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<div class="title">NeonGatherNdWorkload.cpp</div> </div>
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<a href="_neon_gather_nd_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 © 2022-2024 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="_neon_gather_nd_workload_8hpp.html">NeonGatherNdWorkload.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="_neon_workload_utils_8hpp.html">NeonWorkloadUtils.hpp</a>&quot;</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_polymorphic_downcast_8hpp.html">armnn/utility/PolymorphicDowncast.hpp</a>&gt;</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_arm_compute_utils_8hpp.html">aclCommon/ArmComputeUtils.hpp</a>&gt;</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_workload_utils_8hpp.html">backendsCommon/WorkloadUtils.hpp</a>&quot;</span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160; </div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;{</div>
<div class="line"><a name="l00014"></a><span class="lineno"><a class="line" href="namespacearmnn.html#aec41b8c86e61ce02a07b8215bf8bc073"> 14</a></span>&#160;<a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> <a class="code" href="namespacearmnn.html#aec41b8c86e61ce02a07b8215bf8bc073">NeonGatherNdWorkloadValidate</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; paramsInfo,</div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; indicesInfo,</div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; outputInfo)</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; <span class="comment">// Calculate ND, K, W, C.</span></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; std::map&lt;std::string, unsigned int&gt; keyIndices = <a class="code" href="namespacearmnn.html#ac40d3e4035af5fbe68d9e126a8d6367c">CalculateGatherNdKeyIndices</a>(paramsInfo, indicesInfo);</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment"> /// Validate Mul</span></div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"></span> <span class="comment">// Indices with shape { W, ND }</span></div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> indices_W_ND_Info = indicesInfo;</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; indices_W_ND_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ keyIndices[<span class="stringliteral">&quot;W&quot;</span>], keyIndices[<span class="stringliteral">&quot;ND&quot;</span>] });</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclIndicesInfo = BuildArmComputeTensorInfo(indices_W_ND_Info);</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; </div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; <span class="comment">// Flattened coefficients with shape { ND }</span></div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> flattenedCoeff_Info = indicesInfo;</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; flattenedCoeff_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ keyIndices[<span class="stringliteral">&quot;ND&quot;</span>] });</div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclFlattenedCoeffInfo = BuildArmComputeTensorInfo(flattenedCoeff_Info);</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; <span class="comment">// Output of Mul with shape { W, ND }</span></div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclOutputMulInfo = BuildArmComputeTensorInfo(indices_W_ND_Info);</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; </div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; <span class="keyword">auto</span> statusMul = arm_compute::NEPixelWiseMultiplication::validate(&amp;aclIndicesInfo,</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; &amp;aclFlattenedCoeffInfo,</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; &amp;aclOutputMulInfo,</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; 1.0f,</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; arm_compute::ConvertPolicy::WRAP,</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; arm_compute::RoundingPolicy::TO_ZERO,</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; arm_compute::ActivationLayerInfo());</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;<span class="comment"> /// Validate ReduceSum</span></div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;<span class="comment"></span> <span class="comment">// Flattened indices with shape { W }</span></div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> flattenedIndices_Info = indicesInfo;</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; flattenedIndices_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ keyIndices[<span class="stringliteral">&quot;W&quot;</span>] });</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclFlattenedIndicesInfo = BuildArmComputeTensorInfo(flattenedIndices_Info);</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; <span class="keyword">const</span> std::vector&lt;unsigned int&gt; armnnReduceAxes(1, 1);</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <a class="code" href="namespacearmnn.html#ac6e86c1def7f674d3c4cb7f577874aa6">arm_compute::Coordinates</a> coords = BuildArmComputeReductionCoordinates(aclOutputMulInfo.num_dimensions(),</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; indices_W_ND_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(),</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; armnnReduceAxes);</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; </div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="keyword">auto</span> statusReduceSum = arm_compute::NEReductionOperation::validate(&amp;aclOutputMulInfo,</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; &amp;aclFlattenedIndicesInfo,</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(coords[0]),</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; arm_compute::ReductionOperation::SUM,</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="keyword">false</span>);</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160;<span class="comment"> /// Validate Gather</span></div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160;<span class="comment"></span> <span class="comment">// Params with shape { K, C }</span></div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> params_K_C_Info = paramsInfo;</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; params_K_C_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ keyIndices[<span class="stringliteral">&quot;K&quot;</span>], keyIndices[<span class="stringliteral">&quot;C&quot;</span>] });</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclParamsInfo = BuildArmComputeTensorInfo(params_K_C_Info);</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; </div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="comment">// Output of gather with shape { W, C }</span></div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputGather_Info = outputInfo;</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; outputGather_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ keyIndices[<span class="stringliteral">&quot;W&quot;</span>], keyIndices[<span class="stringliteral">&quot;C&quot;</span>] });</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="keyword">const</span> arm_compute::TensorInfo aclOutputGatherInfo = BuildArmComputeTensorInfo(outputGather_Info);</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; </div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <span class="keyword">auto</span> aclAxis = <a class="code" href="namespacearmnn.html#a44a3b98b37a25c995aa9e4dae7d7b456">ComputeAclAxis</a>(0, params_K_C_Info);</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <span class="keyword">auto</span> statusGather =</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; arm_compute::NEGather::validate(&amp;aclParamsInfo, &amp;aclFlattenedIndicesInfo, &amp;aclOutputGatherInfo, aclAxis);</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160;<span class="comment"> /// Validate Reshape</span></div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160;<span class="comment"></span> <span class="keyword">const</span> arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(outputInfo);</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; <span class="keyword">auto</span> statusReshape = arm_compute::NEReshapeLayer::validate(&amp;aclOutputGatherInfo, &amp;aclOutputInfo);</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;<span class="comment"> /// Return OK if all the layers are valid</span></div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160;<span class="comment"></span> <span class="keyword">auto</span> okCode = arm_compute::ErrorCode::OK;</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="keywordflow">if</span> (statusMul.error_code() == okCode &amp;&amp;</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; statusReduceSum.error_code() == okCode &amp;&amp;</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; statusGather.error_code() == okCode &amp;&amp;</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; statusReshape.error_code() == okCode)</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; <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::OK,</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <span class="stringliteral">&quot;All GatherND layers validate status OK.&quot;</span>);</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; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; {</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.html#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::RUNTIME_ERROR,</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="stringliteral">&quot;GatherND layer validate status failed.&quot;</span>);</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; }</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; </div>
<div class="line"><a name="l00097"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_gather_nd_workload.html#aed7f95d9f00861351b0bd4d7b17e27b2"> 97</a></span>&#160;<a class="code" href="classarmnn_1_1_neon_gather_nd_workload.html#aed7f95d9f00861351b0bd4d7b17e27b2">NeonGatherNdWorkload::NeonGatherNdWorkload</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_gather_nd_queue_descriptor.html">GatherNdQueueDescriptor</a>&amp; descriptor,</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</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="l00099"></a><span class="lineno"> 99</span>&#160; : <a class="code" href="classarmnn_1_1_neon_base_workload.html">NeonBaseWorkload</a>&lt;<a class="code" href="structarmnn_1_1_gather_nd_queue_descriptor.html">GatherNdQueueDescriptor</a>&gt;(descriptor, <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</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; <a