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<div class="title">NeonBatchMatMulWorkload.cpp</div> </div>
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<a href="_neon_batch_mat_mul_workload_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>  </div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_neon_batch_mat_mul_workload_8hpp.xhtml">NeonBatchMatMulWorkload.hpp</a>"</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>  </div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_neon_workload_utils_8hpp.xhtml">NeonWorkloadUtils.hpp</a>"</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>  </div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_polymorphic_downcast_8hpp.xhtml">armnn/utility/PolymorphicDowncast.hpp</a>></span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span>  </div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_permute_8hpp.xhtml">armnnUtils/Permute.hpp</a>></span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>  </div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_workload_utils_8hpp.xhtml">backendsCommon/WorkloadUtils.hpp</a>></span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>  </div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <arm_compute/runtime/NEON/functions/NEGEMM.h></span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  </div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <arm_compute/runtime/NEON/functions/NEPermute.h></span></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  </div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  </div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> {</div>
<div class="line"><a name="l00023"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#abc5405fc939efb69e2d630421f0d4271"> 23</a></span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> <a class="code" href="namespacearmnn.xhtml#abc5405fc939efb69e2d630421f0d4271">NeonBatchMatMulValidate</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputX,</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputY,</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& output,</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml">BatchMatMulDescriptor</a>& descriptor)</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> {</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#a0cf8306be7d301de0f095fff9901a525">m_AdjointX</a> || descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#ad945fc98770356dd886a68e98a52e26b">m_AdjointY</a> )</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  {</div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">Exception</a>(<span class="stringliteral">"Support for adjoint not implemented."</span>);</div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  }</div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#aedca000a005e091c23191e82d7e81b1d">m_DataLayoutX</a> != <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a> || descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#aaf7828880989b4b9378d3e86aa6dc843">m_DataLayoutY</a> != <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a> )</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  {</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">Exception</a>(<span class="stringliteral">"Only supported the MatMul in the last 2 dimensions"</span>);</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  }</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  </div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keyword">const</span> <span class="keyword">auto</span> aclInputXInfo = armcomputetensorutils::BuildArmComputeTensorInfo(inputX, descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#aedca000a005e091c23191e82d7e81b1d">m_DataLayoutX</a>);</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keyword">const</span> <span class="keyword">auto</span> aclInputYInfo = armcomputetensorutils::BuildArmComputeTensorInfo(inputY, descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#aaf7828880989b4b9378d3e86aa6dc843">m_DataLayoutY</a>);</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keyword">const</span> <span class="keyword">auto</span> aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  </div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> statusGEMM = <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::OK);</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> statusPermuteX = <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::OK);</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a> statusPermuteY = <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::OK);</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  </div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  arm_compute::TensorInfo aclPermutedXInfo = arm_compute::TensorInfo();</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  arm_compute::TensorInfo aclPermutedYInfo = arm_compute::TensorInfo();</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  </div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#acb441bb8db19bcce78d15cdd8ceb5ea0">m_TransposeX</a> == <span class="keyword">true</span>)</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  {</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="keyword">auto</span> permutationXVector = <a class="code" href="namespacearmnn.xhtml#a15e2ba06d2ecd7ff6013118838e5d1be">GeneratePermutationVectorOnLastTwoDimensions</a>(inputX.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keyword">const</span> <span class="keyword">auto</span> aclPermutationXVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationXVector);</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> permutedXInfo = <a class="code" href="namespacearmnn_utils.xhtml#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(inputX, permutationXVector);</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  aclPermutedXInfo = armcomputetensorutils::BuildArmComputeTensorInfo(permutedXInfo);</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  </div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  statusPermuteX = arm_compute::NEPermute::validate(&aclInputXInfo,</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  &aclPermutedXInfo,</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  aclPermutationXVector);</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  }</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  </div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#a112b466e5d2ab9d1887178adbe3afa1c">m_TransposeY</a> == <span class="keyword">true</span>)</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  {</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keyword">auto</span> permutationYVector = <a class="code" href="namespacearmnn.xhtml#a15e2ba06d2ecd7ff6013118838e5d1be">GeneratePermutationVectorOnLastTwoDimensions</a>(inputY.