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<div class="title">RefUnidirectionalSequenceLstmWorkload.cpp</div> </div>
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<a href="_ref_unidirectional_sequence_lstm_workload_8cpp.html">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 © 2021-2023 Arm Ltd and Contributors. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160; </div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_ref_unidirectional_sequence_lstm_workload_8hpp.html">RefUnidirectionalSequenceLstmWorkload.hpp</a>&quot;</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_activation_8hpp.html">Activation.hpp</a>&quot;</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_encoders_8hpp.html">Encoders.hpp</a>&quot;</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_decoders_8hpp.html">Decoders.hpp</a>&quot;</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_lstm_8hpp.html">Lstm.hpp</a>&quot;</span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_lstm_utils_8hpp.html">LstmUtils.hpp</a>&quot;</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_ref_workload_utils_8hpp.html">RefWorkloadUtils.hpp</a>&quot;</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="preprocessor">#include &lt;<a class="code" href="_permute_8hpp.html">armnnUtils/Permute.hpp</a>&gt;</span></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;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;{</div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; </div>
<div class="line"><a name="l00019"></a><span class="lineno"><a class="line" href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#a012324a56cbf03d956d317178a0c4923"> 19</a></span>&#160;<a class="code" href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#a012324a56cbf03d956d317178a0c4923">RefUnidirectionalSequenceLstmWorkload::RefUnidirectionalSequenceLstmWorkload</a>(</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.html">UnidirectionalSequenceLstmQueueDescriptor</a>&amp; descriptor,</div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.html">WorkloadInfo</a>&amp; info)</div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; : <a class="code" href="classarmnn_1_1_ref_base_workload.html">RefBaseWorkload</a>&lt;<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.html">UnidirectionalSequenceLstmQueueDescriptor</a>&gt;(descriptor, <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; , m_InputToInputWeightsTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputToInputWeights))</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; , m_InputToForgetWeightsTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputToForgetWeights))</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; , m_InputToCellWeightsTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputToCellWeights))</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; , m_InputToOutputWeightsTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputToOutputWeights))</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; , m_RecurrentToInputWeightsTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_RecurrentToInputWeights))</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; , m_RecurrentToForgetWeightsTensor(<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_RecurrentToForgetWeights))</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; , m_RecurrentToCellWeightsTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_RecurrentToCellWeights))</div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; , m_RecurrentToOutputWeightsTensor(<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_RecurrentToOutputWeights))</div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; , m_CellToInputWeightsTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_CellToInputWeights))</div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; , m_CellToForgetWeightsTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_CellToForgetWeights))</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; , m_CellToOutputWeightsTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_CellToOutputWeights))</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; , m_InputGateBiasTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputGateBias))</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; , m_ForgetGateBiasTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_ForgetGateBias))</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; , m_CellBiasTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_CellBias))</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; , m_OutputGateBiasTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_OutputGateBias))</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; , m_ProjectionWeightsTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_ProjectionWeights))</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; , m_ProjectionBiasTensor (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_ProjectionBias))</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; , m_InputLayerNormWeights (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_InputLayerNormWeights))</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; , m_ForgetLayerNormWeights (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_ForgetLayerNormWeights))</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; , m_CellLayerNormWeights (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_CellLayerNormWeights))</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; , m_OutputLayerNormWeights (<a class="code" href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a>(descriptor.m_OutputLayerNormWeights))</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"> 45</span>&#160; </div>
