IVGCVSW-3726 Upload ArmNN Doxygen files * Upload current ArmNN Doxygen files Signed-off-by: Ryan OShea <Ryan.OShea2@arm.com> Change-Id: I8989ed16ee40a99a4495b100bd009cf3e24a7285

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author: Ryan OShea <Ryan.OShea2@arm.com> Fri Mar 13 16:26:19 2020 +0000
committer: Ryan OShea <Ryan.OShea2@arm.com> Fri Mar 13 16:26:19 2020 +0000
tree: 6c71d89db68da1033bb422253cee2970580ed692
parent: 78b26f024641e763c7252198339c83bad8c0982f [diff] [blame]
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+<a href="_quantized_lstm_layer_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;<span class="preprocessor">#include &quot;<a class="code" href="_quantized_lstm_layer_8hpp.xhtml">QuantizedLstmLayer.hpp</a>&quot;</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;</div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_layer_clone_base_8hpp.xhtml">LayerCloneBase.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;<a class="code" href="_quantized_lstm_params_8hpp.xhtml">armnn/QuantizedLstmParams.hpp</a>&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_types_utils_8hpp.xhtml">armnn/TypesUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_cpu_tensor_handle_8hpp.xhtml">backendsCommon/CpuTensorHandle.hpp</a>&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_workload_factory_8hpp.xhtml">backendsCommon/WorkloadFactory.hpp</a>&gt;</span></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">   14</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;{</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;</div><div class="line"><a name="l00017"></a><span class="lineno"><a class="line" href="classarmnn_1_1_quantized_lstm_layer.xhtml#a1e8a4f8777390120259787caa45d743a">   17</a></span>&#160;<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#a1e8a4f8777390120259787caa45d743a">QuantizedLstmLayer::QuantizedLstmLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;    : <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>(3, 2, <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>::<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a890a37ff3bfe123414ba7e6f052b49f3">QuantizedLstm</a>, name)</div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;{</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;}</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;</div><div class="line"><a name="l00022"></a><span class="lineno"><a class="line" href="classarmnn_1_1_quantized_lstm_layer.xhtml#adfa912d0c4c6c00f1af2cbfa799572b7">   22</a></span>&#160;std::unique_ptr&lt;IWorkload&gt; <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#adfa912d0c4c6c00f1af2cbfa799572b7">QuantizedLstmLayer::CreateWorkload</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">IWorkloadFactory</a>&amp; factory)<span class="keyword"> const</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;    <a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml">QuantizedLstmQueueDescriptor</a> descriptor;</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">   26</span>&#160;    <span class="comment">// QuantizedLstmLayer parameters - there are no optional params</span></div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a08a1932be591c315a512a877d38b22df">m_InputToInputWeights</a>  = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">m_InputToInputWeights</a>.get();</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a3ea82566d98c5a657c76c3d851c47848">m_InputToForgetWeights</a> = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">m_InputToForgetWeights</a>.get();</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a28ad98d17603fd8b12e046f8ece58970">m_InputToCellWeights</a>   = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a14ab2bc78421c417c4f97a65b0bd78f9">m_InputToCellWeights</a>.get();</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a83dc9086b2e4a4e4cadb66bd874df798">m_InputToOutputWeights</a> = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#ae8d897b8d282f25a6eb784c4aaa98df6">m_InputToOutputWeights</a>.get();</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a98d377149071d8842d610cc0734d1cfe">m_RecurrentToInputWeights</a>  = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8971757790a032e5936da7847ba14b">m_RecurrentToInputWeights</a>.get();</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a45d73e66cbb2b65049e4016c20657ccf">m_RecurrentToForgetWeights</a> = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a3d5f129421bbe6479a66d4ed1356bf68">m_RecurrentToForgetWeights</a>.get();</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#aea142bd50ffb93631c2e08324ec92a1e">m_RecurrentToCellWeights</a>   = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8c3db3c5474f0760553ff93fbc39e6">m_RecurrentToCellWeights</a>.get();</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#adebc1771e5a1f4b113a7aa594ea74d2c">m_RecurrentToOutputWeights</a> = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a91dda74af4085ae43913746ad817795a">m_RecurrentToOutputWeights</a>.get();</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#acb3aade8fae984f7293e222dcbe66030">m_InputGateBias</a>  = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a9945bc99f8a7400c0724117e29cb3abb">m_InputGateBias</a>.get();</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#aba3ffe91d818266b8785ce971548eb59">m_ForgetGateBias</a> = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a0e0e17d5b494993407cb75d614455ddd">m_ForgetGateBias</a>.get();</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a75980b5795efd899a0c678a06a900c6d">m_CellBias</a>       = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a51255889cbc063130a3d691c1781c5d3">m_CellBias</a>.get();</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a332551528a4b3534c2d6c89ce816fcd9">m_OutputGateBias</a> = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#aacb55e0992b6781a7bd3225ab6e6bb2f">m_OutputGateBias</a>.get();</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    <span class="keywordflow">return</span> factory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ab5ceda49651dcd53fb7eb05658b5a0cb">CreateQuantizedLstm</a>(descriptor, <a class="code" href="classarmnn_1_1_layer.xhtml#a30a858b2b26d651a066537e499fbf40d">PrepInfoAndDesc</a>(descriptor));</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_quantized_lstm_layer.xhtml#a08edea9423b6da5da174ce5269f6e28b">   45</a></span>&#160;<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml">QuantizedLstmLayer</a>* <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#a08edea9423b6da5da174ce5269f6e28b">QuantizedLstmLayer::Clone</a>(<a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>&amp; graph)<span class="keyword"> const</span></div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;    <span class="keyword">auto</span> layer = CloneBase&lt;QuantizedLstmLayer&gt;(graph, <a class="code" href="classarmnn_1_1_layer.xhtml#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">m_InputToInputWeights</a> = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">m_InputToInputWeights</a> ?</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;            std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">m_InputToInputWeights</a>) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    layer-&gt;m_QuantizedLstmParameters.m_InputToForgetWeights = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">m_InputToForgetWeights</a> ?</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;            std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">m_InputToForgetWeights</a>) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    layer-&gt;m_QuantizedLstmParameters.m_InputToCellWeights = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a14ab2bc78421c417c4f97a65b0bd78f9">m_InputToCellWeights</a> ?</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;            std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a14ab2bc78421c417c4f97a65b0bd78f9">m_InputToCellWeights</a>) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    layer-&gt;m_QuantizedLstmParameters.m_InputToOutputWeights = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#ae8d897b8d282f25a6eb784c4aaa98df6">m_InputToOutputWeights</a> ?</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;            std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#ae8d897b8d282f25a6eb784c4aaa98df6">m_InputToOutputWeights</a>) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    layer-&gt;m_QuantizedLstmParameters.m_RecurrentToInputWeights = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8971757790a032e5936da7847ba14b">m_RecurrentToInputWeights</a> ?</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;            std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8971757790a032e5936da7847ba14b">m_RecurrentToInputWeights</a>) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    layer-&gt;m_QuantizedLstmParameters.m_RecurrentToForgetWeights = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a3d5f129421bbe6479a66d4ed1356bf68">m_RecurrentToForgetWeights</a></div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;            ? std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a3d5f129421bbe6479a66d4ed1356bf68">m_RecurrentToForgetWeights</a>) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    layer-&gt;m_QuantizedLstmParameters.m_RecurrentToCellWeights = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8c3db3c5474f0760553ff93fbc39e6">m_RecurrentToCellWeights</a> ?</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;            std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8c3db3c5474f0760553ff93fbc39e6">m_RecurrentToCellWeights</a>) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    layer-&gt;m_QuantizedLstmParameters.m_RecurrentToOutputWeights = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a91dda74af4085ae43913746ad817795a">m_RecurrentToOutputWeights</a></div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;            ? std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a91dda74af4085ae43913746ad817795a">m_RecurrentToOutputWeights</a>) : <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;    layer-&gt;m_QuantizedLstmParameters.m_InputGateBias = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a9945bc99f8a7400c0724117e29cb3abb">m_InputGateBias</a> ?</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;            std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a9945bc99f8a7400c0724117e29cb3abb">m_InputGateBias</a>) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    layer-&gt;m_QuantizedLstmParameters.m_ForgetGateBias = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a0e0e17d5b494993407cb75d614455ddd">m_ForgetGateBias</a> ?</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;            std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a0e0e17d5b494993407cb75d614455ddd">m_ForgetGateBias</a>) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    layer-&gt;m_QuantizedLstmParameters.m_CellBias = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a51255889cbc063130a3d691c1781c5d3">m_CellBias</a> ?</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;            std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a51255889cbc063130a3d691c1781c5d3">m_CellBias</a>) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    layer-&gt;m_QuantizedLstmParameters.m_OutputGateBias = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#aacb55e0992b6781a7bd3225ab6e6bb2f">m_OutputGateBias</a> ?</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;            std::make_unique&lt;ScopedCpuTensorHandle&gt;(*<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#aacb55e0992b6781a7bd3225ab6e6bb2f">m_OutputGateBias</a>) : <span class="keyword">nullptr</span>;</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;    <span class="keywordflow">return</span> std::move(layer);</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_quantized_lstm_layer.xhtml#a65ca562c882ad619684445a1402f415a">   79</a></span>&#160;std::vector&lt;TensorShape&gt; <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#a65ca562c882ad619684445a1402f415a">QuantizedLstmLayer::InferOutputShapes</a>(<span class="keyword">const</span> std::vector&lt;TensorShape&gt;&amp; inputShapes)<span class="keyword"> const</span></div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    BOOST_ASSERT(inputShapes.size() == 3);</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    <span class="comment">// Get input values for validation</span></div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numBatches = inputShapes[0][0];</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = inputShapes[1][1];</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    std::vector&lt;TensorShape&gt; outShapes;</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    outShapes.push_back(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({numBatches, outputSize})); <span class="comment">// cellStateOut</span></div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;    outShapes.push_back(<a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({numBatches, outputSize})); <span class="comment">// output</span></div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    <span class="keywordflow">return</span> outShapes;</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;}</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;</div><div class="line"><a name="l00094"></a><span class="lineno"><a class="line" href="classarmnn_1_1_quantized_lstm_layer.xhtml#a8c8f543d7e9729362c266d12ec169966">   94</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#a8c8f543d7e9729362c266d12ec169966">QuantizedLstmLayer::ValidateTensorShapesFromInputs</a>()</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;{</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    <a class="code" href="classarmnn_1_1_layer.xhtml#a0607e36e88f38c34c71c663164b76776">VerifyLayerConnections</a>(3, <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    <span class="keyword">auto</span> inferredShapes = <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    {</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;        <a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-&gt;<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), <span class="comment">// input</span></div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        <a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-&gt;<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), <span class="comment">// previousCellStateIn</span></div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;        <a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(2).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-&gt;<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()  <span class="comment">// previousOutputIn</span></div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;    });</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;    BOOST_ASSERT(inferredShapes.size() == 2);</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    <span class="comment">// Check weights and bias for nullptr</span></div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">m_InputToInputWeights</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToInputWeights should not be null.&quot;</span>);</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">m_InputToForgetWeights</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToForgetWeights should not be null.&quot;</span>);</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a14ab2bc78421c417c4f97a65b0bd78f9">m_InputToCellWeights</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToCellWeights should not be null.&quot;</span>);</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#ae8d897b8d282f25a6eb784c4aaa98df6">m_InputToOutputWeights</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputToOutputWeights should not be null.&quot;</span>);</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8971757790a032e5936da7847ba14b">m_RecurrentToInputWeights</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToInputWeights should not be null.&quot;</span>);</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a3d5f129421bbe6479a66d4ed1356bf68">m_RecurrentToForgetWeights</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToForgetWeights should not be null.&quot;</span>);</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8c3db3c5474f0760553ff93fbc39e6">m_RecurrentToCellWeights</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToCellWeights should not be null.&quot;</span>);</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a91dda74af4085ae43913746ad817795a">m_RecurrentToOutputWeights</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_RecurrentToOutputWeights should not be null.&quot;</span>);</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;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a9945bc99f8a7400c0724117e29cb3abb">m_InputGateBias</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_InputGateBias should not be null.&quot;</span>);</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a0e0e17d5b494993407cb75d614455ddd">m_ForgetGateBias</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_ForgetGateBias should not be null.&quot;</span>);</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a51255889cbc063130a3d691c1781c5d3">m_CellBias</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_CellBias should not be null.&quot;</span>);</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#aacb55e0992b6781a7bd3225ab6e6bb2f">m_OutputGateBias</a> != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;                     <span class="stringliteral">&quot;QuantizedLstmLayer: m_QuantizedLstmParameters.m_OutputGateBias should not be null.&quot;</span>);</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    <span class="comment">// Check output TensorShape(s) match inferred shape</span></div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    ConditionalThrowIfNotEqual&lt;LayerValidationException&gt;(</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;            <span class="stringliteral">&quot;QuantizedLstmLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.&quot;</span>,</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;            <a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;            inferredShapes[0]);</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    ConditionalThrowIfNotEqual&lt;LayerValidationException&gt;(</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;            <span class="stringliteral">&quot;QuantizedLstmLayer: TensorShape set on OutputSlot[1] does not match the inferred shape.&quot;</span>,</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;            <a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;            inferredShapes[1]);</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;}</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"><a class="line" href="classarmnn_1_1_quantized_lstm_layer.xhtml#abe659a5afa7523f5dbc04bcba9b31f1a">  147</a></span>&#160;<a class="code" href="classarmnn_1_1_layer.xhtml#a585d59ec610af46a76487fd6c1c55ac1">Layer::ConstantTensors</a> <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#abe659a5afa7523f5dbc04bcba9b31f1a">QuantizedLstmLayer::GetConstantTensorsByRef</a>()</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;{</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    <span class="keywordflow">return</span></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;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">m_InputToInputWeights</a>,</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">m_InputToForgetWeights</a>,</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a14ab2bc78421c417c4f97a65b0bd78f9">m_InputToCellWeights</a>,</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#ae8d897b8d282f25a6eb784c4aaa98df6">m_InputToOutputWeights</a>,</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8971757790a032e5936da7847ba14b">m_RecurrentToInputWeights</a>,</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a3d5f129421bbe6479a66d4ed1356bf68">m_RecurrentToForgetWeights</a>,</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8c3db3c5474f0760553ff93fbc39e6">m_RecurrentToCellWeights</a>,</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a91dda74af4085ae43913746ad817795a">m_RecurrentToOutputWeights</a>,</div><div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a9945bc99f8a7400c0724117e29cb3abb">m_InputGateBias</a>,</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a0e0e17d5b494993407cb75d614455ddd">m_ForgetGateBias</a>,</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a51255889cbc063130a3d691c1781c5d3">m_CellBias</a>,</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;        <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#aacb55e0992b6781a7bd3225ab6e6bb2f">m_OutputGateBias</a></div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;    };</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;</div><div class="line"><a name="l00168"></a><span class="lineno"><a class="line" href="classarmnn_1_1_quantized_lstm_layer.xhtml#a75a50f464326fefa605ea84ae2c9be85">  168</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#a75a50f464326fefa605ea84ae2c9be85">QuantizedLstmLayer::Accept</a>(<a class="code" href="classarmnn_1_1_i_layer_visitor.xhtml">ILayerVisitor</a>&amp; visitor)<span class="keyword"> const</span></div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    <a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml">QuantizedLstmInputParams</a> inputParams;</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;    <span class="comment">// InputToX weight tensors</span></div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToInputWeightsTensor;</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">m_InputToInputWeights</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    {</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToInputWeightsTensorCopy(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">m_InputToInputWeights</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;                                                  <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">m_InputToInputWeights</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;        inputToInputWeightsTensor = inputToInputWeightsTensorCopy;</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#affcee5f4ab5994a21bee3b78b4e43de3">m_InputToInputWeights</a> = &amp;inputToInputWeightsTensor;</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;    }</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToForgetWeightsTensor;</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">m_InputToForgetWeights</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    {</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToForgetWeightsTensorCopy(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">m_InputToForgetWeights</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;                                                   <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">m_InputToForgetWeights</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;        inputToForgetWeightsTensor = inputToForgetWeightsTensorCopy;</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a31da1ead6794dd64571afdd0b6efc771">m_InputToForgetWeights</a> = &amp;inputToForgetWeightsTensor;</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    }</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;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToCellWeightsTensor;</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a14ab2bc78421c417c4f97a65b0bd78f9">m_InputToCellWeights</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;    {</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToCellWeightsTensorCopy(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a14ab2bc78421c417c4f97a65b0bd78f9">m_InputToCellWeights</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;                                                 <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a14ab2bc78421c417c4f97a65b0bd78f9">m_InputToCellWeights</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;        inputToCellWeightsTensor = inputToCellWeightsTensorCopy;</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a49e11acda22742cbaf6f1b259ead0d84">m_InputToCellWeights</a> = &amp;inputToCellWeightsTensor;</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;</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToOutputWeightsTensor;</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#ae8d897b8d282f25a6eb784c4aaa98df6">m_InputToOutputWeights</a> != <span class="keyword">nullptr</span>)</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;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputToOutputWeightsTensorCopy(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#ae8d897b8d282f25a6eb784c4aaa98df6">m_InputToOutputWeights</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;                                                   <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#ae8d897b8d282f25a6eb784c4aaa98df6">m_InputToOutputWeights</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;        inputToOutputWeightsTensor = inputToOutputWeightsTensorCopy;</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a6e30c7b3451da3ea9cf4259fb602e6e6">m_InputToOutputWeights</a> = &amp;inputToOutputWeightsTensor;</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">  208</span>&#160;</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;    <span class="comment">// RecurrentToX weight tensors</span></div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToInputWeightsTensor;</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8971757790a032e5936da7847ba14b">m_RecurrentToInputWeights</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;    {</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToInputWeightsTensorCopy(</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;                <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8971757790a032e5936da7847ba14b">m_RecurrentToInputWeights</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;                <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8971757790a032e5936da7847ba14b">m_RecurrentToInputWeights</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;        recurrentToInputWeightsTensor = recurrentToInputWeightsTensorCopy;</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a435d3651482bbfcc11263b4e4e0c900f">m_RecurrentToInputWeights</a> = &amp;recurrentToInputWeightsTensor;</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;    }</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToForgetWeightsTensor;</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a3d5f129421bbe6479a66d4ed1356bf68">m_RecurrentToForgetWeights</a> != <span class="keyword">nullptr</span>)</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;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToForgetWeightsTensorCopy(</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;                <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a3d5f129421bbe6479a66d4ed1356bf68">m_RecurrentToForgetWeights</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;                <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a3d5f129421bbe6479a66d4ed1356bf68">m_RecurrentToForgetWeights</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;        recurrentToForgetWeightsTensor = recurrentToForgetWeightsTensorCopy;</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ae83131e16df1cace69395a5f99bc5ecb">m_RecurrentToForgetWeights</a> = &amp;recurrentToForgetWeightsTensor;</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;    }</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToCellWeightsTensor;</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8c3db3c5474f0760553ff93fbc39e6">m_RecurrentToCellWeights</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    {</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToCellWeightsTensorCopy(</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;                <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8c3db3c5474f0760553ff93fbc39e6">m_RecurrentToCellWeights</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;                <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8c3db3c5474f0760553ff93fbc39e6">m_RecurrentToCellWeights</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;        recurrentToCellWeightsTensor = recurrentToCellWeightsTensorCopy;</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a1759754ccb88ecc9af44f3aae6e244ee">m_RecurrentToCellWeights</a> = &amp;recurrentToCellWeightsTensor;</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    }</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;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToOutputWeightsTensor;</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a91dda74af4085ae43913746ad817795a">m_RecurrentToOutputWeights</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;    {</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> recurrentToOutputWeightsTensorCopy(</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;                <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a91dda74af4085ae43913746ad817795a">m_RecurrentToOutputWeights</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;                <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a91dda74af4085ae43913746ad817795a">m_RecurrentToOutputWeights</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;        recurrentToOutputWeightsTensor = recurrentToOutputWeightsTensorCopy;</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a56b81ca8ba4b4937e0787e4951f043fc">m_RecurrentToOutputWeights</a> = &amp;recurrentToOutputWeightsTensor;</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;    }</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;    <span class="comment">// Bias tensors</span></div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputGateBiasTensor;</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a9945bc99f8a7400c0724117e29cb3abb">m_InputGateBias</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    {</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> inputGateBiasTensorCopy(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a9945bc99f8a7400c0724117e29cb3abb">m_InputGateBias</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;                                            <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a9945bc99f8a7400c0724117e29cb3abb">m_InputGateBias</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;        inputGateBiasTensor = inputGateBiasTensorCopy;</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a9e081a9b94defb30d1558dc912507e0e">m_InputGateBias</a> = &amp;inputGateBiasTensor;</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;    }</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;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBiasTensor;</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a0e0e17d5b494993407cb75d614455ddd">m_ForgetGateBias</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;    {</div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> forgetGateBiasTensorCopy(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a0e0e17d5b494993407cb75d614455ddd">m_ForgetGateBias</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;                                             <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a0e0e17d5b494993407cb75d614455ddd">m_ForgetGateBias</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;        forgetGateBiasTensor = forgetGateBiasTensorCopy;</div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#ace7a1f1f1041b412b7d8ef82b95ff352">m_ForgetGateBias</a> = &amp;forgetGateBiasTensor;</div><div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;    }</div><div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;</div><div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellBiasTensor;</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a51255889cbc063130a3d691c1781c5d3">m_CellBias</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;    {</div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> cellBiasTensorCopy(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a51255889cbc063130a3d691c1781c5d3">m_CellBias</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;                                       <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a51255889cbc063130a3d691c1781c5d3">m_CellBias</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;        cellBiasTensor = cellBiasTensorCopy;</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a4a9d678146f572808a361dbdc5489f38">m_CellBias</a> = &amp;cellBiasTensor;</div><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;    }</div><div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;</div><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> outputGateBiasTensor;</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#aacb55e0992b6781a7bd3225ab6e6bb2f">m_OutputGateBias</a> != <span class="keyword">nullptr</span>)</div><div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;    {</div><div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> outputGateBiasCopy(<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#aacb55e0992b6781a7bd3225ab6e6bb2f">m_OutputGateBias</a>-&gt;GetTensorInfo(),</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;                                       <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">m_QuantizedLstmParameters</a>.<a class="code" href="structarmnn_1_1_quantized_lstm_parameters.xhtml#aacb55e0992b6781a7bd3225ab6e6bb2f">m_OutputGateBias</a>-&gt;Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;        outputGateBiasTensor = outputGateBiasCopy;</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;        inputParams.<a class="code" href="structarmnn_1_1_quantized_lstm_input_params.xhtml#a8c0f6d48705f40c5590dde09be262222">m_OutputGateBias</a> = &amp;outputGateBiasTensor;</div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;    }</div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;</div><div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;    visitor.<a class="code" href="classarmnn_1_1_i_layer_visitor.xhtml#acb1bac244973743d460064c1e0d816fd">VisitQuantizedLstmLayer</a>(<span class="keyword">this</span>, inputParams, <a class="code" href="classarmnn_1_1_layer.xhtml#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</div><div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;}</div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;} <span class="comment">// namespace armnn</span></div><div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml_a45d73e66cbb2b65049e4016c20657ccf"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a45d73e66cbb2b65049e4016c20657ccf">armnn::QuantizedLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00537">WorkloadData.hpp:537</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_parameters_xhtml_a6e8971757790a032e5936da7847ba14b"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8971757790a032e5936da7847ba14b">armnn::QuantizedLstmParameters::m_RecurrentToInputWeights</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_RecurrentToInputWeights</div><div class="ttdoc">A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8)...</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00026">QuantizedLstmLayer.hpp:26</a></div></div>
+<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml_abe659a5afa7523f5dbc04bcba9b31f1a"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml#abe659a5afa7523f5dbc04bcba9b31f1a">armnn::QuantizedLstmLayer::GetConstantTensorsByRef</a></div><div class="ttdeci">Layer::ConstantTensors GetConstantTensorsByRef() override</div><div class="ttdoc">Retrieve the handles to the constant values stored by the layer. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8cpp_source.xhtml#l00147">QuantizedLstmLayer.cpp:147</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml_acb3aade8fae984f7293e222dcbe66030"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#acb3aade8fae984f7293e222dcbe66030">armnn::QuantizedLstmQueueDescriptor::m_InputGateBias</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00541">WorkloadData.hpp:541</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_quantized_lstm_layer_xhtml_ad3c37b52145c3cf1b4856c0df008a468"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml#ad3c37b52145c3cf1b4856c0df008a468">armnn::QuantizedLstmLayer::m_QuantizedLstmParameters</a></div><div class="ttdeci">QuantizedLstmParameters m_QuantizedLstmParameters</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00049">QuantizedLstmLayer.hpp:49</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="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape &amp; GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00088">Tensor.hpp:88</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_parameters_xhtml_a5a0d8af26a6aad1e5be521ea7dc550eb"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a5a0d8af26a6aad1e5be521ea7dc550eb">armnn::QuantizedLstmParameters::m_InputToForgetWeights</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_InputToForgetWeights</div><div class="ttdoc">A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8)...</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00019">QuantizedLstmLayer.hpp:19</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_quantized_lstm_parameters_xhtml_a91dda74af4085ae43913746ad817795a"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a91dda74af4085ae43913746ad817795a">armnn::QuantizedLstmParameters::m_RecurrentToOutputWeights</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_RecurrentToOutputWeights</div><div class="ttdoc">A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8)...</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00032">QuantizedLstmLayer.hpp:32</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml">armnn::QuantizedLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00512">WorkloadData.hpp:512</a></div></div>
+<div class="ttc" id="_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_workload_factory_8hpp.xhtml">WorkloadFactory.hpp</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="classarmnn_1_1_i_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.xhtml#l00021">WorkloadFactory.hpp:21</a></div></div>
+<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml_a08edea9423b6da5da174ce5269f6e28b"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml#a08edea9423b6da5da174ce5269f6e28b">armnn::QuantizedLstmLayer::Clone</a></div><div class="ttdeci">QuantizedLstmLayer * Clone(Graph &amp;graph) const override</div><div class="ttdoc">Creates a dynamically-allocated copy of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8cpp_source.xhtml#l00045">QuantizedLstmLayer.cpp:45</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml_a28ad98d17603fd8b12e046f8ece58970"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a28ad98d17603fd8b12e046f8ece58970">armnn::QuantizedLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00533">WorkloadData.hpp:533</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="_quantized_lstm_params_8hpp_xhtml"><div class="ttname"><a href="_quantized_lstm_params_8hpp.xhtml">QuantizedLstmParams.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ab5ceda49651dcd53fb7eb05658b5a0cb"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ab5ceda49651dcd53fb7eb05658b5a0cb">armnn::IWorkloadFactory::CreateQuantizedLstm</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateQuantizedLstm(const QuantizedLstmQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01364">WorkloadFactory.cpp:1364</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_quantized_lstm_parameters_xhtml_a4d731c5e73638c7cf7e63f65e9f8b550"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a4d731c5e73638c7cf7e63f65e9f8b550">armnn::QuantizedLstmParameters::m_InputToInputWeights</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_InputToInputWeights</div><div class="ttdoc">A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8)...</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00017">QuantizedLstmLayer.hpp:17</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_parameters_xhtml_a3d5f129421bbe6479a66d4ed1356bf68"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a3d5f129421bbe6479a66d4ed1356bf68">armnn::QuantizedLstmParameters::m_RecurrentToForgetWeights</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_RecurrentToForgetWeights</div><div class="ttdoc">A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8)...</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00028">QuantizedLstmLayer.hpp:28</a></div></div>
+<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml#a8c8f543d7e9729362c266d12ec169966">armnn::QuantizedLstmLayer::ValidateTensorShapesFromInputs</a></div><div class="ttdeci">void ValidateTensorShapesFromInputs() override</div><div class="ttdoc">Check if the input tensor shape(s) will lead to a valid configuration of QuantizedLstmLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8cpp_source.xhtml#l00094">QuantizedLstmLayer.cpp:94</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</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_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
+<div class="ttc" id="classarmnn_1_1_input_slot_xhtml_a3153abb7c0c0a84629079b2fac7db54f"><div class="ttname"><a href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">armnn::InputSlot::GetConnection</a></div><div class="ttdeci">const IOutputSlot * GetConnection() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00199">Layer.hpp:199</a></div></div>
+<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml_a1e8a4f8777390120259787caa45d743a"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml#a1e8a4f8777390120259787caa45d743a">armnn::QuantizedLstmLayer::QuantizedLstmLayer</a></div><div class="ttdeci">QuantizedLstmLayer(const char *name)</div><div class="ttdoc">Constructor to create a QuantizedLstmLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8cpp_source.xhtml#l00017">QuantizedLstmLayer.cpp:17</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_parameters_xhtml_a9945bc99f8a7400c0724117e29cb3abb"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a9945bc99f8a7400c0724117e29cb3abb">armnn::QuantizedLstmParameters::m_InputGateBias</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_InputGateBias</div><div class="ttdoc">A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32). </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00035">QuantizedLstmLayer.hpp:35</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_parameters_xhtml_a51255889cbc063130a3d691c1781c5d3"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a51255889cbc063130a3d691c1781c5d3">armnn::QuantizedLstmParameters::m_CellBias</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_CellBias</div><div class="ttdoc">A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32). </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00039">QuantizedLstmLayer.hpp:39</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="classarmnn_1_1_layer_xhtml_a0607e36e88f38c34c71c663164b76776"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0607e36e88f38c34c71c663164b76776">armnn::Layer::VerifyLayerConnections</a></div><div class="ttdeci">void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &amp;location) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00338">Layer.cpp:338</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot &amp; GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00310">Layer.hpp:310</a></div></div>
+<div class="ttc" id="_types_utils_8hpp_xhtml"><div class="ttname"><a href="_types_utils_8hpp.xhtml">TypesUtils.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml">armnn::QuantizedLstmLayer</a></div><div class="ttdoc">This layer represents a QuantizedLstm operation. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00045">QuantizedLstmLayer.hpp:45</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_xhtml_a30a858b2b26d651a066537e499fbf40d"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a30a858b2b26d651a066537e499fbf40d">armnn::Layer::PrepInfoAndDesc</a></div><div class="ttdeci">WorkloadInfo PrepInfoAndDesc(QueueDescriptor &amp;descriptor) const</div><div class="ttdoc">Helper function to reduce duplication in *LayerCreateWorkload. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00351">Layer.hpp:351</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_parameters_xhtml_a0e0e17d5b494993407cb75d614455ddd"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a0e0e17d5b494993407cb75d614455ddd">armnn::QuantizedLstmParameters::m_ForgetGateBias</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_ForgetGateBias</div><div class="ttdoc">A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32). </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00037">QuantizedLstmLayer.hpp:37</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_quantized_lstm_queue_descriptor_xhtml_aba3ffe91d818266b8785ce971548eb59"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#aba3ffe91d818266b8785ce971548eb59">armnn::QuantizedLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00542">WorkloadData.hpp:542</a></div></div>
+<div class="ttc" id="_quantized_lstm_layer_8hpp_xhtml"><div class="ttname"><a href="_quantized_lstm_layer_8hpp.xhtml">QuantizedLstmLayer.hpp</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#l00199">Tensor.hpp:199</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_quantized_lstm_queue_descriptor_xhtml_a98d377149071d8842d610cc0734d1cfe"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a98d377149071d8842d610cc0734d1cfe">armnn::QuantizedLstmQueueDescriptor::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00536">WorkloadData.hpp:536</a></div></div>
+<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml_a75a50f464326fefa605ea84ae2c9be85"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml#a75a50f464326fefa605ea84ae2c9be85">armnn::QuantizedLstmLayer::Accept</a></div><div class="ttdeci">void Accept(ILayerVisitor &amp;visitor) const override</div><div class="ttdoc">Apply a visitor to this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8cpp_source.xhtml#l00168">QuantizedLstmLayer.cpp:168</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml_aea142bd50ffb93631c2e08324ec92a1e"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#aea142bd50ffb93631c2e08324ec92a1e">armnn::QuantizedLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00538">WorkloadData.hpp:538</a></div></div>
+<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml_adfa912d0c4c6c00f1af2cbfa799572b7"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml#adfa912d0c4c6c00f1af2cbfa799572b7">armnn::QuantizedLstmLayer::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateWorkload(const IWorkloadFactory &amp;factory) const override</div><div class="ttdoc">Makes a workload for the QuantizedLstm type. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8cpp_source.xhtml#l00022">QuantizedLstmLayer.cpp:22</a></div></div>
+<div class="ttc" id="_exceptions_8hpp_xhtml_aa3be76aec4ce713822a5ea1ecbb7bc61"><div class="ttname"><a href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a></div><div class="ttdeci">#define CHECK_LOCATION()</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00192">Exceptions.hpp:192</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml_adebc1771e5a1f4b113a7aa594ea74d2c"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#adebc1771e5a1f4b113a7aa594ea74d2c">armnn::QuantizedLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00539">WorkloadData.hpp:539</a></div></div>
+<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</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="classarmnn_1_1_i_layer_visitor_xhtml_acb1bac244973743d460064c1e0d816fd"><div class="ttname"><a href="classarmnn_1_1_i_layer_visitor.xhtml#acb1bac244973743d460064c1e0d816fd">armnn::ILayerVisitor::VisitQuantizedLstmLayer</a></div><div class="ttdeci">virtual void VisitQuantizedLstmLayer(const IConnectableLayer *layer, const QuantizedLstmInputParams &amp;params, const char *name=nullptr)=0</div><div class="ttdoc">Function a QuantizedLstm layer should call back to when its Accept(ILayerVisitor&amp;) function is invoke...</div></div>
+<div class="ttc" id="_cpu_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.xhtml">CpuTensorHandle.hpp</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_parameters_xhtml_aacb55e0992b6781a7bd3225ab6e6bb2f"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#aacb55e0992b6781a7bd3225ab6e6bb2f">armnn::QuantizedLstmParameters::m_OutputGateBias</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_OutputGateBias</div><div class="ttdoc">A unique pointer to represent 1D bias tensor with dimensions [outputSize] (int32). </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00041">QuantizedLstmLayer.hpp:41</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml_a75980b5795efd899a0c678a06a900c6d"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a75980b5795efd899a0c678a06a900c6d">armnn::QuantizedLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00543">WorkloadData.hpp:543</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a890a37ff3bfe123414ba7e6f052b49f3"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a890a37ff3bfe123414ba7e6f052b49f3">armnn::LayerType::QuantizedLstm</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_quantized_lstm_queue_descriptor_xhtml_a332551528a4b3534c2d6c89ce816fcd9"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a332551528a4b3534c2d6c89ce816fcd9">armnn::QuantizedLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00544">WorkloadData.hpp:544</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="structarmnn_1_1_quantized_lstm_parameters_xhtml_a14ab2bc78421c417c4f97a65b0bd78f9"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a14ab2bc78421c417c4f97a65b0bd78f9">armnn::QuantizedLstmParameters::m_InputToCellWeights</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_InputToCellWeights</div><div class="ttdoc">A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8)...</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00021">QuantizedLstmLayer.hpp:21</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_layer_visitor.xhtml">armnn::ILayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_layer_visitor_8hpp_source.xhtml#l00016">ILayerVisitor.hpp:16</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a9943775a364fc4ab53b85ac88f311886"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">armnn::IOutputSlot::GetTensorInfo</a></div><div class="ttdeci">virtual const TensorInfo &amp; GetTensorInfo() const =0</div></div>
+<div class="ttc" id="classarmnn_1_1_layer_xhtml_a7ddf0cf6f620d59c10e63495ace795d0"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a7ddf0cf6f620d59c10e63495ace795d0">armnn::Layer::GetName</a></div><div class="ttdeci">const char * GetName() const override</div><div class="ttdoc">Returns the name of the layer. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00305">Layer.hpp:305</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml_a3ea82566d98c5a657c76c3d851c47848"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a3ea82566d98c5a657c76c3d851c47848">armnn::QuantizedLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00532">WorkloadData.hpp:532</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_parameters_xhtml_ae8d897b8d282f25a6eb784c4aaa98df6"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#ae8d897b8d282f25a6eb784c4aaa98df6">armnn::QuantizedLstmParameters::m_InputToOutputWeights</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_InputToOutputWeights</div><div class="ttdoc">A unique pointer to represent 2D weights tensor with dimensions [outputSize, inputSize] (QAsymm8)...</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00023">QuantizedLstmLayer.hpp:23</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml_a83dc9086b2e4a4e4cadb66bd874df798"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a83dc9086b2e4a4e4cadb66bd874df798">armnn::QuantizedLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00534">WorkloadData.hpp:534</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_xhtml_a585d59ec610af46a76487fd6c1c55ac1"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a585d59ec610af46a76487fd6c1c55ac1">armnn::Layer::ConstantTensors</a></div><div class="ttdeci">std::vector&lt; std::reference_wrapper&lt; std::unique_ptr&lt; ScopedCpuTensorHandle &gt; &gt;&gt; ConstantTensors</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00363">Layer.hpp:363</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml_a08a1932be591c315a512a877d38b22df"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml#a08a1932be591c315a512a877d38b22df">armnn::QuantizedLstmQueueDescriptor::m_InputToInputWeights</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00531">WorkloadData.hpp:531</a></div></div>
+<div class="ttc" id="structarmnn_1_1_quantized_lstm_parameters_xhtml_a6e8c3db3c5474f0760553ff93fbc39e6"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_parameters.xhtml#a6e8c3db3c5474f0760553ff93fbc39e6">armnn::QuantizedLstmParameters::m_RecurrentToCellWeights</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_RecurrentToCellWeights</div><div class="ttdoc">A unique pointer to represent 2D weights tensor with dimensions [outputSize, outputSize] (QAsymm8)...</div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00030">QuantizedLstmLayer.hpp:30</a></div></div>
+<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00063">Layer.cpp:63</a></div></div>
+<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::QuantizedLstmLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector&lt; TensorShape &gt; InferOutputShapes(const std::vector&lt; TensorShape &gt; &amp;inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8cpp_source.xhtml#l00079">QuantizedLstmLayer.cpp:79</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div>
+<div class="ttc" id="_layer_clone_base_8hpp_xhtml"><div class="ttname"><a href="_layer_clone_base_8hpp.xhtml">LayerCloneBase.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8hpp_source.xhtml#l00014">InternalTypes.hpp:14</a></div></div>
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+    <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_e0a84d05c80a2ef4231141dcbbeac5c8.xhtml">armnn</a></li><li class="navelem"><a class="el" href="dir_9da6642ce0fd5a8c83524f1b621275be.xhtml">layers</a></li><li class="navelem"><a class="el" href="_quantized_lstm_layer_8cpp.xhtml">QuantizedLstmLayer.cpp</a></li>
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commit	de36e4a9c299028e792c3a5bd99ad0816d806077	[log] [tgz]
author	Ryan OShea <Ryan.OShea2@arm.com>	Fri Mar 13 16:26:19 2020 +0000
committer	Ryan OShea <Ryan.OShea2@arm.com>	Fri Mar 13 16:26:19 2020 +0000
tree	6c71d89db68da1033bb422253cee2970580ed692
parent	78b26f024641e763c7252198339c83bad8c0982f [diff] [blame]