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diff --git a/20.02/_splitter_test_impl_8cpp_source.xhtml b/20.02/_splitter_test_impl_8cpp_source.xhtml new file mode 100644 index 0000000000..8576ff5e53 --- /dev/null +++ b/20.02/_splitter_test_impl_8cpp_source.xhtml @@ -0,0 +1,144 @@ +<!-- 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/test/layerTests/SplitterTestImpl.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('_splitter_test_impl_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">SplitterTestImpl.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_splitter_test_impl_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="_splitter_test_impl_8hpp.xhtml">SplitterTestImpl.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="_quantize_helper_8hpp.xhtml">QuantizeHelper.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_tensor_copy_utils_8hpp.xhtml">backendsCommon/test/TensorCopyUtils.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_workload_test_utils_8hpp.xhtml">backendsCommon/test/WorkloadTestUtils.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_tensor_helpers_8hpp.xhtml">test/TensorHelpers.hpp</a>></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">namespace</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> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> std::vector<LayerTestResult<T,3>> SplitterTestCommon(</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keywordtype">float</span> qScale = 0.0f,</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  int32_t qOffset = 0)</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> {</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 5;</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 6;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 3;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="comment">// NOTE: Compute Library imposes a restriction that the x and y dimension (input height and width)</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="comment">// cannot be split.</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="comment">// For the reasons for this, see first comment on https://jira.arm.com/browse/IVGCVSW-1239</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="comment">//</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="comment">// This test has therefore been recast to split the channels, then split the resulting subtensor.</span></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">// To take channel 0 of original output</span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="comment">// and channel 0 and channel 1 of the split subtensor.</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth1 = inputWidth;</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight1 = inputHeight;</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels1 = 1;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="comment">// To take channel 1 and 2 of the original output.</span></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth2 = inputWidth;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight2 = inputHeight;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels2 = 2;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="comment">// Define the tensor descriptors.</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({ inputChannels, inputHeight, inputWidth }, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> </div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="comment">// Outputs of the original split.</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo1({ outputChannels1, outputHeight1, outputWidth1 }, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo2({ outputChannels2, outputHeight2, outputWidth2 }, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// Outputs of the subsequent subtensor split.</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo3({ outputChannels1, outputHeight1, outputWidth1 }, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo4({ outputChannels1, outputHeight1, outputWidth1 }, ArmnnType, qScale, qOffset);</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="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// The quantization doesn't really matter as the splitter operator doesn't dequantize/quantize.</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordflow">if</span>(armnn::IsQuantizedType<T>())</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  {</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  outputTensorInfo1.SetQuantizationScale(qScale);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  outputTensorInfo1.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  outputTensorInfo2.SetQuantizationScale(qScale);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  outputTensorInfo2.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  outputTensorInfo3.SetQuantizationScale(qScale);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  outputTensorInfo3.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  outputTensorInfo4.SetQuantizationScale(qScale);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  outputTensorInfo4.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  }</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T,3></a> ret1(outputTensorInfo1);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T,3></a> ret2(outputTensorInfo2);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T,3></a> ret3(outputTensorInfo3);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T,3></a> ret4(outputTensorInfo4);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keyword">auto</span> input = MakeTensor<T, 3>(inputTensorInfo, std::vector<T>(</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  1.0f, 2.0f, 3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  6.0f, 7.0f, 8.0f, 9.0f, 10.0f,</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  11.0f, 12.0f, 13.0f, 14.0f, 15.0f,</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  16.0f, 17.0f, 18.0f, 19.0f, 20.0f,</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  21.0f, 22.0f, 23.0f, 24.0f, 25.0f,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  26.0f, 27.0f, 28.0f, 29.0f, 30.0f,</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  31.0f, 32.0f, 33.0f, 34.0f, 35.0f,</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  36.0f, 37.0f, 38.0f, 39.0f, 40.0f,</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  41.0f, 42.0f, 43.0f, 44.0f, 45.0f,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  46.0f, 