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<div class="title">WorkloadUtils.cpp</div> </div>
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<a href="_workload_utils_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 © 2017-2023 Arm Ltd. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160; </div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_workload_utils_8hpp.html">backendsCommon/WorkloadUtils.hpp</a>&gt;</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160; </div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_utils_8hpp.html">armnn/Utils.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="_numeric_cast_8hpp.html">armnn/utility/NumericCast.hpp</a>&gt;</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_data_layout_indexed_8hpp.html">armnnUtils/DataLayoutIndexed.hpp</a>&gt;</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="preprocessor">#include &lt;fmt/format.h&gt;</span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="preprocessor">#include &lt;numeric&gt;</span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160; </div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;{</div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160; </div>
<div class="line"><a name="l00018"></a><span class="lineno"><a class="line" href="namespacearmnn.html#aafe6180ef80d9f334f3a3ba9cc0db35d"> 18</a></span>&#160;<a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> <a class="code" href="namespacearmnn.html#aafe6180ef80d9f334f3a3ba9cc0db35d">PermuteTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor_handle.html">ConstTensorHandle</a>* tensor,</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a>&amp; permutationVector, <span class="keywordtype">void</span>* permuteBuffer)</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;{</div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; <span class="keywordflow">if</span> (tensor == <span class="keyword">nullptr</span>)</div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; {</div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">&quot;WorkloadUtils: PermuteTensor: Null input tensor pointer&quot;</span>);</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; }</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; <span class="keywordflow">if</span> (permuteBuffer == <span class="keyword">nullptr</span>)</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="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">&quot;WorkloadUtils: PermuteTensor: Null permute buffer pointer&quot;</span>);</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; }</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; </div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> tensorInfo = tensor-&gt;<a class="code" href="classarmnn_1_1_const_tensor_handle.html#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>();</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="keywordflow">if</span> (permutationVector.<a class="code" href="classarmnn_1_1_permutation_vector.html#a490ec6b59006d1fe1ec2ea30e69fb97c">GetSize</a>() &gt; 0)</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; {</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; tensorInfo = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(tensorInfo, permutationVector);</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; <a class="code" href="namespacearmnn_utils.html#af3c74017185773dd61d8ca6662d65d43">armnnUtils::Permute</a>(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), permutationVector,</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; tensor-&gt;<a class="code" href="classarmnn_1_1_const_tensor_handle.html#a3a76fc8b348e13d5a6ac1240c96ebef4">GetConstTensor</a>&lt;<span class="keywordtype">void</span>&gt;(), permuteBuffer,</div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <a class="code" href="namespacearmnn.html#aa02b9e06fb20fa3c13da0427e6ee5ab2">GetDataTypeSize</a>(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>()));</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; }</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; {</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; ::memcpy(permuteBuffer, tensor-&gt;<a class="code" href="classarmnn_1_1_const_tensor_handle.html#a3a76fc8b348e13d5a6ac1240c96ebef4">GetConstTensor</a>&lt;<span class="keywordtype">void</span>&gt;(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>());</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; }</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8ffca1e21bdfa7f945617acd606aac91">SetConstant</a>(<span class="keyword">true</span>);</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a>(tensorInfo, permuteBuffer);</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"> 46</span>&#160; </div>
<div class="line"><a name="l00047"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a3170fdd696155a247ecd81d445c0e2e1"> 47</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#a3170fdd696155a247ecd81d445c0e2e1">ReshapeWeightsForAcl</a>(<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; weightInfo, <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</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="comment">// Reshape the weights in-place</span></div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; weightShape = weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="keywordflow">switch</span> (dataLayout)</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; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>:</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="comment">// The data layout is NHWC, reshape from [ H, W, I, M ] to [ 1, H, W, I * M ]</span></div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ 1,</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; weightShape[0],</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; weightShape[1],</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; weightShape[2] * weightShape[3] });</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ 1,</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; weightShape[0] * weightShape[1],</div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; weightShape[2],</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; weightShape[3] });</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>:</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="comment">// The data layout is NCHW, reshape from [ M, I, H, W ] to [ 1, I * M, H, W, ]</span></div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ 1, weightShape[0] * weightShape[1], weightShape[2], weightShape[3] });</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; }</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; </div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> DataType&gt;</div>
<div class="line"><a name="l00073"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a52b301fd3adce20b51c4482cb52f1a38"> 73</a></span>&#160;<a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a> <a class="code" href="namespacearmnn.html#a52b301fd3adce20b51c4482cb52f1a38">ReorderWeightChannelsForAcl</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a>&amp; weightHandle, <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout, <span class="keywordtype">void</span>* permuteBuffer)</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160;{</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>* weight = <span class="keyword">static_cast&lt;</span><a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>*<span class="keyword">&gt;</span>(permuteBuffer);</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; weightShape = weightHandle.<a class="code" href="classarmnn_1_1_base_tensor.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> multiplier;</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height;</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width;</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels;</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <span class="keywordflow">switch</span> (dataLayout)</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; {</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>: <span class="comment">//It actually is [ H, W, I, M ]</span></div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; height = weightShape[0];</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; width = weightShape[1];</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; inputChannels = weightShape[2];</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; multiplier = weightShape[3];</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>: <span class="comment">//It actually is [ M, I, H, W ]</span></div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; height = weightShape[2];</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; width = weightShape[3];</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; inputChannels = weightShape[1];</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; multiplier = weightShape[0];</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <span class="keywordflow">break</span>;</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"> 97</span>&#160; </div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; std::vector&lt;DataType&gt; weightAclOrder(height*width*inputChannels*multiplier);</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> destinationWeightsChannel;</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> totalChannels = inputChannels * multiplier;</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channelSize = height * width;</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannel = 0;</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; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> originWeightsChannel = 0; originWeightsChannel &lt; totalChannels; originWeightsChannel++)</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; {</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; inputChannel = originWeightsChannel % inputChannels;</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; destinationWeightsChannel = (originWeightsChannel - inputChannel) / inputChannels + multiplier * inputChannel;</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; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; channelSize; i++)</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; weightAclOrder[i + destinationWeightsChannel * channelSize] =</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; weight[i + originWeightsChannel * channelSize];</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; }</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; }</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; ::memcpy(permuteBuffer, weightAclOrder.data(), weightHandle.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>());</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a>(weightHandle.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>(), permuteBuffer);</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160;}</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; </div>
<div class="line"><a name="l00121"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a1e8288eac7e909fdb58b6113d816763a"> 121</a></span>&#160;<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> <a class="code" href="namespacearmnn.html#a1e8288eac7e909fdb58b6113d816763a">ConvertWeightTensorInfoFromArmnnToAcl</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; weightInfo, <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160;{</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <span class="comment">// Convert the weight format from ArmNN&#39;s [ M, I, H, W ] (does NOT depend on the data layout) to either</span></div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="comment">// [ 1, H, W, I * M ] (if NHWC) or [ 1, I * M, H, W ] (if NCHW), as required by the compute library</span></div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; </div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="comment">// 1. Permute the weights if necessary</span></div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="comment">// If the data layout is NCHW no permutation is necessary, as a reshape to [ 1, I * M, H, W ] can be better done</span></div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <span class="comment">// starting from the current shape of [ M, I, H, W ]</span></div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> weightPermutedInfo(weightInfo);</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</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; <span class="comment">// The data layout is NHWC, then permute the weights from [ M, I, H, W ] to [ H, W, I, M ]</span></div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a> permutationVector{ 3, 2, 0, 1 };</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; weightPermutedInfo = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(weightInfo, permutationVector);</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; }</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; </div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; <span class="comment">// 2. Reshape the weights</span></div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <a class="code" href="namespacearmnn.html#a3170fdd696155a247ecd81d445c0e2e1">ReshapeWeightsForAcl</a>(weightPermutedInfo, dataLayout);</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; </div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <span class="comment">// 3. Return the permuted weight info</span></div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; <span class="keywordflow">return</span> weightPermutedInfo;</div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160;}</div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; </div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; </div>
<div class="line"><a name="l00145"></a><span class="lineno"><a class="line" href="namespacearmnn.html#af35f79341ec6c10a8bd4c8caf0585ffb"> 145</a></span>&#160;std::tuple&lt;ConstTensor, unsigned int&gt; <a class="code" href="namespacearmnn.html#af35f79341ec6c10a8bd4c8caf0585ffb">Convert1HWOTensorToAcl</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor_handle.html">ConstTensorHandle</a>* weightTensor,</div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; inputInfo,</div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout,</div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; <span class="keywordtype">void</span>* permuteBuffer)</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; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> weightsInfo = weightTensor-&gt;<a class="code" href="classarmnn_1_1_const_tensor_handle.html#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>();</div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthMultiplier = 1;</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a> permutationVector{};</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; {</div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; <span class="comment">// No permutation required. Data layouts are the same.</span></div>
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; </div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; depthMultiplier = weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[3] / inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[3];</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="keywordflow">else</span> <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>)</div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; {</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <span class="comment">// [ 1, H, W, I*M] --&gt; [ 1, I * M, H, W ]</span></div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; depthMultiplier = weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[3] / inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[1];</div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; permutationVector = { 0, 2, 3, 1 };</div>
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; }</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; {</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(fmt::format(<span class="stringliteral">&quot;Unknown data layout for tensor conversion: {}&quot;</span>,</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; <a class="code" href="namespacearmnn.html#aeef70b7611ae71e97ab55c75ef72b210">GetDataLayoutName</a>(dataLayout)));</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; }</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; </div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; <a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a> weightsPermuted = <a class="code" href="namespacearmnn.html#aafe6180ef80d9f334f3a3ba9cc0db35d">PermuteTensor</a>(weightTensor, permutationVector, permuteBuffer);</div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; </div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; <span class="keywordflow">return</span> std::make_tuple(weightsPermuted, depthMultiplier);</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; </div>
<div class="line"><a name="l00176"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ac4aa9e41515b354234645f115c49de32"> 176</a></span>&#160;std::tuple&lt;TensorInfo, unsigned int&gt; <a class="code" href="namespacearmnn.html#ac4aa9e41515b354234645f115c49de32">Convert1HWOTensorInfoToAcl</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; weightInfo,</div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; inputInfo,</div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160;{</div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> aclDepthMultiplier = 1;</div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> weightsPermuted;</div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</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">// No permutation required. Input and weights data layouts are the same.</span></div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; aclDepthMultiplier = weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[3] / inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[3];</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; weightsPermuted = weightInfo;</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"> 188</span>&#160; </div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>)</div>
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160; {</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; <span class="comment">// Weights permutation required. Weights [N,H,W,C] and input [N,C,H,W] data layouts are different.</span></div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; <span class="comment">// [ 1, H, W, I*M] --&gt; [ 1, I * M, H, W ]</span></div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160; aclDepthMultiplier = weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[3] / inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[1];</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a> permutationVector{ 0, 2, 3, 1 };</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; weightsPermuted = <a class="code" href="namespacearmnn_utils.html#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(weightInfo, permutationVector);</div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; }</div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; {</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(fmt::format(<span class="stringliteral">&quot;Unknown data layout for tensor info conversion: {}&quot;</span>,</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; <a class="code" href="namespacearmnn.html#aeef70b7611ae71e97ab55c75ef72b210">GetDataLayoutName</a>(dataLayout)));</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; }</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; <span class="keywordflow">return</span> std::make_tuple(weightsPermuted, aclDepthMultiplier);</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160;}</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; </div>
<div class="line"><a name="l00207"></a><span class="lineno"><a class="line" href="namespacearmnn.html#aa22a82f5240a0eb0d61135345080aa2d"> 207</a></span>&#160;std::tuple&lt;ConstTensor, unsigned int&gt; <a class="code" href="namespacearmnn.html#aa22a82f5240a0eb0d61135345080aa2d">Convert1HWOtoMIHW</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor_handle.html">ConstTensorHandle</a>* weightTensor,</div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; inputInfo,</div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a>&amp; dataLayout,</div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; <span class="keywordtype">void</span>* permuteBuffer)</div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160;{</div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> weightsInfo = weightTensor-&gt;<a class="code" href="classarmnn_1_1_const_tensor_handle.html#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>();</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> (weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#ab85cd8cc10c96a7c99c14042c251fc48">HasPerAxisQuantization</a>())</div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; {</div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;Can&#39;t convert tensor from [1,H,W,Cout] to [M,Cin,H,W] when per channel &quot;</span></div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; <span class="stringliteral">&quot;quantization is applied.&quot;</span>);</div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; }</div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; </div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; <span class="comment">// Reshape weights [ 1, H, W, I*M ] --&gt; [ H, W, I, M ]</span></div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; <span class="keyword">auto</span> weightsShape = weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; <span class="keyword">auto</span> channelIndex = <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a>(dataLayout).<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>();</div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthMultiplier = weightsShape[3] / inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[channelIndex];</div>
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; weightsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ weightsShape[1],</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; weightsShape[2],</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[channelIndex],</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; depthMultiplier});</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; </div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; <span class="comment">// Permute [ H, W, I, M ] --&gt; [ M, I, H, W ]</span></div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a> permutationVector = { 2, 3, 1, 0 };</div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; <a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a> weightsPermuted = <a class="code" href="namespacearmnn.html#aafe6180ef80d9f334f3a3ba9cc0db35d">PermuteTensor</a>(weightTensor, permutationVector, permuteBuffer);</div>
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160; </div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; <span class="keywordflow">return</span> std::make_tuple(weightsPermuted, depthMultiplier);</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160;}</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; </div>
<div class="line"><a name="l00236"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a8ca9f249dc67c111b8234b2c78d672cd"> 236</a></span>&#160;<a class="code" href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a> <a class="code" href="namespacearmnn.html#a8ca9f249dc67c111b8234b2c78d672cd">ConvertWeightTensorFromArmnnToAcl</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor_handle.html">ConstTensorHandle</a>* weightTensor,</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160; <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout,</div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; <span class="keywordtype">void</span>* permuteBuffer)</div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160;{</div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; <span class="keywordflow">if</span> (weightTensor == <span class="keyword">nullptr</span>)</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">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">&quot;WorkloadUtils: PermuteTensor: Null input tensor pointer&quot;</span>);</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; <span class="keywordflow">if</span> (permuteBuffer == <span class="keyword">nullptr</span>)</div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; {</div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a>(<span class="stringliteral">&quot;WorkloadUtils: PermuteTensor: Null permute buffer pointer&quot;</span>);</div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; }</div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160; </div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160; <span class="keyword">auto</span> multiplier = weightTensor-&gt;<a class="code" href="classarmnn_1_1_const_tensor_handle.html#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[0];</div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; <span class="keyword">auto</span> inputChannels = weightTensor-&gt;<a class="code" href="classarmnn_1_1_const_tensor_handle.html#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[1];</div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; </div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; <span class="comment">// Convert the weight format from ArmNN&#39;s [ M, I, H, W ] (does NOT depend on the data layout) to either</span></div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; <span class="comment">// [ 1, H, W, I * M ] (if NHWC) or [ 1, I * M, H, W ] (if NCHW), as required by the compute library</span></div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; </div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; <span class="comment">// 1. Permute the weights if necessary</span></div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; <span class="comment">// If the data layout is NCHW no permutation is necessary, as a reshape to [ 1, I * M, H, W ] can be better done</span></div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; <span class="comment">// starting from the current shape of [ M, I, H, W ]</span></div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; <span class="comment">// If no permutation is necessary, leave the permutation vector empty</span></div>
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; <a class="code" href="classarmnn_1_1_permutation_vector.html">PermutationVector</a> permutationVector{};</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; {</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; <span class="comment">// The data layout is NHWC, then permute the weights from [ M, I, H, W ] to [ H, W, I, M ]</span></div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; permutationVector = { 3, 2, 0, 1 };</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; }</div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; <a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a> weightPermuted = <a class="code" href="namespacearmnn.html#aafe6180ef80d9f334f3a3ba9cc0db35d">PermuteTensor</a>(weightTensor, permutationVector, permuteBuffer);</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; </div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; <span class="comment">// Shuffle the weights data to obtain the channel order needed used by Acl</span></div>
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; <span class="keywordflow">if</span> (multiplier &gt; 1 &amp;&amp; inputChannels &gt; 1 &amp;&amp; dataLayout == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; {</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; <span class="keywordflow">switch</span> (weightPermuted.<a class="code" href="classarmnn_1_1_base_tensor.html#aea909c7327109228ef618d459015def3">GetDataType</a>())</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; {</div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>:</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; weightPermuted = ReorderWeightChannelsForAcl&lt;float&gt;(weightPermuted, dataLayout, permuteBuffer);</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>:</div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; weightPermuted =</div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160; ReorderWeightChannelsForAcl&lt;half_float::half&gt;(weightPermuted, dataLayout, permuteBuffer);</div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">DataType::QAsymmS8</a>:</div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>:</div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; weightPermuted = ReorderWeightChannelsForAcl&lt;uint8_t&gt;(weightPermuted, dataLayout, permuteBuffer);</div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>:</div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; weightPermuted = ReorderWeightChannelsForAcl&lt;int8_t&gt;(weightPermuted, dataLayout, permuteBuffer);</div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; }</div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; }</div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; </div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; <span class="comment">// 2. Reshape the weights</span></div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; <a class="code" href="namespacearmnn.html#a3170fdd696155a247ecd81d445c0e2e1">ReshapeWeightsForAcl</a>(weightPermuted.<a class="code" href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>(), dataLayout);</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">// 3. Return both the tensor and the allocated storage to ensure that the data stays alive</span></div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; <span class="keywordflow">return</span> weightPermuted;</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; </div>
<div class="line"><a name="l00298"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ad69ffa576a596b9eb20ab6a41420c541"> 298</a></span>&#160;int32_t <a class="code" href="namespacearmnn.html#ad69ffa576a596b9eb20ab6a41420c541">ConvertMaskToACLFormat</a>(int32_t mask, int32_t numDim)</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; int32_t reversedMask = 0;</div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; armnn::numeric_cast&lt;unsigned int&gt;(numDim); ++i)</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">// Check if bit set in mask for each dimension</span></div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; int32_t bit = (mask &amp; 1 &lt;&lt; i) != 0;</div>
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; <span class="comment">// Increment the new mask with the bits reversed</span></div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; reversedMask += (bit &lt;&lt; std::max(numDim-(armnn::numeric_cast&lt;int&gt;(i)+1), 0));</div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; }</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; </div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; <span class="keywordflow">return</span> reversedMask;</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"><a class="line" href="namespacearmnn.html#ac40d3e4035af5fbe68d9e126a8d6367c"> 312</a></span>&#160;std::map&lt;std::string, unsigned int&gt; <a class="code" href="namespacearmnn.html#ac40d3e4035af5fbe68d9e126a8d6367c">CalculateGatherNdKeyIndices</a>(<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo0, <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo1)</div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160;{</div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160; std::vector&lt;unsigned int&gt; paramsShape;</div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; inputInfo0.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; {</div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; paramsShape.push_back(inputInfo0.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[i]);</div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160; }</div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160; </div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; std::vector&lt;unsigned int&gt; indicesShape;</div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; inputInfo1.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; {</div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; indicesShape.push_back(inputInfo1.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[i]);</div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; }</div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160; </div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160; std::map&lt;std::string, unsigned int&gt; keyIndices;</div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; </div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160; <span class="comment">// N: number of batches</span></div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160; keyIndices[<span class="stringliteral">&quot;N&quot;</span>] = 1;</div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160; </div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160; <span class="comment">// ND: number of dimensions that are sliced from params</span></div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; keyIndices[<span class="stringliteral">&quot;ND&quot;</span>] = indicesShape.back();</div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160; </div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160; <span class="comment">// W: number of indices in each batch (all but the last dimension)</span></div>
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; keyIndices[<span class="stringliteral">&quot;W&quot;</span>] =</div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160; <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(std::accumulate(std::begin(indicesShape),</div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; std::end(indicesShape) - 1,</div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; 1,</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; std::multiplies&lt;&gt;() ));</div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; <span class="comment">// K: range of each index</span></div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; keyIndices[<span class="stringliteral">&quot;K&quot;</span>] =</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(std::accumulate(std::begin(paramsShape),</div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; std::begin(paramsShape) + <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(keyIndices[<span class="stringliteral">&quot;ND&quot;</span>]),</div>
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160; 1,</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160; std::multiplies&lt;&gt;() ));</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160; <span class="comment">// C: number of channels for each index</span></div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160; keyIndices[<span class="stringliteral">&quot;C&quot;</span>] =</div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>&#160; <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(std::accumulate(std::begin(paramsShape) + <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span>(keyIndices[<span class="stringliteral">&quot;ND&quot;</span>]),</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160; std::end(paramsShape),</div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160; 1,</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>&#160; std::multiplies&lt;&gt;() ));</div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>&#160; </div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>&#160; <span class="keywordflow">return</span> keyIndices;</div>
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>&#160;}</div>
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>&#160; </div>
<div class="line"><a name="l00356"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a15e2ba06d2ecd7ff6013118838e5d1be"> 356</a></span>&#160;<a class="code" href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a> <a class="code" href="namespacearmnn.html#a15e2ba06d2ecd7ff6013118838e5d1be">GeneratePermutationVectorOnLastTwoDimensions</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> rank)</div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>&#160;{</div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>&#160; <a class="code" href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a> permutationVector{};</div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>&#160; <span class="keywordflow">switch</span> (rank)</div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>&#160; {</div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>&#160; <span class="keywordflow">case</span> 2:</div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>&#160; permutationVector = {1U, 0U};</div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>&#160; <span class="keywordflow">case</span> 3:</div>
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>&#160; permutationVector = {0U, 2U, 1U};</div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>&#160; <span class="keywordflow">case</span> 4:</div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>&#160; permutationVector = {0U, 1U, 3U, 2U};</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>&#160; <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.html">Exception</a>(<span class="stringliteral">&quot;Invalid number of dimensions.&quot;</span>);</div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>&#160; }</div>
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>&#160; <span class="keywordflow">return</span> permutationVector;</div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>&#160;}</div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>&#160; </div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>&#160;} <span class="comment">// namespace armnn</span></div>
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</div><!-- doc-content -->
<div class="ttc" id="anamespacearmnn_html_ac4aa9e41515b354234645f115c49de32"><div class="ttname"><a href="namespacearmnn.html#ac4aa9e41515b354234645f115c49de32">armnn::Convert1HWOTensorInfoToAcl</a></div><div class="ttdeci">std::tuple&lt; TensorInfo, unsigned int &gt; Convert1HWOTensorInfoToAcl(const TensorInfo &amp;weightInfo, const TensorInfo &amp;inputInfo, const DataLayout dataLayout)</div><div class="ttdoc">Weights for depthwise have a datalayout of [1,H,W,O] = [1,H,W,I*M] This function coverts a TensorInfo...</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.html#l00176">WorkloadUtils.cpp:176</a></div></div>
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<div class="ttc" id="anamespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00062">Types.hpp:62</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>
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<div class="ttc" id="aclassarmnn_1_1_const_tensor_handle_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor_handle.html">armnn::ConstTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_8hpp_source.html#l00024">TensorHandle.hpp:24</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="anamespacearmnn_html_aafe6180ef80d9f334f3a3ba9cc0db35d"><div class="ttname"><a href="namespacearmnn.html#aafe6180ef80d9f334f3a3ba9cc0db35d">armnn::PermuteTensor</a></div><div class="ttdeci">armnn::ConstTensor PermuteTensor(const ConstTensorHandle *tensor, const PermutationVector &amp;permutationVector, void *permuteBuffer)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.html#l00018">WorkloadUtils.cpp:18</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_utils_1_1_data_layout_indexed_html"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a></div><div class="ttdoc">Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout.</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00017">DataLayoutIndexed.hpp:17</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div><div class="ttdeci">@ Float32</div></div>
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<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div><div class="ttdeci">@ QAsymmU8</div></div>
<div class="ttc" id="aclassarmnn_1_1_const_tensor_handle_html_a66e8f43a5b42b500871ed96e15419567"><div class="ttname"><a href="classarmnn_1_1_const_tensor_handle.html#a66e8f43a5b42b500871ed96e15419567">armnn::ConstTensorHandle::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_8hpp_source.html#l00040">TensorHandle.hpp:40</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div><div class="ttdeci">@ QSymmS8</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="aclassarmnn_1_1_tensor_info_html_ab85cd8cc10c96a7c99c14042c251fc48"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#ab85cd8cc10c96a7c99c14042c251fc48">armnn::TensorInfo::HasPerAxisQuantization</a></div><div class="ttdeci">bool HasPerAxisQuantization() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00446">Tensor.cpp:446</a></div></div>
<div class="ttc" id="a_numeric_cast_8hpp_html"><div class="ttname"><a href="_numeric_cast_8hpp.html">NumericCast.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_base_tensor_html_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_base_tensor.html#aea909c7327109228ef618d459015def3">armnn::BaseTensor::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00302">Tensor.hpp:302</a></div></div>
<div class="ttc" id="anamespacearmnn_html_aa22a82f5240a0eb0d61135345080aa2d"><div class="ttname"><a href="namespacearmnn.html#aa22a82f5240a0eb0d61135345080aa2d">armnn::Convert1HWOtoMIHW</a></div><div class="ttdeci">std::tuple&lt; ConstTensor, unsigned int &gt; Convert1HWOtoMIHW(const ConstTensorHandle *weightTensor, const TensorInfo &amp;inputInfo, const DataLayout &amp;dataLayout, void *permuteBuffer)</div><div class="ttdoc">Converts a (weights) tensor from [1, H, W, I*M] = [1, H, W, O] to [M, I, H, W].</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.html#l00207">WorkloadUtils.cpp:207</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_const_tensor_handle_html_a3a76fc8b348e13d5a6ac1240c96ebef4"><div class="ttname"><a href="classarmnn_1_1_const_tensor_handle.html#a3a76fc8b348e13d5a6ac1240c96ebef4">armnn::ConstTensorHandle::GetConstTensor</a></div><div class="ttdeci">const T * GetConstTensor() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_handle_8hpp_source.html#l00028">TensorHandle.hpp:28</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_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div><div class="ttdeci">@ Float16</div></div>
<div class="ttc" id="anamespacearmnn_html_a8ca9f249dc67c111b8234b2c78d672cd"><div class="ttname"><a href="namespacearmnn.html#a8ca9f249dc67c111b8234b2c78d672cd">armnn::ConvertWeightTensorFromArmnnToAcl</a></div><div class="ttdeci">armnn::ConstTensor ConvertWeightTensorFromArmnnToAcl(const ConstTensorHandle *weightTensor, DataLayout dataLayout, void *permuteBuffer)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.html#l00236">WorkloadUtils.cpp:236</a></div></div>
<div class="ttc" id="a_utils_8hpp_html"><div class="ttname"><a href="_utils_8hpp.html">Utils.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#l00312">WorkloadUtils.cpp:312</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00048">Types.hpp:48</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_invalid_argument_exception_html"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00080">Exceptions.hpp:80</a></div></div>
<div class="ttc" id="anamespacearmnn_html_aa02b9e06fb20fa3c13da0427e6ee5ab2"><div class="ttname"><a href="namespacearmnn.html#aa02b9e06fb20fa3c13da0427e6ee5ab2">armnn::GetDataTypeSize</a></div><div class="ttdeci">constexpr unsigned int GetDataTypeSize(DataType dataType)</div><div class="ttdef"><b>Definition:</b> <a href="_types_utils_8hpp_source.html#l00182">TypesUtils.hpp:182</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_base_tensor_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_base_tensor.html#a8b5d0f8a24e9d9238f412260a552acf8">armnn::BaseTensor::GetShape</a></div><div class="ttdeci">const TensorShape &amp; GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00299">Tensor.hpp:299</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_permutation_vector_html"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.html">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00314">Types.hpp:314</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a52b301fd3adce20b51c4482cb52f1a38"><div class="ttname"><a href="namespacearmnn.html#a52b301fd3adce20b51c4482cb52f1a38">armnn::ReorderWeightChannelsForAcl</a></div><div class="ttdeci">ConstTensor ReorderWeightChannelsForAcl(const ConstTensor &amp;weightHandle, DataLayout dataLayout, void *permuteBuffer)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.html#l00073">WorkloadUtils.cpp:73</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_exception_html"><div class="ttname"><a href="classarmnn_1_1_exception.html">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.html#l00046">Exceptions.hpp:46</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_base_tensor_html_a8aeddebdcf02e1832b22203c08a6b678"><div class="ttname"><a href="classarmnn_1_1_base_tensor.html#a8aeddebdcf02e1832b22203c08a6b678">armnn::BaseTensor::GetInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00297">Tensor.hpp:297</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00200">Tensor.hpp:200</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div><div class="ttdeci">@ QAsymmS8</div></div>
<div class="ttc" id="anamespacearmnn_html_a3170fdd696155a247ecd81d445c0e2e1"><div class="ttname"><a href="namespacearmnn.html#a3170fdd696155a247ecd81d445c0e2e1">armnn::ReshapeWeightsForAcl</a></div><div class="ttdeci">void ReshapeWeightsForAcl(TensorInfo &amp;weightInfo, DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.html#l00047">WorkloadUtils.cpp:47</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_permutation_vector_html_a490ec6b59006d1fe1ec2ea30e69fb97c"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.html#a490ec6b59006d1fe1ec2ea30e69fb97c">armnn::PermutationVector::GetSize</a></div><div class="ttdeci">SizeType GetSize() const</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00357">Types.hpp:357</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="anamespacearmnn_html_a15e2ba06d2ecd7ff6013118838e5d1be"><div class="ttname"><a href="namespacearmnn.html#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.html#l00356">WorkloadUtils.cpp:356</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad69ffa576a596b9eb20ab6a41420c541"><div class="ttname"><a href="namespacearmnn.html#ad69ffa576a596b9eb20ab6a41420c541">armnn::ConvertMaskToACLFormat</a></div><div class="ttdeci">int32_t ConvertMaskToACLFormat(int32_t mask, int32_t numDim)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.html#l00298">WorkloadUtils.cpp:298</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a1e8288eac7e909fdb58b6113d816763a"><div class="ttname"><a href="namespacearmnn.html#a1e8288eac7e909fdb58b6113d816763a">armnn::ConvertWeightTensorInfoFromArmnnToAcl</a></div><div class="ttdeci">TensorInfo ConvertWeightTensorInfoFromArmnnToAcl(const TensorInfo &amp;weightInfo, DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.html#l00121">WorkloadUtils.cpp:121</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="aclassarmnn_utils_1_1_data_layout_indexed_html_a861b2621ee46e4b63379988b360b8cd9"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">armnnUtils::DataLayoutIndexed::GetChannelsIndex</a></div><div class="ttdeci">unsigned int GetChannelsIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00023">DataLayoutIndexed.hpp:23</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00329">Tensor.hpp:329</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8ffca1e21bdfa7f945617acd606aac91"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8ffca1e21bdfa7f945617acd606aac91">armnn::TensorInfo::SetConstant</a></div><div class="ttdeci">void SetConstant(const bool IsConstant=true)</div><div class="ttdoc">Marks the data corresponding to this tensor info as constant.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00514">Tensor.cpp:514</a></div></div>
<div class="ttc" id="a_data_layout_indexed_8hpp_html"><div class="ttname"><a href="_data_layout_indexed_8hpp.html">DataLayoutIndexed.hpp</a></div></div>
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