<div class="line"><a name="l00046"></a><span class="lineno"><a class="line" href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#ae071e8822437c78baea75c3aef3a263a"> 46</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#ae071e8822437c78baea75c3aef3a263a">RefUnidirectionalSequenceLstmWorkload::Execute</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <a class="code" href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#ae071e8822437c78baea75c3aef3a263a">Execute</a>(<a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>, <a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>);</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;}</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; </div>
<div class="line"><a name="l00051"></a><span class="lineno"><a class="line" href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#ae1c43d025fc90382d7aff7a500937e2c"> 51</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#ae1c43d025fc90382d7aff7a500937e2c">RefUnidirectionalSequenceLstmWorkload::ExecuteAsync</a>(<a class="code" href="structarmnn_1_1experimental_1_1_execution_data.html">ExecutionData</a>&amp; executionData)</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160;{</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; <a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html">WorkingMemDescriptor</a>* workingMemDescriptor = <span class="keyword">static_cast&lt;</span><a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html">WorkingMemDescriptor</a>*<span class="keyword">&gt;</span>(executionData.<a class="code" href="structarmnn_1_1experimental_1_1_execution_data.html#ad2b382076f26f48cd44783cfca2e3642">m_Data</a>);</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <a class="code" href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#ae071e8822437c78baea75c3aef3a263a">Execute</a>(workingMemDescriptor-&gt;<a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>, workingMemDescriptor-&gt;<a class="code" href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>);</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;}</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; </div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#ae071e8822437c78baea75c3aef3a263a">RefUnidirectionalSequenceLstmWorkload::Execute</a>(std::vector&lt;ITensorHandle*&gt; inputs,</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; std::vector&lt;ITensorHandle*&gt; outputs)<span class="keyword"> const</span></div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <a class="code" href="_ref_workload_utils_8hpp.html#a06acca4fd832e0fb179604112c0505af">ARMNN_SCOPED_PROFILING_EVENT_REF_NAME_GUID</a>(<span class="stringliteral">&quot;RefUnidirectionalSequenceLstmWorkload_Execute&quot;</span>);</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; </div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo = <a class="code" href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">GetTensorInfo</a>(inputs[0]);</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; outputStateInfo = <a class="code" href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">GetTensorInfo</a>(inputs[1]);</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; cellStateInfo = <a class="code" href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">GetTensorInfo</a>(inputs[2]);</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputStateOutInfo = <a class="code" href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">GetTensorInfo</a>(outputs[0]);</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> cellStateOutInfo = <a class="code" href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">GetTensorInfo</a>(outputs[1]);</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">GetTensorInfo</a>(outputs[2]);</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; inputShape = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; outputShape= outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; <span class="keyword">auto</span> inputTensor = <span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span>*<span class="keyword">&gt;</span>(inputs[0]-&gt;Map());</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; </div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a>)</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; {</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <span class="comment">// Permute to time major</span></div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a>&amp; mappings = {1U, 0U, 2U};</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; std::vector&lt;float&gt; inputValue(inputTensor, inputTensor + inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; inputShape = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), mappings);</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(inputShape);</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(inputShape, mappings, inputValue.data(), inputTensor, <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>));</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; </div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; outputShape = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), mappings);</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(outputShape);</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; }</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="comment">// As it is permuted to time major, maxTime is inputShape[0].