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>());</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">const</span> <span class="keyword">auto</span> aclPermutationYVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationYVector);</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> permutedYInfo = <a class="code" href="namespacearmnn_utils.xhtml#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(inputY, permutationYVector);</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  aclPermutedYInfo = armcomputetensorutils::BuildArmComputeTensorInfo(permutedYInfo);</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  </div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  statusPermuteY = arm_compute::NEPermute::validate(&aclInputYInfo,</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  &aclPermutedYInfo,</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  aclPermutationYVector);</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  }</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  </div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">const</span> arm_compute::GEMMInfo& gemm_info = arm_compute::GEMMInfo(<span class="keyword">false</span>, <span class="comment">// is inputX reshaped</span></div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">false</span>, <span class="comment">// is inputY reshaped</span></div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">false</span>); <span class="comment">// is inputY reshaped only 1st run</span></div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  </div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  statusGEMM = arm_compute::NEGEMM::validate(descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#acb441bb8db19bcce78d15cdd8ceb5ea0">m_TransposeX</a> ? &aclPermutedXInfo : &aclInputXInfo,</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#a112b466e5d2ab9d1887178adbe3afa1c">m_TransposeY</a> ? &aclPermutedYInfo : &aclInputYInfo,</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">nullptr</span>,</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  &aclOutputInfo,</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  1.0,</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  0,</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  gemm_info);</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  </div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordflow">if</span> (statusPermuteX.error_code() == arm_compute::ErrorCode::OK &&</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  statusPermuteY.error_code() == arm_compute::ErrorCode::OK &&</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  statusGEMM.error_code() == arm_compute::ErrorCode::OK)</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  {</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::OK,</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="stringliteral">"All BatchMatMul layers validate status OK."</span>);</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  }</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  {</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">arm_compute::Status</a>(arm_compute::ErrorCode::RUNTIME_ERROR,</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="stringliteral">"BatchMatMul layer validate status failed."</span></div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  + statusGEMM.error_description()</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  + statusPermuteX.error_description()</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  + statusPermuteY.error_description());</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  }</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  </div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span> }</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  </div>
<div class="line"><a name="l00102"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_batch_mat_mul_workload.xhtml#a2eed4c19f5918cfa8efd910e6195c99c"> 102</a></span> <a class="code" href="classarmnn_1_1_neon_batch_mat_mul_workload.xhtml#a2eed4c19f5918cfa8efd910e6195c99c">NeonBatchMatMulWorkload::NeonBatchMatMulWorkload</a>(</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_batch_mat_mul_queue_descriptor.xhtml">BatchMatMulQueueDescriptor</a>& descriptor, <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a>& info)</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  : <a class="code" href="classarmnn_1_1_neon_base_workload.xhtml">NeonBaseWorkload</a><<a class="code" href="structarmnn_1_1_batch_mat_mul_queue_descriptor.xhtml">BatchMatMulQueueDescriptor</a>>(descriptor, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>)</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span> {</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#a0cf8306be7d301de0f095fff9901a525">m_AdjointX</a> || descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#ad945fc98770356dd886a68e98a52e26b">m_AdjointY</a> )</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  {</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">Exception</a>(<span class="stringliteral">"Support for adjoint not implemented."