47.0f, 48.0f, 49.0f, 50.0f,</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  51.0f, 52.0f, 53.0f, 54.0f, 55.0f,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  56.0f, 57.0f, 58.0f, 59.0f, 60.0f,</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>  61.0f, 62.0f, 63.0f, 64.0f, 65.0f,</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  66.0f, 67.0f, 68.0f, 69.0f, 70.0f,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  71.0f, 72.0f, 73.0f, 74.0f, 75.0f,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  76.0f, 77.0f, 78.0f, 79.0f, 80.0f,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  81.0f, 82.0f, 83.0f, 84.0f, 85.0f,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  86.0f, 87.0f, 88.0f, 89.0f, 90.0f,</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>  qScale, qOffset)</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  ));</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <span class="comment">// Channel 0 of the original input.</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  ret1.outputExpected = MakeTensor<T, 3>(outputTensorInfo1, std::vector<T>(</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  1.0f, 2.0f, 3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  6.0f, 7.0f, 8.0f, 9.0f, 10.0f,</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  11.0f, 12.0f, 13.0f, 14.0f, 15.0f,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  16.0f, 17.0f, 18.0f, 19.0f, 20.0f,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  21.0f, 22.0f, 23.0f, 24.0f, 25.0f,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  26.0f, 27.0f, 28.0f, 29.0f, 30.0f,</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  },</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  qScale, qOffset)</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> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="comment">// Channel 1 & 2 of the original input.</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  ret2.outputExpected = MakeTensor<T, 3>(outputTensorInfo2, std::vector<T>(</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  31.0f, 32.0f, 33.0f, 34.0f, 35.0f,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  36.0f, 37.0f, 38.0f, 39.0f, 40.0f,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  41.0f, 42.0f, 43.0f, 44.0f, 45.0f,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  46.0f, 47.0f, 48.0f, 49.0f, 50.0f,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  51.0f, 52.0f, 53.0f, 54.0f, 55.0f,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  56.0f, 57.0f, 58.0f, 59.0f, 60.0f,</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>  61.0f, 62.0f, 63.0f, 64.0f, 65.0f,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  66.0f, 67.0f, 68.0f, 69.0f, 70.0f,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  71.0f, 72.0f, 73.0f, 74.0f, 75.0f,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  76.0f, 77.0f, 78.0f, 79.0f, 80.0f,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  81.0f, 82.0f, 83.0f, 84.0f, 85.0f,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  86.0f, 87.0f, 88.0f, 89.0f, 90.0f,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  },</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  qScale, qOffset)</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  ));</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="comment">// Channel 0 of return 2 (i.e. channels 1 and 2 of the original input).</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  ret3.outputExpected = MakeTensor<T, 3>(outputTensorInfo3, std::vector<T>(</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  31.0f, 32.0f, 33.0f, 34.0f, 35.0f,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  36.0f, 37.0f, 38.0f, 39.0f, 40.0f,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  41.0f, 42.0f, 43.0f, 44.0f, 45.0f,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  46.0f, 47.0f, 48.0f, 49.0f, 50.0f,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  51.0f, 52.0f, 53.0f, 54.0f, 55.0f,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  56.0f, 57.0f, 58.0f, 59.0f, 60.0f,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  },</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  qScale, qOffset)</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  ));</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="comment">// Channel 1 of return 2.</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  ret4.outputExpected = MakeTensor<T, 3>(outputTensorInfo4, std::vector<T>(</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  61.0f, 62.0f, 63.0f, 64.0f, 65.0f,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  66.0f, 67.0f, 68.0f, 69.0f, 70.0f,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  71.0f, 72.0f, 73.0f, 74.0f, 75.0f,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  76.0f, 77.0f, 78.0f, 79.0f, 80.0f,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  81.0f, 82.0f, 83.0f, 84.0f, 85.0f,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  86.0f, 87.0f, 88.0f, 89.0f, 90.0f,</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  },</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  qScale, qOffset)</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  ));</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="comment">// NOTE: as a corollary of the splitting of x and y restriction the x and y values of the view origins</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="comment">// have to be zero, the co-ordinates are as per the tensor info above channels, height/y, width/x</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="comment">// note that under the hood the compute engine reverses these i.e. its coordinate system is x, y, channels.</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  std::vector<unsigned int> wOrigin1 = {0, 0, 0}; <span class="comment">//Extent of the window is defined by size of output[0].</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <a class="code" href="structarmnn_1_1_splitter_queue_descriptor_1_1_view_origin.xhtml">armnn::SplitterQueueDescriptor::ViewOrigin</a> window1(wOrigin1);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  std::vector<unsigned int> wOrigin2 = {1, 0, 0}; <span class="comment">//Extent of the window is defined by size of output[1].</span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <a class="code" href="structarmnn_1_1_splitter_queue_descriptor_1_1_view_origin.xhtml">armnn::SplitterQueueDescriptor::ViewOrigin</a> window2(wOrigin2);</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  std::vector<unsigned int> wOrigin3 = {0, 0, 0}; <span class="comment">//Extent of the window is defined by size of output[2].