</span></div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> maxTime = inputShape[0];</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = inputShape[1];</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = outputShape[2];</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = inputShape[2];</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; </div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; TensorInfo scratchInfo = outputInfo;</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; scratchInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({batchSize, cellStateInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[1]});</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; std::vector&lt;float&gt; inputGateScratchBuffer;</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; std::vector&lt;float&gt; cellScratchBuffer(scratchInfo.GetNumElements(), 0.);</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; std::vector&lt;float&gt; forgetGateScratchBuffer(scratchInfo.GetNumElements(), 0.);</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; std::vector&lt;float&gt; outputGateScratchBuffer(scratchInfo.GetNumElements(), 0.);</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; std::vector&lt;float&gt; outputStateOutBuffer(outputStateInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(), 0.);</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; std::vector&lt;float&gt; cellStateOutBuffer(cellStateInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(), 0.);</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; </div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="keywordtype">void</span>* outputStateOutData = outputStateOutBuffer.data();</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keywordtype">void</span>* cellStateOutData = cellStateOutBuffer.data();</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; std::unique_ptr&lt;Encoder&lt;float&gt;&gt; inputGateScratch;</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; std::unique_ptr&lt;Encoder&lt;float&gt;&gt; cellScratch = MakeEncoder&lt;float&gt;(scratchInfo, cellScratchBuffer.data());</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; std::unique_ptr&lt;Encoder&lt;float&gt;&gt; forgetGateScratch = MakeEncoder&lt;float&gt;(scratchInfo, forgetGateScratchBuffer.data());</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; std::unique_ptr&lt;Encoder&lt;float&gt;&gt; outputGateScratch = MakeEncoder&lt;float&gt;(scratchInfo, outputGateScratchBuffer.data());</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; </div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; inputGateScratchDecoder;</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; cellScratchDecoder = MakeDecoder&lt;float&gt;(scratchInfo, cellScratchBuffer.data());</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; forgetGateScratchDecoder = MakeDecoder&lt;float&gt;(scratchInfo,</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; forgetGateScratchBuffer.data());</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; outputGateScratchDecoder = MakeDecoder&lt;float&gt;(scratchInfo,</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; outputGateScratchBuffer.data());</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; </div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; <span class="keyword">const</span> <span class="keywordtype">bool</span> useCifg = <a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a>;</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <span class="keyword">const</span> <span class="keywordtype">bool</span> usePeephole = <a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a>;</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="keyword">const</span> <span class="keywordtype">bool</span> useLayerNorm = <a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a>;</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; </div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keywordflow">if</span> (!useCifg)</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; {</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; inputGateScratchBuffer.resize(scratchInfo.GetNumElements(), 0.);</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; inputGateScratch = MakeEncoder&lt;float&gt;(scratchInfo, inputGateScratchBuffer.data());</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; inputGateScratchDecoder = MakeDecoder&lt;float&gt;(scratchInfo, inputGateScratchBuffer.data());</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; }</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; </div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; std::unique_ptr&lt;Encoder&lt;float&gt;&gt; outputStateOut = MakeEncoder&lt;float&gt;(outputStateInfo, outputStateOutData);</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; std::unique_ptr&lt;Encoder&lt;float&gt;&gt; cellStateOut = MakeEncoder&lt;float&gt;(cellStateInfo, cellStateOutData);</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; cellStateOutDecoder = MakeDecoder&lt;float&gt;(cellStateInfo, cellStateOutData);</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; </div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; TensorInfo lstmInputInfo = inputInfo;</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; TensorShape batchInputShape = TensorShape({batchSize, inputSize});</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; lstmInputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(batchInputShape);</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; TensorInfo lstmOutputInfo = outputInfo;</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; lstmOutputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({batchSize, outputSize});</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; </div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="keyword">const</span> TensorShape&amp; inputToOutputWeightsShape = m_InputToOutputWeightsTensor-&gt;GetShape();</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <span class="keyword">const</span> TensorShape&amp; recurrentToOutputWeightsShape = m_RecurrentToOutputWeightsTensor-&gt;GetShape();</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> nOutput = recurrentToOutputWeightsShape[1];</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; <span class="keyword">auto</span> outputStateInData = inputs[1]-&gt;Map();</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; outputStateIn = MakeDecoder&lt;float&gt;(outputStateInfo, outputStateInData);</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; </div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keyword">auto</span> cellStateInData = inputs[2]-&gt;Map();</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; cellStateIn = MakeDecoder&lt;float&gt;(cellStateInfo, cellStateInData);</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; </div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; <span class="keyword">auto</span> currentInputData = <span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span>*<span class="keyword">&gt;</span>(inputs[0]-&gt;Map());</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; inputData = MakeDecoder&lt;float&gt;(lstmInputInfo, currentInputData);</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; <span class="keyword">auto</span> currentOutputData = <span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span>*<span class="keyword">&gt;</span>(outputs[2]-&gt;Map());</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; std::unique_ptr&lt;Encoder&lt;float&gt;&gt; output = MakeEncoder&lt;float&gt;(lstmOutputInfo, currentOutputData);</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; outputDecoder = MakeDecoder&lt;float&gt;(lstmOutputInfo, currentOutputData);</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; </div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; inputToInputWeightsTensor;</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; inputToForgetWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; m_InputToForgetWeightsTensor-&gt;GetTensorInfo(), m_InputToForgetWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; inputToCellWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; m_InputToCellWeightsTensor-&gt;GetTensorInfo(), m_InputToCellWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; inputToOutputWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; m_InputToOutputWeightsTensor-&gt;GetTensorInfo(), m_InputToOutputWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</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; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; recurrentToInputWeightsTensor;</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; recurrentToForgetWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; m_RecurrentToForgetWeightsTensor-&gt;GetTensorInfo(), m_RecurrentToForgetWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; recurrentToCellWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; m_RecurrentToCellWeightsTensor-&gt;GetTensorInfo(), m_RecurrentToCellWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; recurrentToOutputWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; m_RecurrentToOutputWeightsTensor-&gt;GetTensorInfo(), m_RecurrentToOutputWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; </div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; inputGateBiasTensor;</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; forgetGateBiasTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; m_ForgetGateBiasTensor-&gt;GetTensorInfo(), m_ForgetGateBiasTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; cellBiasTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; m_CellBiasTensor-&gt;GetTensorInfo(), m_CellBiasTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; outputGateBiasTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; m_OutputGateBiasTensor-&gt;GetTensorInfo(), m_OutputGateBiasTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; </div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; cellToInputWeightsTensor;</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; cellToForgetWeightsTensor;</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; cellToOutputWeightsTensor;</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; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; projectionWeightsTensor;</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; projectionBiasTensor;</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; </div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; inputLayerNormWeights;</div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; forgetLayerNormWeights;</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; cellLayerNormWeights;</div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160; std::unique_ptr&lt;Decoder&lt;float&gt;&gt; outputLayerNormWeights;</div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160; </div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; <span class="keywordflow">if</span> (useLayerNorm)</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; <span class="keywordflow">if</span> (!useCifg)</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; {</div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160; inputLayerNormWeights = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; m_InputLayerNormWeights-&gt;GetTensorInfo(), m_InputLayerNormWeights-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; }</div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; forgetLayerNormWeights = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; m_ForgetLayerNormWeights-&gt;GetTensorInfo(), m_ForgetLayerNormWeights-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; cellLayerNormWeights = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; m_CellLayerNormWeights-&gt;GetTensorInfo(), m_CellLayerNormWeights-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; outputLayerNormWeights = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; m_OutputLayerNormWeights-&gt;GetTensorInfo(), m_OutputLayerNormWeights-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</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; </div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160; <span