</span>);</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  }</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#aedca000a005e091c23191e82d7e81b1d">m_DataLayoutX</a> != <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a> ||</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#aaf7828880989b4b9378d3e86aa6dc843">m_DataLayoutY</a> != <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a> )</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  {</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">Exception</a>(<span class="stringliteral">"Only supported the MatMul in the last 2 dimensions"</span>);</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  }</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  </div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="comment">// Report Profiling Details</span></div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a>(<span class="stringliteral">"NeonBatchMatMulWorkload_Construct"</span>,</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>,</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>,</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  this->GetGuid());</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  </div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">ValidateInputsOutputs</a>(<span class="stringliteral">"NeonBatchMatMulWorkload"</span>, 2, 1);</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  </div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  arm_compute::ITensor& inputX = PolymorphicDowncast<IAclTensorHandle*>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0])->GetTensor();</div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  arm_compute::ITensor& inputY = PolymorphicDowncast<IAclTensorHandle*>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[1])->GetTensor();</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]);</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  arm_compute::ITensor& output = outputHandle->GetTensor();</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  </div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a> aclDataLayoutX = ConvertDataLayout(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#aedca000a005e091c23191e82d7e81b1d">m_DataLayoutX</a>);</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a> aclDataLayoutY = ConvertDataLayout(<a class="code" href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">m_Data</a>.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#aaf7828880989b4b9378d3e86aa6dc843">m_DataLayoutY</a>);</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  </div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  inputX.info()->set_data_layout(aclDataLayoutX);</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  inputY.info()->set_data_layout(aclDataLayoutY);</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  </div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#acb441bb8db19bcce78d15cdd8ceb5ea0">m_TransposeX</a> == <span class="keyword">true</span>)</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  {</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> permutationXVector</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  = <a class="code" href="namespacearmnn.xhtml#a15e2ba06d2ecd7ff6013118838e5d1be">GeneratePermutationVectorOnLastTwoDimensions</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos[0].GetNumDimensions());</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> permutedXInfo = <a class="code" href="namespacearmnn_utils.xhtml#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos[0], permutationXVector);</div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keyword">const</span> <span class="keyword">auto</span> aclPermutationXVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationXVector);</div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  </div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="keyword">auto</span> permuteLayerX = std::make_unique<arm_compute::NEPermute>();</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  BuildArmComputeTensor(m_PermutedTensorX, permutedXInfo);</div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  InitialiseArmComputeTensorEmpty(m_PermutedTensorX);</div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  permuteLayerX->configure(&inputX, &m_PermutedTensorX, aclPermutationXVector);</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  m_PermuteLayerX.reset(permuteLayerX.release());</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  }</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  </div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">if</span> (descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#a112b466e5d2ab9d1887178adbe3afa1c">m_TransposeY</a> == <span class="keyword">true</span>)</div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  {</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a> permutationYVector</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  = <a class="code" href="namespacearmnn.xhtml#a15e2ba06d2ecd7ff6013118838e5d1be">GeneratePermutationVectorOnLastTwoDimensions</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos[1].GetNumDimensions());</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> permutedYInfo = <a class="code" href="namespacearmnn_utils.xhtml#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.m_InputTensorInfos[1], permutationYVector);</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keyword">const</span> <span class="keyword">auto</span> aclPermutationYVector = armcomputetensorutils::BuildArmComputePermutationVector(permutationYVector);</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  </div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="keyword">auto</span> permuteLayerY = std::make_unique<arm_compute::NEPermute>();</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  BuildArmComputeTensor(m_PermutedTensorY, permutedYInfo);</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  InitialiseArmComputeTensorEmpty(m_PermutedTensorY);</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  permuteLayerY->configure(&inputY, &m_PermutedTensorY, aclPermutationYVector);</div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  m_PermuteLayerY.reset(permuteLayerY.release());</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  }</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  </div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keyword">const</span> arm_compute::GEMMInfo& gemm_info = arm_compute::GEMMInfo(<span class="keyword">false</span>, <span class="comment">// is inputX reshaped</span></div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keyword">false</span>, <span class="comment">// is inputY reshaped</span></div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">false</span>); <span class="comment">// is inputY reshaped only 1st run</span></div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keyword">auto</span> gemmLayer = std::make_unique<arm_compute::NEGEMM>();</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  gemmLayer->configure(descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#acb441bb8db19bcce78d15cdd8ceb5ea0">m_TransposeX</a> ? &m_PermutedTensorX : &inputX,</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#a112b466e5d2ab9d1887178adbe3afa1c">m_TransposeY</a> ? &m_PermutedTensorY : &inputY,</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keyword">nullptr</span>,</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  &output,</div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  1.0,</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  0,</div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  gemm_info);</div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  m_GEMMLayer.reset(gemmLayer.release());</div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span> }</div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  </div>
<div class="line"><a name="l00177"></a><span class="lineno"><a class="line" href="classarmnn_1_1_neon_batch_mat_mul_workload.xhtml#ae071e8822437c78baea75c3aef3a263a"> 177</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_neon_batch_mat_mul_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">NeonBatchMatMulWorkload::Execute</a>()<span class="keyword"> const</span></div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a>(<span class="stringliteral">"NeonBatchMatMulWorkload_Execute"</span>, this-><a class="code" href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">GetGuid</a>());</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordflow">if</span> (m_PermuteLayerX)</div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  {</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  m_PermuteLayerX->run();</div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  }</div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keywordflow">if</span> (m_PermuteLayerY)</div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  {</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  m_PermuteLayerY->run();</div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  }</div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  m_GEMMLayer->run();</div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span> }</div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span> } <span class="comment">//namespace armnn</span></div>
</div><!-- fragment --></div><!-- contents -->
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<div class="ttc" id="anamespacearmnn_xhtml_abc5405fc939efb69e2d630421f0d4271"><div class="ttname"><a href="namespacearmnn.xhtml#abc5405fc939efb69e2d630421f0d4271">armnn::NeonBatchMatMulValidate</a></div><div class="ttdeci">arm_compute::Status NeonBatchMatMulValidate(const TensorInfo &inputX, const TensorInfo &inputY, const TensorInfo &output, const BatchMatMulDescriptor &descriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_batch_mat_mul_workload_8cpp_source.xhtml#l00023">NeonBatchMatMulWorkload.cpp:23</a></div></div>
<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_xhtml_acb441bb8db19bcce78d15cdd8ceb5ea0"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#acb441bb8db19bcce78d15cdd8ceb5ea0">armnn::BatchMatMulDescriptor::m_TransposeX</a></div><div class="ttdeci">bool m_TransposeX</div><div class="ttdoc">Transpose the slices of each input tensor Transpose and Adjoint can not both be set to true for the s...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01559">Descriptors.hpp:1559</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_base_workload_xhtml_aaff95a48875d8fb4a616352906660ca9"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#aaff95a48875d8fb4a616352906660ca9">armnn::BaseWorkload< BatchMatMulQueueDescriptor >::GetGuid</a></div><div class="ttdeci">arm::pipe::ProfilingGuid GetGuid() const final</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00061">Workload.hpp:61</a></div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a765d2cee4ccce5b9467e0c2b6d25b84a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a765d2cee4ccce5b9467e0c2b6d25b84a">armnn::QueueDescriptor::ValidateInputsOutputs</a></div><div class="ttdeci">void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8cpp_source.xhtml#l00475">WorkloadData.cpp:475</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00062">Types.hpp:62</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_neon_batch_mat_mul_workload_xhtml_a2eed4c19f5918cfa8efd910e6195c99c"><div class="ttname"><a href="classarmnn_1_1_neon_batch_mat_mul_workload.xhtml#a2eed4c19f5918cfa8efd910e6195c99c">armnn::NeonBatchMatMulWorkload::NeonBatchMatMulWorkload</a></div><div class="ttdeci">NeonBatchMatMulWorkload(const BatchMatMulQueueDescriptor &descriptor, const WorkloadInfo &info)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_batch_mat_mul_workload_8cpp_source.xhtml#l00102">NeonBatchMatMulWorkload.cpp:102</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_exception.xhtml">armnn::Exception</a></div><div class="ttdoc">Base class for all ArmNN exceptions so that users can filter to just those.</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00046">Exceptions.hpp:46</a></div></div>
<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_queue_descriptor.xhtml">armnn::BatchMatMulQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00743">WorkloadData.hpp:743</a></div></div>
<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml">armnn::BatchMatMulDescriptor</a></div><div class="ttdoc">A BatchMatMulDescriptor for the BatchMatMul operator.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01531">Descriptors.hpp:1531</a></div></div>
<div class="ttc" id="a_polymorphic_downcast_8hpp_xhtml"><div class="ttname"><a href="_polymorphic_downcast_8hpp.xhtml">PolymorphicDowncast.hpp</a></div></div>
<div class="ttc" id="a_neon_batch_mat_mul_workload_8hpp_xhtml"><div class="ttname"><a href="_neon_batch_mat_mul_workload_8hpp.xhtml">NeonBatchMatMulWorkload.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_base_workload_xhtml_afb8d2c8817c75de9d01a4c0e0d5c160b"><div class="ttname"><a href="classarmnn_1_1_base_workload.xhtml#afb8d2c8817c75de9d01a4c0e0d5c160b">armnn::BaseWorkload< BatchMatMulQueueDescriptor >::m_Data</a></div><div class="ttdeci">BatchMatMulQueueDescriptor m_Data</div><div class="ttdef"><b>Definition:</b> <a href="_workload_8hpp_source.xhtml#l00083">Workload.hpp:83</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors.</div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.xhtml#l00006">01_00_quick_start.dox:6</a></div></div>