</span></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="structarmnn_1_1_splitter_queue_descriptor_1_1_view_origin.xhtml">armnn::SplitterQueueDescriptor::ViewOrigin</a> window3(wOrigin3);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  std::vector<unsigned int> wOrigin4 = {1, 0, 0}; <span class="comment">//Extent of the window is defined by size of output[3].</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <a class="code" href="structarmnn_1_1_splitter_queue_descriptor_1_1_view_origin.xhtml">armnn::SplitterQueueDescriptor::ViewOrigin</a> window4(wOrigin4);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> </div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordtype">bool</span> subTensorsSupported = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a37f4eba7877deb34f4d8d64c9bcb9ab5">SupportsSubTensors</a>();</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>  std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> </div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle1 =</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  subTensorsSupported ?</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac043991b839903b2ba9da884e4020848">CreateSubTensorHandle</a>(*inputHandle, outputTensorInfo1.GetShape(), wOrigin1.data()) :</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo1);</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>  std::unique_ptr<armnn::ITensorHandle> outputHandle2 =</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  subTensorsSupported ?</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac043991b839903b2ba9da884e4020848">CreateSubTensorHandle</a>(*inputHandle, outputTensorInfo2.GetShape(), wOrigin2.data()) :</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo2);</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle3 =</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  subTensorsSupported ?</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac043991b839903b2ba9da884e4020848">CreateSubTensorHandle</a>(*outputHandle2, outputTensorInfo3.GetShape(), wOrigin3.data()) :</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo3);</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle4 =</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  subTensorsSupported ?</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac043991b839903b2ba9da884e4020848">CreateSubTensorHandle</a>(*outputHandle2, outputTensorInfo4.GetShape(), wOrigin4.data()) :</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo4);</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">// Do the first split</span></div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <a class="code" href="structarmnn_1_1_splitter_queue_descriptor.xhtml">armnn::SplitterQueueDescriptor</a> data;</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  AddOutputToWorkload(data, info, outputTensorInfo1, outputHandle1.get());</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  AddOutputToWorkload(data, info, outputTensorInfo2, outputHandle2.get());</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  data.<a class="code" href="structarmnn_1_1_splitter_queue_descriptor.xhtml#ab1794eb3e74c9700cd3d500fc06dc2e5">m_ViewOrigins</a>.push_back(window1);</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  data.<a class="code" href="structarmnn_1_1_splitter_queue_descriptor.xhtml#ab1794eb3e74c9700cd3d500fc06dc2e5">m_ViewOrigins</a>.push_back(window2);</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac306abe0073a04300f2d96d0b5eb6218">CreateSplitter</a>(data, info);</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> </div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  inputHandle->Allocate();</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  outputHandle1->Allocate();</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  outputHandle2->Allocate();</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> </div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &input[0][0][0]);</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> </div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  workload->Execute();</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> </div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret1.output[0][0][0], outputHandle1.get());</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret2.output[0][0][0], outputHandle2.get());</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> </div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="comment">// Do the second split.</span></div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <a class="code" href="structarmnn_1_1_splitter_queue_descriptor.xhtml">armnn::SplitterQueueDescriptor</a> data2;</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> info2;</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  AddInputToWorkload(data2, info2, outputTensorInfo2, outputHandle2.get());</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  AddOutputToWorkload(data2, info2, outputTensorInfo3, outputHandle3.get());</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  AddOutputToWorkload(data2, info2, outputTensorInfo4, outputHandle4.get());</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> </div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  data2.m_ViewOrigins.push_back(window3);</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  data2.m_ViewOrigins.push_back(window4);</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  std::unique_ptr<armnn::IWorkload> workload2 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac306abe0073a04300f2d96d0b5eb6218">CreateSplitter</a>(data2, info2);</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  outputHandle3->Allocate();</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  outputHandle4->Allocate();</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  ExecuteWorkload(*workload2, memoryManager);</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> </div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret3.output[0][0][0], outputHandle3.get());</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret4.output[0][0][0], outputHandle4.get());</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> </div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  std::vector<LayerTestResult<T,3>> ret = {ret1, ret2, ret3, ret4,};</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> </div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> }</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span> </div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 3></a> CopyViaSplitterTestImpl(</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keywordtype">float</span> qScale, int32_t qOffset)</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> {</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo({ 3, 6, 5 }, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keyword">auto</span> input = MakeTensor<T, 3>(</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  tensorInfo,</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  1.0f, 2.0f, 3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  6.0f, 7.0f, 8.0f, 9.0f, 10.0f,</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  11.0f, 12.0f, 13.0f, 14.0f, 15.0f,</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  16.0f, 17.0f, 18.0f, 19.0f, 20.0f,</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  21.0f, 22.0f, 23.0f, 24.0f, 25.0f,</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  26.0f, 27.0f, 28.0f, 29.0f, 30.0f,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> </div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  31.0f, 32.0f, 33.0f, 34.0f, 35.0f,</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  36.0f, 37.0f, 38.0f, 39.0f, 40.0f,</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  41.0f, 42.0f, 43.0f, 44.0f, 45.0f,</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  46.0f, 47.0f, 48.0f, 49.0f, 50.0f,</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  51.0f, 52.0f, 53.0f, 54.0f, 55.0f,</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  56.0f, 57.0f, 58.0f, 59.0f, 60.0f,</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span> </div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  61.0f, 62.0f, 63.0f, 64.0f, 65.0f,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  66.0f, 67.0f, 68.0f, 69.0f, 70.0f,</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  71.0f, 72.0f, 73.0f, 74.0f, 75.0f,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  76.0f, 77.0f, 78.0f, 79.0f, 80.0f,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  81.0f, 82.0f, 83.0f, 84.0f, 85.0f,</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  86.0f, 87.0f, 88.0f, 89.0f, 90.0f,</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  },</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  qScale, qOffset));</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> </div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  std::vector<unsigned int> origin = { 0, 0, 0 };</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <a class="code" href="structarmnn_1_1_splitter_queue_descriptor_1_1_view_origin.xhtml">armnn::SplitterQueueDescriptor::ViewOrigin</a> window(origin);</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> </div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> subTensorsSupported = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a37f4eba7877deb34f4d8d64c9bcb9ab5">SupportsSubTensors</a>();</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> </div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(tensorInfo);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle =</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  subTensorsSupported ?</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac043991b839903b2ba9da884e4020848">CreateSubTensorHandle</a>(*inputHandle, tensorInfo.GetShape(), origin.data()) :</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(tensorInfo);</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> </div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="structarmnn_1_1_splitter_queue_descriptor.xhtml">armnn::SplitterQueueDescriptor</a> data;</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> info;</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  AddInputToWorkload(data, info, tensorInfo, inputHandle.get());</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  AddOutputToWorkload(data, info, tensorInfo, outputHandle.get());</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  data.<a class="code" href="structarmnn_1_1_splitter_queue_descriptor.xhtml#ab1794eb3e74c9700cd3d500fc06dc2e5">m_ViewOrigins</a>.push_back(window);</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> </div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac306abe0073a04300f2d96d0b5eb6218">CreateSplitter</a>(data, info);</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> </div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  inputHandle->Allocate();</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  outputHandle->Allocate();</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> </div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &input[0][0][0]);</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> </div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  workload->Execute();</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> </div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 3></a> ret(tensorInfo);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret.output[0][0][0], outputHandle.get());</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  ret.outputExpected = input;</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> </div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> }</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span> </div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> } <span class="comment">// anonymous namespace</span></div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> </div><div class="line"><a name="l00325"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#af2dfa3c07a3698b69f323f64e7b5b370"> 325</a></span> std::vector<LayerTestResult<float,3>> <a class="code" href="_splitter_test_impl_8cpp.xhtml#a23e8abfd741a311fb1b4cbcaaac78954">SplitterFloat32Test</a>(</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> {</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">return</span> SplitterTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager);</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span> }</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> </div><div class="line"><a name="l00332"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#a2dc8e105415f62c0d87b9d0b2f7c4a2f"> 332</a></span> std::vector<LayerTestResult<armnn::Half,3>> <a