams)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00079">ConstTensorLayerVisitor.cpp:79</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a10d15f3df1ab52b3b915a4be1dbf386b"><div class="ttname"><a href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">armnn::BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00268">ConstTensorLayerVisitor.cpp:268</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_quantized_lstm_layer_visitor_xhtml_ac6627007bd7a0b3a00cc690307840039"><div class="ttname"><a href="classarmnn_1_1_test_quantized_lstm_layer_visitor.xhtml#ac6627007bd7a0b3a00cc690307840039">armnn::TestQuantizedLstmLayerVisitor::CheckInputParameters</a></div><div class="ttdeci">void CheckInputParameters(const QuantizedLstmInputParams &amp;inputParams)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00226">ConstTensorLayerVisitor.cpp:226</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_quantized_lstm_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_test_quantized_lstm_layer_visitor.xhtml">armnn::TestQuantizedLstmLayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8hpp_source.xhtml#l00257">ConstTensorLayerVisitor.hpp:257</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00935">Descriptors.hpp:935</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00448">Descriptors.hpp:448</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_q_lstm_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml">armnn::TestQLstmLayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8hpp_source.xhtml#l00224">ConstTensorLayerVisitor.hpp:224</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_depthwise_convolution2d_layer_visitor_xhtml_a8498083056c114343a16c556beea6057"><div class="ttname"><a href="classarmnn_1_1_test_depthwise_convolution2d_layer_visitor.xhtml#a8498083056c114343a16c556beea6057">armnn::TestDepthwiseConvolution2dLayerVisitor::CheckDescriptor</a></div><div class="ttdeci">void CheckDescriptor(const DepthwiseConvolution2dDescriptor &amp;convolution2dDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00026">ConstTensorLayerVisitor.cpp:26</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a435d3651482bbfcc11263b4e4e0c900f"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">armnn::QuantizedLstmInputParams::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00038">QuantizedLstmParams.hpp:38</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00937">Descriptors.hpp:937</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_constant_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_test_constant_layer_visitor.xhtml">armnn::TestConstantLayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8hpp_source.xhtml#l00170">ConstTensorLayerVisitor.hpp:170</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_ad0b8c32bb5381f4cc999093ba3b98b43"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#ad0b8c32bb5381f4cc999093ba3b98b43">armnn::LstmInputParams::m_CellLayerNormWeights</a></div><div class="ttdeci">const ConstTensor * m_CellLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00059">LstmParams.hpp:59</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_ace7a1f1f1041b412b7d8ef82b95ff352"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">armnn::LstmInputParams::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensor * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00052">LstmParams.hpp:52</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a49e11acda22742cbaf6f1b259ead0d84"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">armnn::LstmInputParams::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00042">LstmParams.hpp:42</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_convolution2d_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_test_convolution2d_layer_visitor.xhtml">armnn::TestConvolution2dLayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8hpp_source.xhtml#l00015">ConstTensorLayerVisitor.hpp:15</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a6e30c7b3451da3ea9cf4259fb602e6e6"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">armnn::LstmInputParams::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00043">LstmParams.hpp:43</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#l01187">Descriptors.hpp:1187</a></div></div>
<div class="ttc" id="_profiler_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</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 &amp; forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00941">Descriptors.hpp:941</a></div></div>
<div class="ttc" id="structarmnn_1_1_empty_optional_xhtml"><div class="ttname"><a href="structarmnn_1_1_empty_optional.xhtml">armnn::EmptyOptional</a></div><div class="ttdoc">EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...</div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.xhtml#l00032">Optional.hpp:32</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_ae83131e16df1cace69395a5f99bc5ecb"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">armnn::LstmInputParams::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00045">LstmParams.hpp:45</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::DepthwiseConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00500">Descriptors.hpp:500</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a8c9198a992b02e61a6777329d487dde3"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a8c9198a992b02e61a6777329d487dde3">armnn::IConnectableLayer::Accept</a></div><div class="ttdeci">virtual void Accept(ILayerVisitor &amp;visitor) const =0</div><div class="ttdoc">Apply a visitor to this layer. </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#l01195">Descriptors.hpp:1195</a></div></div>