<div class="ttc" id="anamespacearmnn_utils_xhtml_abeaf4f6785039866fd075f4569ba8e84"><div class="ttname"><a href="namespacearmnn_utils.xhtml#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a></div><div class="ttdeci">armnn::TensorShape Permuted(const armnn::TensorShape &srcShape, const armnn::PermutationVector &mappings)</div><div class="ttdef"><b>Definition:</b> <a href="_permute_8cpp_source.xhtml#l00098">Permute.cpp:98</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_neon_batch_mat_mul_workload_xhtml_ae071e8822437c78baea75c3aef3a263a"><div class="ttname"><a href="classarmnn_1_1_neon_batch_mat_mul_workload.xhtml#ae071e8822437c78baea75c3aef3a263a">armnn::NeonBatchMatMulWorkload::Execute</a></div><div class="ttdeci">virtual void Execute() const override</div><div class="ttdef"><b>Definition:</b> <a href="_neon_batch_mat_mul_workload_8cpp_source.xhtml#l00177">NeonBatchMatMulWorkload.cpp:177</a></div></div>
<div class="ttc" id="a_neon_workload_utils_8hpp_xhtml_a9165e41bcaf1b90f9ff91ef681e88c4f"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml#a9165e41bcaf1b90f9ff91ef681e88c4f">ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID</a></div><div class="ttdeci">#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.xhtml#l00024">NeonWorkloadUtils.hpp:24</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div><div class="ttdeci">@ NCHW</div></div>
<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_xhtml_aedca000a005e091c23191e82d7e81b1d"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#aedca000a005e091c23191e82d7e81b1d">armnn::BatchMatMulDescriptor::m_DataLayoutX</a></div><div class="ttdeci">DataLayout m_DataLayoutX</div><div class="ttdoc">Data layout of each input tensor, such as NHWC/NDHWC (leave as default for arbitrary layout)</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01568">Descriptors.hpp:1568</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#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.xhtml#l00195">Tensor.hpp:195</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_a15e2ba06d2ecd7ff6013118838e5d1be"><div class="ttname"><a href="namespacearmnn.xhtml#a15e2ba06d2ecd7ff6013118838e5d1be">armnn::GeneratePermutationVectorOnLastTwoDimensions</a></div><div class="ttdeci">armnn::PermutationVector GeneratePermutationVectorOnLastTwoDimensions(unsigned int rank)</div><div class="ttdoc">Generates a permutation vector of size rank that permutes the 2 most right dimensions.</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00344">WorkloadUtils.cpp:344</a></div></div>
<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_xhtml_a112b466e5d2ab9d1887178adbe3afa1c"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#a112b466e5d2ab9d1887178adbe3afa1c">armnn::BatchMatMulDescriptor::m_TransposeY</a></div><div class="ttdeci">bool m_TransposeY</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01560">Descriptors.hpp:1560</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="a_neon_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml">NeonWorkloadUtils.hpp</a></div></div>
<div class="ttc" id="a_permute_8hpp_xhtml"><div class="ttname"><a href="_permute_8hpp.xhtml">Permute.hpp</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_a67a0db04d321a74b7e7fcfd3f1a3f70b"><div class="ttname"><a href="namespacearmnn.xhtml#a67a0db04d321a74b7e7fcfd3f1a3f70b">armnn::Status</a></div><div class="ttdeci">Status</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00042">Types.hpp:42</a></div></div>
<div class="ttc" id="astructarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer.</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_permutation_vector_xhtml"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00295">Types.hpp:295</a></div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00066">WorkloadData.hpp:66</a></div></div>
<div class="ttc" id="a_profiling_8hpp_xhtml_a786492a3881a4c760ab1eec2149f4aba"><div class="ttname"><a href="_profiling_8hpp.xhtml#a786492a3881a4c760ab1eec2149f4aba">ARMNN_REPORT_PROFILING_WORKLOAD_DESC</a></div><div class="ttdeci">#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)</div><div class="ttdef"><b>Definition:</b> <a href="_profiling_8hpp_source.xhtml#l00227">Profiling.hpp:227</a></div></div>
<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_xhtml_aaf7828880989b4b9378d3e86aa6dc843"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#aaf7828880989b4b9378d3e86aa6dc843">armnn::BatchMatMulDescriptor::m_DataLayoutY</a></div><div class="ttdeci">DataLayout m_DataLayoutY</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01569">Descriptors.hpp:1569</a></div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00027">WorkloadData.hpp:27</a></div></div>
<div class="ttc" id="a_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_utils_8hpp.xhtml">WorkloadUtils.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_neon_base_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_base_workload.xhtml">armnn::NeonBaseWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_base_workload_8hpp_source.xhtml#l00013">NeonBaseWorkload.hpp:13</a></div></div>
<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_xhtml_ad945fc98770356dd886a68e98a52e26b"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#ad945fc98770356dd886a68e98a52e26b">armnn::BatchMatMulDescriptor::m_AdjointY</a></div><div class="ttdeci">bool m_AdjointY</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01565">Descriptors.hpp:1565</a></div></div>
<div class="ttc" id="astructarmnn_1_1_batch_mat_mul_descriptor_xhtml_a0cf8306be7d301de0f095fff9901a525"><div class="ttname"><a href="structarmnn_1_1_batch_mat_mul_descriptor.xhtml#a0cf8306be7d301de0f095fff9901a525">armnn::BatchMatMulDescriptor::m_AdjointX</a></div><div class="ttdeci">bool m_AdjointX</div><div class="ttdoc">Adjoint the slices of each input tensor Transpose and Adjoint can not both be set to true for the sam...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01564">Descriptors.hpp:1564</a></div></div>
<div class="ttc" id="astructarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00026">WorkloadData.hpp:26</a></div></div>
<div class="ttc" id="anamespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div><div class="ttdeci">@ info</div></div>
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