class="code" href="_splitter_test_impl_8cpp.xhtml#a453db2afb43ae787956ad61d8a066590">SplitterFloat16Test</a>(</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span> {</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="keywordflow">return</span> SplitterTestCommon<armnn::DataType::Float16>(workloadFactory, memoryManager);</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> }</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> </div><div class="line"><a name="l00339"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#aa783b71d120d14fa279d55109374a3ff"> 339</a></span> std::vector<LayerTestResult<uint8_t,3>> <a class="code" href="_splitter_test_impl_8cpp.xhtml#a1eac36c98897fbaa8d475f3a915758bb">SplitterUint8Test</a>(</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span> {</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordflow">return</span> SplitterTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, 1.0f, 0);</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span> }</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> </div><div class="line"><a name="l00346"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#a26c45172004eb8d931f711d1823cfc31"> 346</a></span> std::vector<LayerTestResult<int16_t,3>> <a class="code" href="_splitter_test_impl_8cpp.xhtml#ab5fc5e347f35600b9c89932ba7f4f8b2">SplitterInt16Test</a>(</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> {</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">return</span> SplitterTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, 1.0f, 0);</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> }</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span> </div><div class="line"><a name="l00353"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#ac95add95bf20160322f853e3bf4eff81"> 353</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 3></a> <a class="code" href="_splitter_test_impl_8cpp.xhtml#ac95add95bf20160322f853e3bf4eff81">CopyViaSplitterFloat32Test</a>(</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> {</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="keywordflow">return</span> CopyViaSplitterTestImpl<armnn::DataType::Float32>(workloadFactory, memoryManager, 0.0f, 0);</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> }</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span> </div><div class="line"><a name="l00360"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#af17e5820f33c37402a85c966b469a52a"> 360</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<armnn::Half, 3></a> <a class="code" href="_splitter_test_impl_8cpp.xhtml#af17e5820f33c37402a85c966b469a52a">CopyViaSplitterFloat16Test</a>(</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> {</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keywordflow">return</span> CopyViaSplitterTestImpl<armnn::DataType::Float16>(workloadFactory, memoryManager, 0.0f, 0);</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span> }</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span> </div><div class="line"><a name="l00367"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#a32caee0c12392e001c04d36b1f0774cf"> 367</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 3></a> <a class="code" href="_splitter_test_impl_8cpp.xhtml#a32caee0c12392e001c04d36b1f0774cf">CopyViaSplitterUint8Test</a>(</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> {</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keywordflow">return</span> CopyViaSplitterTestImpl<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, 1.0f, 0);</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> }</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> </div><div class="line"><a name="l00374"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#ae5c9cb5a3ad371cee5b3e04f79106b74"> 374</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 3></a> <a class="code" href="_splitter_test_impl_8cpp.xhtml#ae5c9cb5a3ad371cee5b3e04f79106b74">CopyViaSplitterInt16Test</a>(</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager)</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> {</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="keywordflow">return</span> CopyViaSplitterTestImpl<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, 1.0f, 0);</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> }</div><div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ac306abe0073a04300f2d96d0b5eb6218"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ac306abe0073a04300f2d96d0b5eb6218">armnn::IWorkloadFactory::CreateSplitter</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateSplitter(const SplitterQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01406">WorkloadFactory.cpp:1406</a></div></div> +<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_a23e8abfd741a311fb1b4cbcaaac78954"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a23e8abfd741a311fb1b4cbcaaac78954">SplitterFloat32Test</a></div><div class="ttdeci">std::vector< LayerTestResult< float, 3 > > SplitterFloat32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00325">SplitterTestImpl.cpp:325</a></div></div> +<div class="ttc" id="_tensor_copy_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_copy_utils_8hpp.xhtml">TensorCopyUtils.hpp</a></div></div> +<div class="ttc" id="structarmnn_1_1_splitter_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_splitter_queue_descriptor.xhtml">armnn::SplitterQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00083">WorkloadData.hpp:83</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="_quantize_helper_8hpp_xhtml"><div class="ttname"><a href="_quantize_helper_8hpp.xhtml">QuantizeHelper.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.xhtml#l00021">WorkloadFactory.hpp:21</a></div></div> +<div class="ttc" id="_workload_test_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_test_utils_8hpp.xhtml">WorkloadTestUtils.hpp</a></div></div> +<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_a32caee0c12392e001c04d36b1f0774cf"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a32caee0c12392e001c04d36b1f0774cf">CopyViaSplitterUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 3 > CopyViaSplitterUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00367">SplitterTestImpl.cpp:367</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ac043991b839903b2ba9da884e4020848"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ac043991b839903b2ba9da884e4020848">armnn::IWorkloadFactory::CreateSubTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateSubTensorHandle(