diff options
Diffstat (limited to '20.02/_workload_utils_8cpp_source.xhtml')
| -rw-r--r-- | 20.02/_workload_utils_8cpp_source.xhtml | 153 |
1 files changed, 153 insertions, 0 deletions
diff --git a/20.02/_workload_utils_8cpp_source.xhtml b/20.02/_workload_utils_8cpp_source.xhtml new file mode 100644 index 0000000000..231e4eeddb --- /dev/null +++ b/20.02/_workload_utils_8cpp_source.xhtml @@ -0,0 +1,153 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/backends/backendsCommon/WorkloadUtils.cpp Source File</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">20.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_workload_utils_8cpp_source.xhtml','');}); +</script> +<div id="doc-content"> +<!-- window showing the filter options --> +<div id="MSearchSelectWindow" + onmouseover="return searchBox.OnSearchSelectShow()" + onmouseout="return searchBox.OnSearchSelectHide()" + onkeydown="return searchBox.OnSearchSelectKey(event)"> +</div> + +<!-- iframe showing the search results (closed by default) --> +<div id="MSearchResultsWindow"> +<iframe src="javascript:void(0)" frameborder="0" + name="MSearchResults" id="MSearchResults"> +</iframe> +</div> + +<div class="header"> + <div class="headertitle"> +<div class="title">WorkloadUtils.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_workload_utils_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 © 2017 Arm Ltd. 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="_workload_utils_8hpp.xhtml">backendsCommon/WorkloadUtils.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="_utils_8hpp.xhtml">armnn/Utils.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="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></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> </div><div class="line"><a name="l00013"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a2a9ac8ebb69307ad4ec894ffa0523dbf"> 13</a></span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> <a class="code" href="namespacearmnn.xhtml#a2a9ac8ebb69307ad4ec894ffa0523dbf">PermuteTensor</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml">ConstCpuTensorHandle</a>* tensor,</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">PermutationVector</a>& permutationVector, <span class="keywordtype">void</span>* permuteBuffer)</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>  BOOST_ASSERT_MSG(tensor, <span class="stringliteral">"Invalid input tensor"</span>);</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  BOOST_ASSERT_MSG(permuteBuffer, <span class="stringliteral">"Invalid permute buffer"</span>);</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> tensorInfo = tensor-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>();</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="keywordflow">if</span> (permutationVector.<a class="code" href="classarmnn_1_1_permutation_vector.xhtml#a490ec6b59006d1fe1ec2ea30e69fb97c">GetSize</a>() > 0)</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  {</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  tensorInfo = <a class="code" href="namespacearmnn_utils.xhtml#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(tensorInfo, permutationVector);</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnnUtils::Permute</a>(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(), permutationVector,</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  tensor-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a3a76fc8b348e13d5a6ac1240c96ebef4">GetConstTensor</a><<span class="keywordtype">void</span>>(), permuteBuffer,</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <a class="code" href="namespacearmnn.xhtml#aa02b9e06fb20fa3c13da0427e6ee5ab2">GetDataTypeSize</a>(tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>()));</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">else</span></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>  ::memcpy(permuteBuffer, tensor-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a3a76fc8b348e13d5a6ac1240c96ebef4">GetConstTensor</a><<span class="keywordtype">void</span>>(), tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>());</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> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>(tensorInfo, permuteBuffer);</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</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"><a class="line" href="namespacearmnn.xhtml#a3170fdd696155a247ecd81d445c0e2e1"> 36</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#a3170fdd696155a247ecd81d445c0e2e1">ReshapeWeightsForAcl</a>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& weightInfo, <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="comment">// Reshape the weights in-place</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& weightShape = weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>:</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <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="l00044"></a><span class="lineno"> 44</span>  weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ 1,</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  weightShape[0],</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  weightShape[1],</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  weightShape[2] * weightShape[3] });</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ 1,</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  weightShape[0] * weightShape[1],</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  weightShape[2],</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  weightShape[3] });</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>:</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <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="l00056"></a><span class="lineno"> 56</span>  weightInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">SetShape</a>({ 1, weightShape[0] * weightShape[1], weightShape[2], weightShape[3] });</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keywordflow">break</span>;</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> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="keyword">template</span> <<span class="keyword">typename</span> DataType></div><div class="line"><a name="l00062"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a52b301fd3adce20b51c4482cb52f1a38"> 62</a></span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> <a class="code" href="namespacearmnn.xhtml#a52b301fd3adce20b51c4482cb52f1a38">ReorderWeightChannelsForAcl</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>& weightHandle, <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout, <span class="keywordtype">void</span>* permuteBuffer)</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> {</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>* weight = <span class="keyword">static_cast<</span><a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>*<span class="keyword">></span>(permuteBuffer);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>& weightShape = weightHandle.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> multiplier;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordflow">switch</span> (dataLayout)</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="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>: <span class="comment">//It actually is [ H, W, I, M ]</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  height = weightShape[0];</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  width = weightShape[1];</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  inputChannels = weightShape[2];</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  multiplier = weightShape[3];</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>: <span class="comment">//It actually is [ M, I, H, W ]</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  height = weightShape[2];</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  width = weightShape[3];</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  inputChannels = weightShape[1];</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  multiplier = weightShape[0];</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  }</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  std::vector<DataType> weightAclOrder(height*width*inputChannels*multiplier);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> destinationWeightsChannel;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> totalChannels = inputChannels * multiplier;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channelSize = height * width;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannel = 0;</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">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> originWeightsChannel = 0; originWeightsChannel < totalChannels; originWeightsChannel++)</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  {</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  inputChannel = originWeightsChannel % inputChannels;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  destinationWeightsChannel = (originWeightsChannel - inputChannel) / inputChannels + multiplier * inputChannel;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> </div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < channelSize; i++)</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>  weightAclOrder[i + destinationWeightsChannel * channelSize] =</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  weight[i + originWeightsChannel * channelSize];</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  }</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  }</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  ::memcpy(permuteBuffer, weightAclOrder.data(), weightHandle.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">GetNumBytes</a>());</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a>(weightHandle.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>(), permuteBuffer);</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> </div><div class="line"><a name="l00109"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a1e8288eac7e909fdb58b6113d816763a"> 109</a></span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a1e8288eac7e909fdb58b6113d816763a">ConvertWeightTensorInfoFromArmnnToAcl</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& weightInfo, <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> {</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="comment">// Convert the weight format from ArmNN's [ M, I, H, W ] (does NOT depend on the data layout) to either</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <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="l00113"></a><span class="lineno"> 113</span> </div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="comment">// 1. Permute the weights if necessary</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <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="l00116"></a><span class="lineno"> 116</span>  <span class="comment">// starting from the current shape of [ M, I, H, W ]</span></div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> weightPermutedInfo(weightInfo);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  {</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <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="l00121"></a><span class="lineno"> 121</span>  <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">PermutationVector</a> permutationVector{ 3, 2, 0, 1 };</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  weightPermutedInfo = <a class="code" href="namespacearmnn_utils.xhtml#abeaf4f6785039866fd075f4569ba8e84">armnnUtils::Permuted</a>(weightInfo, permutationVector);</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> </div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="comment">// 2. Reshape the weights</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <a class="code" href="namespacearmnn.xhtml#a3170fdd696155a247ecd81d445c0e2e1">ReshapeWeightsForAcl</a>(weightPermutedInfo, dataLayout);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="comment">// 3. Return the permuted weight info</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">return</span> weightPermutedInfo;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> }</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a51e8b95a429e11678ffa8b9fdc88351b"> 132</a></span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> <a class="code" href="namespacearmnn.xhtml#a51e8b95a429e11678ffa8b9fdc88351b">ConvertWeightTensorFromArmnnToAcl</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml">ConstCpuTensorHandle</a>* weightTensor,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keywordtype">void</span>* permuteBuffer)</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  BOOST_ASSERT_MSG(weightTensor, <span class="stringliteral">"Invalid input tensor"</span>);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  BOOST_ASSERT_MSG(permuteBuffer, <span class="stringliteral">"Invalid permute buffer"</span>);</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keyword">auto</span> multiplier = weightTensor-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[0];</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keyword">auto</span> inputChannels = weightTensor-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[1];</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="comment">// Convert the weight format from ArmNN's [ M, I, H, W ] (does NOT depend on the data layout) to either</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <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="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="comment">// 1. Permute the weights if necessary</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <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="l00147"></a><span class="lineno"> 147</span>  <span class="comment">// starting from the current shape of [ M, I, H, W ]</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="comment">// If no permutation is necessary, leave the permutation vector empty</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <a class="code" href="classarmnn_1_1_permutation_vector.xhtml">PermutationVector</a> permutationVector{};</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  {</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <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="l00153"></a><span class="lineno"> 153</span>  permutationVector = { 3, 2, 0, 1 };</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  }</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> weightPermuted = <a class="code" href="namespacearmnn.xhtml#a2a9ac8ebb69307ad4ec894ffa0523dbf">PermuteTensor</a>(weightTensor, permutationVector, permuteBuffer);</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="comment">// Shuffle the weights data to obtain the channel order needed used by Acl</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keywordflow">if</span> (multiplier > 1 && inputChannels > 1 && dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  {</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordflow">switch</span> (weightPermuted.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3">GetDataType</a>())</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>:</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  weightPermuted = ReorderWeightChannelsForAcl<float>(weightPermuted, dataLayout, permuteBuffer);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>:</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  weightPermuted =</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  ReorderWeightChannelsForAcl<half_float::half>(weightPermuted, dataLayout, permuteBuffer);</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">DataType::QAsymmS8</a>:</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>:</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  weightPermuted = ReorderWeightChannelsForAcl<uint8_t>(weightPermuted, dataLayout, permuteBuffer);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <a class="code" href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a34346ec9593088efe3a29c0dad92166d">DataType::QuantizedSymm8PerAxis</a>:</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="code" href="_utils_8hpp.xhtml#abbf421eb1186af0d505648ed2ea54a00">ARMNN_FALLTHROUGH</a>;</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>:</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  weightPermuted = ReorderWeightChannelsForAcl<int8_t>(weightPermuted, dataLayout, permuteBuffer);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  }</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> </div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="comment">// 2. Reshape the weights</span></div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="namespacearmnn.xhtml#a3170fdd696155a247ecd81d445c0e2e1">ReshapeWeightsForAcl</a>(weightPermuted.<a class="code" href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">GetInfo</a>(), dataLayout);</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>  <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="l00189"></a><span class="lineno"> 189</span>  <span class="keywordflow">return</span> weightPermuted;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> }</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> </div><div class="line"><a name="l00192"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#ad69ffa576a596b9eb20ab6a41420c541"> 192</a></span> int32_t <a class="code" href="namespacearmnn.xhtml#ad69ffa576a596b9eb20ab6a41420c541">ConvertMaskToACLFormat</a>(int32_t mask, int32_t numDim)</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> {</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  int32_t reversedMask = 0;</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < boost::numeric_cast<unsigned int>(numDim); ++i)</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  {</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// Check if bit set in mask for each dimension</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  int32_t bit = (mask & 1 << i) != 0;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="comment">// Increment the new mask with the bits reversed</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  reversedMask += (bit << std::max(numDim-(boost::numeric_cast<int>(i)+1), 0));</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  }</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> </div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordflow">return</span> reversedMask;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> }</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> </div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> } <span class="comment">// namespace armnn</span></div><div class="ttc" id="namespacearmnn_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#l00049">Types.hpp:49</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00088">Tensor.hpp:88</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a51e8b95a429e11678ffa8b9fdc88351b"><div class="ttname"><a href="namespacearmnn.xhtml#a51e8b95a429e11678ffa8b9fdc88351b">armnn::ConvertWeightTensorFromArmnnToAcl</a></div><div class="ttdeci">armnn::ConstTensor ConvertWeightTensorFromArmnnToAcl(const ConstCpuTensorHandle *weightTensor, DataLayout dataLayout, void *permuteBuffer)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00132">WorkloadUtils.cpp:132</a></div></div> +<div class="ttc" id="_utils_8hpp_xhtml"><div class="ttname"><a href="_utils_8hpp.xhtml">Utils.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a1e8288eac7e909fdb58b6113d816763a"><div class="ttname"><a href="namespacearmnn.xhtml#a1e8288eac7e909fdb58b6113d816763a">armnn::ConvertWeightTensorInfoFromArmnnToAcl</a></div><div class="ttdeci">TensorInfo ConvertWeightTensorInfoFromArmnnToAcl(const TensorInfo &weightInfo, DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00109">WorkloadUtils.cpp:109</a></div></div> +<div class="ttc" id="_deprecated_8hpp_xhtml_ab66a241a0ed3ee89c866e777b035d0ed"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_BEGIN</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00033">Deprecated.hpp:33</a></div></div> +<div class="ttc" id="classarmnn_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#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a34346ec9593088efe3a29c0dad92166d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a34346ec9593088efe3a29c0dad92166d">armnn::DataType::QuantizedSymm8PerAxis</a></div></div> +<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::BaseTensor::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00169">Tensor.hpp:169</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_abcbdfb544ece4c31d0b37715ad0f3be0"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#abcbdfb544ece4c31d0b37715ad0f3be0">armnn::TensorInfo::GetNumBytes</a></div><div class="ttdeci">unsigned int GetNumBytes() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00213">Tensor.cpp:213</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_cpu_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_cpu_tensor_handle.xhtml">armnn::ConstCpuTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.xhtml#l00027">CpuTensorHandle.hpp:27</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_cpu_tensor_handle_xhtml_a3a76fc8b348e13d5a6ac1240c96ebef4"><div class="ttname"><a href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a3a76fc8b348e13d5a6ac1240c96ebef4">armnn::ConstCpuTensorHandle::GetConstTensor</a></div><div class="ttdeci">const T * GetConstTensor() const</div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.xhtml#l00031">CpuTensorHandle.hpp:31</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div> +<div class="ttc" id="classarmnn_1_1_permutation_vector_xhtml_a490ec6b59006d1fe1ec2ea30e69fb97c"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.xhtml#a490ec6b59006d1fe1ec2ea30e69fb97c">armnn::PermutationVector::GetSize</a></div><div class="ttdeci">SizeType GetSize() const</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00202">Types.hpp:202</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a2a9ac8ebb69307ad4ec894ffa0523dbf"><div class="ttname"><a href="namespacearmnn.xhtml#a2a9ac8ebb69307ad4ec894ffa0523dbf">armnn::PermuteTensor</a></div><div class="ttdeci">armnn::ConstTensor PermuteTensor(const ConstCpuTensorHandle *tensor, const PermutationVector &permutationVector, void *permuteBuffer)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00013">WorkloadUtils.cpp:13</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a52b301fd3adce20b51c4482cb52f1a38"><div class="ttname"><a href="namespacearmnn.xhtml#a52b301fd3adce20b51c4482cb52f1a38">armnn::ReorderWeightChannelsForAcl</a></div><div class="ttdeci">ConstTensor ReorderWeightChannelsForAcl(const ConstTensor &weightHandle, DataLayout dataLayout, void *permuteBuffer)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00062">WorkloadUtils.cpp:62</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_abe8889e8150beef5fd204b2d87b49298"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#abe8889e8150beef5fd204b2d87b49298">armnn::TensorInfo::SetShape</a></div><div class="ttdeci">void SetShape(const TensorShape &newShape)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00090">Tensor.hpp:90</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00032">Types.hpp:32</a></div></div> +<div class="ttc" id="_deprecated_8hpp_xhtml_ad762b11b48e5c1d1c1743f529485728a"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_END</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00034">Deprecated.hpp:34</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#aea909c7327109228ef618d459015def3">armnn::TensorInfo::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00095">Tensor.hpp:95</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4afa662c6eb71caef475b2b981ce8eccd7">armnn::LayerType::Permute</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00199">Tensor.hpp:199</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div> +<div class="ttc" id="_utils_8hpp_xhtml_abbf421eb1186af0d505648ed2ea54a00"><div class="ttname"><a href="_utils_8hpp.xhtml#abbf421eb1186af0d505648ed2ea54a00">ARMNN_FALLTHROUGH</a></div><div class="ttdeci">#define ARMNN_FALLTHROUGH</div><div class="ttdef"><b>Definition:</b> <a href="_utils_8hpp_source.xhtml#l00035">Utils.hpp:35</a></div></div> +<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_a8aeddebdcf02e1832b22203c08a6b678"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#a8aeddebdcf02e1832b22203c08a6b678">armnn::BaseTensor::GetInfo</a></div><div class="ttdeci">const TensorInfo & GetInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00167">Tensor.hpp:167</a></div></div> +<div class="ttc" id="classarmnn_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#l00173">Types.hpp:173</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad69ffa576a596b9eb20ab6a41420c541"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00192">WorkloadUtils.cpp:192</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div></div> +<div class="ttc" id="classarmnn_1_1_base_tensor_xhtml_aea909c7327109228ef618d459015def3"><div class="ttname"><a href="classarmnn_1_1_base_tensor.xhtml#aea909c7327109228ef618d459015def3">armnn::BaseTensor::GetDataType</a></div><div class="ttdeci">DataType GetDataType() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00172">Tensor.hpp:172</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a3170fdd696155a247ecd81d445c0e2e1"><div class="ttname"><a href="namespacearmnn.xhtml#a3170fdd696155a247ecd81d445c0e2e1">armnn::ReshapeWeightsForAcl</a></div><div class="ttdeci">void ReshapeWeightsForAcl(TensorInfo &weightInfo, DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_utils_8cpp_source.xhtml#l00036">WorkloadUtils.cpp:36</a></div></div> +<div class="ttc" id="namespacearmnn_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="classarmnn_1_1_const_cpu_tensor_handle_xhtml_a66e8f43a5b42b500871ed96e15419567"><div class="ttname"><a href="classarmnn_1_1_const_cpu_tensor_handle.xhtml#a66e8f43a5b42b500871ed96e15419567">armnn::ConstCpuTensorHandle::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const</div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.xhtml#l00037">CpuTensorHandle.hpp:37</a></div></div> +<div class="ttc" id="_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_utils_8hpp.xhtml">WorkloadUtils.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa02b9e06fb20fa3c13da0427e6ee5ab2"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00115">TypesUtils.hpp:115</a></div></div> +</div><!-- fragment --></div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.xhtml">backendsCommon</a></li><li class="navelem"><a class="el" href="_workload_utils_8cpp.xhtml">WorkloadUtils.cpp</a></li> + <li class="footer">Generated on Fri Mar 13 2020 16:09:11 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + </ul> +</div> +</body> +</html> |