class="keywordflow">if</span> (!useCifg)</div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; {</div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; inputToInputWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; m_InputToInputWeightsTensor-&gt;GetTensorInfo(), m_InputToInputWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; inputGateBiasTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; m_InputGateBiasTensor-&gt;GetTensorInfo(), m_InputGateBiasTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; recurrentToInputWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; m_RecurrentToInputWeightsTensor-&gt;GetTensorInfo(), m_RecurrentToInputWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</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; </div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; <span class="keywordflow">if</span> (usePeephole)</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; {</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; cellToForgetWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; m_CellToForgetWeightsTensor-&gt;GetTensorInfo(), m_CellToForgetWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; cellToOutputWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; m_CellToOutputWeightsTensor-&gt;GetTensorInfo(), m_CellToOutputWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; }</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; </div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; <span class="keywordflow">if</span> (!useCifg &amp;&amp; usePeephole)</div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; {</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; cellToInputWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; m_CellToInputWeightsTensor-&gt;GetTensorInfo(), m_CellToInputWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; }</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; </div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a>)</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; projectionWeightsTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; m_ProjectionWeightsTensor-&gt;GetTensorInfo(), m_ProjectionWeightsTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160; <span class="keywordflow">if</span> (m_ProjectionBiasTensor)</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; {</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; projectionBiasTensor = MakeDecoder&lt;float&gt;(</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; m_ProjectionBiasTensor-&gt;GetTensorInfo(), m_ProjectionBiasTensor-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;());</div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; }</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160; }</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; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchInputSize = batchSize * inputSize;</div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchOutputSize = batchSize * nOutput;</div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; </div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> t = 0; t &lt; maxTime; ++t)</div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; {</div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; <a class="code" href="namespacearmnn.html#a952423703fa6b92f18d19df3995633b4">LstmImpl</a>(<a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>,</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; lstmInputInfo,</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; lstmOutputInfo,</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; inputToOutputWeightsShape,</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; recurrentToOutputWeightsShape,</div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; inputData,</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; outputStateIn,</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; cellStateIn,</div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; outputStateOut,</div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; cellStateOut,</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; output,</div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; cellStateOutDecoder,</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; outputDecoder,</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; inputToInputWeightsTensor,</div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; inputToForgetWeightsTensor,</div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; inputToCellWeightsTensor,</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; inputToOutputWeightsTensor,</div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; recurrentToInputWeightsTensor,</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; recurrentToForgetWeightsTensor,</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; recurrentToCellWeightsTensor,</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; recurrentToOutputWeightsTensor,</div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; cellToInputWeightsTensor,</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; cellToForgetWeightsTensor,</div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; cellToOutputWeightsTensor,</div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; inputGateBiasTensor,</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; forgetGateBiasTensor,</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; cellBiasTensor,</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; outputGateBiasTensor,</div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; projectionWeightsTensor,</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; projectionBiasTensor,</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; inputLayerNormWeights,</div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; forgetLayerNormWeights,</div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; cellLayerNormWeights,</div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160; outputLayerNormWeights,</div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; inputGateScratch,</div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; cellScratch,</div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; forgetGateScratch,</div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; outputGateScratch,</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; inputGateScratchDecoder,</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; cellScratchDecoder,</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; forgetGateScratchDecoder,</div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; outputGateScratchDecoder,</div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; m_LayerNormEpsilon);</div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; </div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; currentInputData += batchInputSize;</div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; inputData = MakeDecoder&lt;float&gt;(lstmInputInfo, currentInputData);</div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; currentOutputData += batchOutputSize;</div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; output = MakeEncoder&lt;float&gt;(lstmOutputInfo, currentOutputData);</div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; outputDecoder = MakeDecoder&lt;float&gt;(lstmOutputInfo, currentOutputData);</div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160; </div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; <span class="comment">// Assign output state out to the next output state in</span></div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; outputStateIn = MakeDecoder&lt;float&gt;(outputStateInfo, outputStateOutData);</div>
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; </div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; <span class="comment">// Assign cell state out to the next cell state in</span></div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; cellStateIn = MakeDecoder&lt;float&gt;(cellStateInfo, cellStateOutData);</div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; }</div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; </div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.html#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a>)</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; {</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; <span class="comment">// Permute Output back to batch major</span></div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; <span class="keyword">const</span> PermutationVector&amp; mappings = {1U, 0U, 2U};</div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; <span class="keyword">auto</span> outputData = <span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span>*<span class="keyword">&gt;</span>(outputs[2]-&gt;Map());</div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; std::vector&lt;float&gt; outputValue(outputData, outputData + outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; outputShape = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), mappings);</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(outputShape);</div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(outputShape, mappings, outputValue.data(), outputData, <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>));</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160; }</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160;}</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160; </div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160;} <span class="comment">//namespace armnn</span></div>
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</div><!-- doc-content -->
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00198">Tensor.hpp:198</a></div></div>
<div class="ttc" id="astructarmnn_1_1_lstm_descriptor_html_a3dcd10ca3ea2e132558b1e2814668c15"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.html#a3dcd10ca3ea2e132558b1e2814668c15">armnn::LstmDescriptor::m_TimeMajor</a></div><div class="ttdeci">bool m_TimeMajor</div><div class="ttdoc">Enable/disable time major.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01154">Descriptors.hpp:1154</a></div></div>
<div class="ttc" id="a_lstm_8hpp_html"><div class="ttname"><a href="_lstm_8hpp.html">Lstm.hpp</a></div></div>
<div class="ttc" id="astructarmnn_1_1experimental_1_1_execution_data_html_ad2b382076f26f48cd44783cfca2e3642"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_execution_data.html#ad2b382076f26f48cd44783cfca2e3642">armnn::experimental::ExecutionData::m_Data</a></div><div class="ttdeci">void * m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_execution_data_8hpp_source.html#l00016">ExecutionData.hpp:16</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="a_lstm_utils_8cpp_html_a8618ae0c77638e01069fdb0063cabb3f"><div class="ttname"><a href="_lstm_utils_8cpp.html#a8618ae0c77638e01069fdb0063cabb3f">AssignScopedTensorHandle</a></div><div class="ttdeci">std::unique_ptr&lt; armnn::ScopedTensorHandle &gt; AssignScopedTensorHandle(const armnn::ConstTensorHandle *ptr)</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_utils_8cpp_source.html#l00299">LstmUtils.cpp:299</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_ref_unidirectional_sequence_lstm_workload_html_ae1c43d025fc90382d7aff7a500937e2c"><div class="ttname"><a href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#ae1c43d025fc90382d7aff7a500937e2c">armnn::RefUnidirectionalSequenceLstmWorkload::ExecuteAsync</a></div><div class="ttdeci">void ExecuteAsync(ExecutionData &amp;executionData) override</div><div class="ttdef"><b>Definition:</b> <a href="_ref_unidirectional_sequence_lstm_workload_8cpp_source.html#l00051">RefUnidirectionalSequenceLstmWorkload.cpp:51</a></div></div>
<div class="ttc" id="a_ref_workload_utils_8hpp_html_a06acca4fd832e0fb179604112c0505af"><div class="ttname"><a href="_ref_workload_utils_8hpp.html#a06acca4fd832e0fb179604112c0505af">ARMNN_SCOPED_PROFILING_EVENT_REF_NAME_GUID</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_REF_NAME_GUID(label)</div><div class="ttdoc">Creates a profiling event that uses GetGuid() and GetName() from the calling class.</div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_utils_8hpp_source.html#l00022">RefWorkloadUtils.hpp:22</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_af3c74017185773dd61d8ca6662d65d43"><div class="ttname"><a href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a></div><div class="ttdeci">void Permute(const armnn::TensorShape &amp;dstShape, const armnn::PermutationVector &amp;mappings, const void *src, void *dst, size_t dataTypeSize)</div><div class="ttdef"><b>Definition:</b> <a href="_permute_8cpp_source.html#l00164">Permute.cpp:164</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_html_abeaf4f6785039866fd075f4569ba8e84"><div class="ttname"><a href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a></div><div class="ttdeci">armnn::TensorShape Permuted(const armnn::TensorShape &amp;srcShape, const armnn::PermutationVector &amp;mappings)</div><div class="ttdef"><b>Definition:</b> <a href="_permute_8cpp_source.html#l00125">Permute.cpp:125</a></div></div>
<div class="ttc" id="astructarmnn_1_1_lstm_descriptor_html_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.html#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01148">Descriptors.hpp:1148</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a952423703fa6b92f18d19df3995633b4"><div class="ttname"><a href="namespacearmnn.html#a952423703fa6b92f18d19df3995633b4">armnn::LstmImpl</a></div><div class="ttdeci">void LstmImpl(const LstmDescriptor &amp;descriptor, const TensorInfo &amp;inputInfo, const TensorInfo &amp;outputInfo, const TensorShape &amp;inputToOutputWeightsShape, const TensorShape &amp;recurrentToOutputWeightsShape, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;inputData, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;outputStateIn, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;cellStateIn, std::unique_ptr&lt; Encoder&lt; float &gt;&gt; &amp;outputStateOut, std::unique_ptr&lt; Encoder&lt; float &gt;&gt; &amp;cellStateOut, std::unique_ptr&lt; Encoder&lt; float &gt;&gt; &amp;output, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;cellStateOutDecoder, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;outputDecoder, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;inputToInputWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;inputToForgetWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;inputToCellWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;inputToOutputWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;recurrentToInputWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;recurrentToForgetWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;recurrentToCellWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;recurrentToOutputWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;cellToInputWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;cellToForgetWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;cellToOutputWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;inputGateBiasTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;forgetGateBiasTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;cellBiasTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;outputGateBiasTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;projectionWeightsTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;projectionBiasTensor, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;inputLayerNormWeights, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;forgetLayerNormWeights, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;cellLayerNormWeights, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;outputLayerNormWeights, std::unique_ptr&lt; Encoder&lt; float &gt;&gt; &amp;inputGateScratch, std::unique_ptr&lt; Encoder&lt; float &gt;&gt; &amp;cellScratch, std::unique_ptr&lt; Encoder&lt; float &gt;&gt; &amp;forgetGateScratch, std::unique_ptr&lt; Encoder&lt; float &gt;&gt; &amp;outputGateScratch, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;inputGateScratchDecoder, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;cellScratchDecoder, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;forgetGateScratchDecoder, std::unique_ptr&lt; Decoder&lt; float &gt;&gt; &amp;outputGateScratchDecoder, float layerNormEpsilon)</div><div class="ttdef"><b>Definition:</b> <a href="_lstm_8cpp_source.html#l00013">Lstm.cpp:13</a></div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_with_parameters_html_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00066">WorkloadData.hpp:66</a></div></div>
<div class="ttc" id="astructarmnn_1_1_workload_info_html"><div class="ttname"><a href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer.</div><div class="ttdef"><b>Definition:</b> <a href="_workload_info_8hpp_source.html#l00016">WorkloadInfo.hpp:16</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_ref_unidirectional_sequence_lstm_workload_html_a012324a56cbf03d956d317178a0c4923"><div class="ttname"><a href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#a012324a56cbf03d956d317178a0c4923">armnn::RefUnidirectionalSequenceLstmWorkload::RefUnidirectionalSequenceLstmWorkload</a></div><div class="ttdeci">RefUnidirectionalSequenceLstmWorkload(const UnidirectionalSequenceLstmQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info)</div><div class="ttdef"><b>Definition:</b> <a href="_ref_unidirectional_sequence_lstm_workload_8cpp_source.html#l00019">RefUnidirectionalSequenceLstmWorkload.cpp:19</a></div></div>
<div class="ttc" id="anamespacearmnn_html_aa815fde54f6d8e8aa5b4f0301cf4178b"><div class="ttname"><a href="namespacearmnn.html#aa815fde54f6d8e8aa5b4f0301cf4178b">armnn::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo(const ITensorHandle *tensorHandle)</div><div class="ttdoc">float32 helpers</div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_utils_8hpp_source.html#l00033">RefWorkloadUtils.hpp:33</a></div></div>
<div class="ttc" id="a_activation_8hpp_html"><div class="ttname"><a href="_activation_8hpp.html">Activation.hpp</a></div></div>
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<div class="ttc" id="a_permute_8hpp_html"><div class="ttname"><a href="_permute_8hpp.html">Permute.hpp</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div><div class="ttdeci">@ info</div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_html_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00027">WorkloadData.hpp:27</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_ref_unidirectional_sequence_lstm_workload_html_ae071e8822437c78baea75c3aef3a263a"><div class="ttname"><a href="classarmnn_1_1_ref_unidirectional_sequence_lstm_workload.html#ae071e8822437c78baea75c3aef3a263a">armnn::RefUnidirectionalSequenceLstmWorkload::Execute</a></div><div class="ttdeci">void Execute() const override</div><div class="ttdef"><b>Definition:</b> <a href="_ref_unidirectional_sequence_lstm_workload_8cpp_source.html#l00046">RefUnidirectionalSequenceLstmWorkload.cpp:46</a></div></div>
<div class="ttc" id="a_ref_workload_utils_8hpp_html"><div class="ttname"><a href="_ref_workload_utils_8hpp.html">RefWorkloadUtils.hpp</a></div></div>
<div class="ttc" id="astructarmnn_1_1_lstm_descriptor_html_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.html#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input &amp; forget gate).</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01146">Descriptors.hpp:1146</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_base_workload_html_afb8d2c8817c75de9d01a4c0e0d5c160b"><div class="ttname"><a href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">armnn::BaseWorkload&lt; UnidirectionalSequenceLstmQueueDescriptor &gt;::m_Data</a></div><div class="ttdeci">UnidirectionalSequenceLstmQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.html#l00089">Workload.hpp:89</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#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.html#l00193">Tensor.hpp:193</a></div></div>
<div class="ttc" id="astructarmnn_1_1_lstm_descriptor_html_a4a8ec49f130084445d44297549254780"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.html#a4a8ec49f130084445d44297549254780">armnn::LstmDescriptor::m_LayerNormEnabled</a></div><div class="ttdeci">bool m_LayerNormEnabled</div><div class="ttdoc">Enable/disable layer normalization.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01152">Descriptors.hpp:1152</a></div></div>
<div class="ttc" id="a_decoders_8hpp_html"><div class="ttname"><a href="_decoders_8hpp.html">Decoders.hpp</a></div></div>
<div class="ttc" id="astructarmnn_1_1experimental_1_1_working_mem_descriptor_html_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">armnn::experimental::WorkingMemDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_descriptor_8hpp_source.html#l00020">WorkingMemDescriptor.hpp:20</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_abe8889e8150beef5fd204b2d87b49298"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">armnn::TensorInfo::SetShape</a></div><div class="ttdeci">void SetShape(const TensorShape &amp;newShape)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00195">Tensor.hpp:195</a></div></div>
<div class="ttc" id="anamespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors.</div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.html#l00006">01_00_quick_start.dox:6</a></div></div>
<div class="ttc" id="astructarmnn_1_1experimental_1_1_working_mem_descriptor_html"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html">armnn::experimental::WorkingMemDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_descriptor_8hpp_source.html#l00018">WorkingMemDescriptor.hpp:18</a></div></div>
<div class="ttc" id="astructarmnn_1_1_lstm_descriptor_html_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.html#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01150">Descriptors.hpp:1150</a></div></div>
<div class="ttc" id="astructarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.html">armnn::UnidirectionalSequenceLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00696">WorkloadData.hpp:696</a></div></div>
<div class="ttc" id="a_lstm_utils_8hpp_html"><div class="ttname"><a href="_lstm_utils_8hpp.html">LstmUtils.hpp</a></div></div>
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<div class="ttc" id="aclassarmnn_1_1_ref_base_workload_html"><div class="ttname"><a href="classarmnn_1_1_ref_base_workload.html">armnn::RefBaseWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_ref_base_workload_8hpp_source.html#l00013">RefBaseWorkload.hpp:13</a></div></div>
<div class="ttc" id="a_ref_unidirectional_sequence_lstm_workload_8hpp_html"><div class="ttname"><a href="_ref_unidirectional_sequence_lstm_workload_8hpp.html">RefUnidirectionalSequenceLstmWorkload.hpp</a></div></div>
<div class="ttc" id="astructarmnn_1_1experimental_1_1_working_mem_descriptor_html_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_working_mem_descriptor.html#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::experimental::WorkingMemDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_working_mem_descriptor_8hpp_source.html#l00021">WorkingMemDescriptor.hpp:21</a></div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_html_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.html#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector&lt; ITensorHandle * &gt; m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00026">WorkloadData.hpp:26</a></div></div>
<div class="ttc" id="astructarmnn_1_1experimental_1_1_execution_data_html"><div class="ttname"><a href="structarmnn_1_1experimental_1_1_execution_data.html">armnn::experimental::ExecutionData</a></div><div class="ttdef"><b>Definition:</b> <a href="_execution_data_8hpp_source.html#l00014">ExecutionData.hpp:14</a></div></div>
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