<div class="ttc" id="_network_8hpp_xhtml"><div class="ttname"><a href="_network_8hpp.xhtml">Network.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a1759754ccb88ecc9af44f3aae6e244ee"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">armnn::QuantizedLstmInputParams::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00040">QuantizedLstmParams.hpp:40</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a435d3651482bbfcc11263b4e4e0c900f"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">armnn::LstmInputParams::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00044">LstmParams.hpp:44</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_input_params_xhtml_a6e30c7b3451da3ea9cf4259fb602e6e6"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">armnn::QuantizedLstmInputParams::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_params_8hpp_source.xhtml#l00036">QuantizedLstmParams.hpp:36</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_q_lstm_layer_visitor_xhtml_ac45b7720c3156ab1004a904da7d42b44"><div class="ttname"><a href="classarmnn_1_1_test_q_lstm_layer_visitor.xhtml#ac45b7720c3156ab1004a904da7d42b44">armnn::TestQLstmLayerVisitor::CheckConstTensorPtrs</a></div><div class="ttdeci">void CheckConstTensorPtrs(const std::string &amp;name, const ConstTensor *expected, const ConstTensor *actual)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00110">ConstTensorLayerVisitor.cpp:110</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a8f798e19187ac7ae6ae6153ee64ab645"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a8f798e19187ac7ae6ae6153ee64ab645">armnn::NetworkImpl::AddBatchNormalizationLayer</a></div><div class="ttdeci">IConnectableLayer * AddBatchNormalizationLayer(const BatchNormalizationDescriptor &amp;desc, const ConstTensor &amp;mean, const ConstTensor &amp;variance, const ConstTensor &amp;beta, const ConstTensor &amp;gamma, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01962">Network.cpp:1962</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a9b18daea2e9f42386055326fd016519a"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a9b18daea2e9f42386055326fd016519a">armnn::LstmInputParams::m_OutputLayerNormWeights</a></div><div class="ttdeci">const ConstTensor * m_OutputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00060">LstmParams.hpp:60</a></div></div>
<div class="ttc" id="classarmnn_1_1_test_quantized_lstm_layer_visitor_xhtml_ac45b7720c3156ab1004a904da7d42b44"><div class="ttname"><a href="classarmnn_1_1_test_quantized_lstm_layer_visitor.xhtml#ac45b7720c3156ab1004a904da7d42b44">armnn::TestQuantizedLstmLayerVisitor::CheckConstTensorPtrs</a></div><div class="ttdeci">void CheckConstTensorPtrs(const std::string &amp;name, const ConstTensor *expected, const ConstTensor *actual)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00208">ConstTensorLayerVisitor.cpp:208</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a178a72bbf254eff34a807a5ca27cb61f"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a178a72bbf254eff34a807a5ca27cb61f">armnn::NetworkImpl::AddConvolution2dLayer</a></div><div class="ttdeci">IConnectableLayer * AddConvolution2dLayer(const Convolution2dDescriptor &amp;convolution2dDescriptor, const ConstTensor &amp;weights, const Optional&lt; ConstTensor &gt; &amp;biases, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l01786">Network.cpp:1786</a></div></div>
<div class="ttc" id="classarmnn_1_1_network_impl_xhtml_a0a2fdd4f442952c97a8f24de6700473a"><div class="ttname"><a href="classarmnn_1_1_network_impl.xhtml#a0a2fdd4f442952c97a8f24de6700473a">armnn::NetworkImpl::AddLstmLayer</a></div><div class="ttdeci">IConnectableLayer * AddLstmLayer(const LstmDescriptor &amp;descriptor, const LstmInputParams &amp;params, const char *name=nullptr)</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l02059">Network.cpp:2059</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 &amp; forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01191">Descriptors.hpp:1191</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00460">Descriptors.hpp:460</a></div></div>
<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml">armnn::BatchNormalizationDescriptor</a></div><div class="ttdoc">A BatchNormalizationDescriptor for the BatchNormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00626">Descriptors.hpp:626</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Convolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00438">Descriptors.hpp:438</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_a31da1ead6794dd64571afdd0b6efc771"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">armnn::LstmInputParams::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00041">LstmParams.hpp:41</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::DepthwiseConvolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00492">Descriptors.hpp:492</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_input_params_xhtml_affcee5f4ab5994a21bee3b78b4e43de3"><div class="ttname"><a href="structarmnn_1_1_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">armnn::LstmInputParams::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensor * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_params_8hpp_source.xhtml#l00040">LstmParams.hpp:40</a></div></div>
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