class="code" href="classarmnn_1_1_base_workload.html#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.html#a765d2cee4ccce5b9467e0c2b6d25b84a">ValidateInputsOutputs</a>(<span class="stringliteral">&quot;NeonGatherNdWorkload&quot;</span>, 2, 1);</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; </div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> paramsInfo = <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos[0];</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> indicesInfo = <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos[1];</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputInfo = <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_OutputTensorInfos[0];</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; arm_compute::ITensor&amp; input = PolymorphicDowncast&lt;IAclTensorHandle*&gt;(<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>[0])-&gt;GetTensor();</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; arm_compute::ITensor&amp; indices = PolymorphicDowncast&lt;IAclTensorHandle*&gt;(<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>[1])-&gt;GetTensor();</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; arm_compute::ITensor&amp; output = PolymorphicDowncast&lt;IAclTensorHandle*&gt;(<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>[0])-&gt;GetTensor();</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; </div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="comment">// Calculate ND, K, W, C.</span></div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; std::map&lt;std::string, unsigned int&gt; keyIndices = <a class="code" href="namespacearmnn.html#ac40d3e4035af5fbe68d9e126a8d6367c">CalculateGatherNdKeyIndices</a>(paramsInfo, indicesInfo);</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160;<span class="comment"> /// Calculate flattened indices: m_FlattenedIndices = indices * m_FlattenedCoeff.</span></div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160;<span class="comment"> /// This could be done using MatMul instead of multiplication followed by reduce sum operation,</span></div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160;<span class="comment"> /// but GeMM does not support s32 at the moment.</span></div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="comment">// Prepare the tensor to store the output of the reduce_sum operation</span></div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> flattenedIndices_Info = indicesInfo;</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; flattenedIndices_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ keyIndices[<span class="stringliteral">&quot;W&quot;</span>] });</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; BuildArmComputeTensor(m_FlattenedIndices, flattenedIndices_Info);</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_FlattenedIndices);</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; </div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="comment">// Reshape indices into { W, ND }</span></div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; indices.info()-&gt;set_tensor_shape(BuildArmComputeTensorShape({ keyIndices[<span class="stringliteral">&quot;W&quot;</span>], keyIndices[<span class="stringliteral">&quot;ND&quot;</span>] }));</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; <span class="comment">// Calculate the m_FlattenedCoeff</span></div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> paramsShape = paramsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; std::vector&lt;int32_t&gt; flattenedCoeff(keyIndices[<span class="stringliteral">&quot;ND&quot;</span>], 1);</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 1; i &lt; keyIndices[<span class="stringliteral">&quot;ND&quot;</span>]; ++i)</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; {</div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; flattenedCoeff[i - 1] = <span class="keyword">static_cast&lt;</span>int32_t<span class="keyword">&gt;</span>(paramsShape[i]);</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; }</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = keyIndices[<span class="stringliteral">&quot;ND&quot;</span>] - 1; i &gt; 0; --i)</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; {</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; flattenedCoeff[i - 1] *= flattenedCoeff[i];</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; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> flattenedCoeff_Info = indicesInfo;</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; flattenedCoeff_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ keyIndices[<span class="stringliteral">&quot;ND&quot;</span>] });</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; BuildArmComputeTensor(m_FlattenedCoeff, flattenedCoeff_Info);</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_FlattenedCoeff);</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; CopyArmComputeITensorData&lt;int32_t&gt;(flattenedCoeff.data(), m_FlattenedCoeff);</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="comment">// Prepare the tensor to store the output of the multiplication</span></div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputMul_Info = indicesInfo;</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; outputMul_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ keyIndices[<span class="stringliteral">&quot;W&quot;</span>], keyIndices[<span class="stringliteral">&quot;ND&quot;</span>] });</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; BuildArmComputeTensor(m_OutputMul, outputMul_Info);</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_OutputMul);</div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; </div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="comment">// Multiply</span></div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; m_MulLayer.configure(&amp;indices,</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; &amp;m_FlattenedCoeff,</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; &amp;m_OutputMul,</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; 1.0f,</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; arm_compute::ConvertPolicy::WRAP,</div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; arm_compute::RoundingPolicy::TO_ZERO,</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; arm_compute::ActivationLayerInfo());</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; </div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <span class="comment">// Reduce Sum</span></div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; <span class="keyword">const</span> std::vector&lt;unsigned int&gt; armnnReduceAxes(1, 1);</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <a class="code" href="namespacearmnn.html#ac6e86c1def7f674d3c4cb7f577874aa6">arm_compute::Coordinates</a> coords = BuildArmComputeReductionCoordinates(m_OutputMul.info()-&gt;num_dimensions(),</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; outputMul_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(),</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; armnnReduceAxes);</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; m_ReduceSumLayer.configure(&amp;m_OutputMul,</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; &amp;m_FlattenedIndices,</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(coords[0]),</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; arm_compute::ReductionOperation::SUM,</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; <span class="keyword">false</span>);</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160;<span class="comment"></span> </div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160;<span class="comment"> /// Call Gather with adequate shapes</span></div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160;<span class="comment"></span> <span class="comment">// Reshape params into { K, C }</span></div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; paramsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ keyIndices[<span class="stringliteral">&quot;K&quot;</span>], keyIndices[<span class="stringliteral">&quot;C&quot;</span>] });</div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; input.info()-&gt;set_tensor_shape(BuildArmComputeTensorShape(paramsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()));</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; </div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <span class="comment">// Reshape output to have the shape given by gather { W, C }</span></div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; <span class="comment">// (the original outputInfo has the shape given by gatherNd)</span></div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputGather_Info = outputInfo;</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; outputGather_Info.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ keyIndices[<span class="stringliteral">&quot;W&quot;</span>], keyIndices[<span class="stringliteral">&quot;C&quot;</span>] });</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; BuildArmComputeTensor(m_OutputGather, outputGather_Info);</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; armcomputetensorutils::InitialiseArmComputeTensorEmpty(m_OutputGather);</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; m_GatherLayer.configure(&amp;input, &amp;m_FlattenedIndices, &amp;m_OutputGather, <a class="code" href="namespacearmnn.html#a44a3b98b37a25c995aa9e4dae7d7b456">ComputeAclAxis</a>(0, paramsInfo));</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; <span class="comment">// Reshape output to the original output shape</span></div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; m_ReshapeLayer.configure(&amp;m_OutputGather, &amp;output);</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160;}</div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160; </div>
<div class="line"><a name="l00188"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_gather_nd_workload.html#ae071e8822437c78baea75c3aef3a263a"> 188</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_neon_gather_nd_workload.html#ae071e8822437c78baea75c3aef3a263a">NeonGatherNdWorkload::Execute</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160; <a class="code" href="_neon_workload_utils_8hpp.html#a7f97eedf3c9436b110df92c947bbb55d">ARMNN_SCOPED_PROFILING_EVENT_NEON_NAME_GUID</a>(<span class="stringliteral">&quot;NeonGatherNdWorkload_Execute&quot;</span>);</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; m_MulLayer.run();</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; m_ReduceSumLayer.run();</div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160; m_GatherLayer.run();</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; m_ReshapeLayer.run();</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;} <span class="comment">//namespace armnn</span></div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<div class="ttc" id="astructarmnn_1_1_gather_nd_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_gather_nd_queue_descriptor.html">armnn::GatherNdQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00502">WorkloadData.hpp:502</a></div></div>
<div class="ttc" id="a_workload_utils_8hpp_html"><div class="ttname"><a href="_workload_utils_8hpp.html">WorkloadUtils.hpp</a></div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_html_a765d2cee4ccce5b9467e0c2b6d25b84a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.html#a765d2cee4ccce5b9467e0c2b6d25b84a">armnn::QueueDescriptor::ValidateInputsOutputs</a></div><div class="ttdeci">void ValidateInputsOutputs(const std::string &amp;descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8cpp_source.html#l00447">WorkloadData.cpp:447</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="aclassarmnn_1_1_tensor_info_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00197">Tensor.hpp:197</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_neon_gather_nd_workload_html_aed7f95d9f00861351b0bd4d7b17e27b2"><div class="ttname"><a href="classarmnn_1_1_neon_gather_nd_workload.html#aed7f95d9f00861351b0bd4d7b17e27b2">armnn::NeonGatherNdWorkload::NeonGatherNdWorkload</a></div><div class="ttdeci">NeonGatherNdWorkload(const GatherNdQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_gather_nd_workload_8cpp_source.html#l00097">NeonGatherNdWorkload.cpp:97</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ac6e86c1def7f674d3c4cb7f577874aa6"><div class="ttname"><a href="namespacearmnn.html#ac6e86c1def7f674d3c4cb7f577874aa6">armnn::Coordinates</a></div><div class="ttdeci">std::array&lt; unsigned int, MaxNumOfTensorDimensions &gt; Coordinates</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8hpp_source.html#l00015">InternalTypes.hpp:15</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_aec41b8c86e61ce02a07b8215bf8bc073"><div class="ttname"><a href="namespacearmnn.html#aec41b8c86e61ce02a07b8215bf8bc073">armnn::NeonGatherNdWorkloadValidate</a></div><div class="ttdeci">arm_compute::Status NeonGatherNdWorkloadValidate(const TensorInfo &amp;paramsInfo, const TensorInfo &amp;indicesInfo, const TensorInfo &amp;outputInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_gather_nd_workload_8cpp_source.html#l00014">NeonGatherNdWorkload.cpp:14</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="a_polymorphic_downcast_8hpp_html"><div class="ttname"><a href="_polymorphic_downcast_8hpp.html">PolymorphicDowncast.hpp</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ac40d3e4035af5fbe68d9e126a8d6367c"><div class="ttname"><a href="namespacearmnn.html#ac40d3e4035af5fbe68d9e126a8d6367c">armnn::CalculateGatherNdKeyIndices</a></div><div class="ttdeci">std::map&lt; std::string, unsigned int &gt; CalculateGatherNdKeyIndices(TensorInfo inputInfo0, TensorInfo inputInfo1)</div><div class="ttdoc">Calculates the key index values needed for GatherNd: N, ND, K, W, C (N is always 1)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.html#l00313">WorkloadUtils.cpp:313</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_neon_gather_nd_workload_html_ae071e8822437c78baea75c3aef3a263a"><div class="ttname"><a href="classarmnn_1_1_neon_gather_nd_workload.html#ae071e8822437c78baea75c3aef3a263a">armnn::NeonGatherNdWorkload::Execute</a></div><div class="ttdeci">virtual void Execute() const override</div><div class="ttdef"><b>Definition:</b> <a href="_neon_gather_nd_workload_8cpp_source.html#l00188">NeonGatherNdWorkload.cpp:188</a></div></div>
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<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; GatherNdQueueDescriptor &gt;::m_Data</a></div><div class="ttdeci">GatherNdQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.html#l00089">Workload.hpp:89</a></div></div>
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<div class="ttc" id="a_neon_workload_utils_8hpp_html"><div class="ttname"><a href="_neon_workload_utils_8hpp.html">NeonWorkloadUtils.hpp</a></div></div>
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<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="a_neon_gather_nd_workload_8hpp_html"><div class="ttname"><a href="_neon_gather_nd_workload_8hpp.html">NeonGatherNdWorkload.hpp</a></div></div>
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<div class="ttc" id="aclassarmnn_1_1_neon_base_workload_html"><div class="ttname"><a href="classarmnn_1_1_neon_base_workload.html">armnn::NeonBaseWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_base_workload_8hpp_source.html#l00013">NeonBaseWorkload.hpp:13</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a44a3b98b37a25c995aa9e4dae7d7b456"><div class="ttname"><a href="namespacearmnn.html#a44a3b98b37a25c995aa9e4dae7d7b456">armnn::ComputeAclAxis</a></div><div class="ttdeci">int ComputeAclAxis(const int &amp;armnnAxis, const armnn::TensorInfo &amp;tensor)</div><div class="ttdoc">Function to convert ArmNN axis (left to right) to ACL axis (right to left) ranging from [-rank,...</div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_utils_8hpp_source.html#l00246">ArmComputeUtils.hpp:246</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>
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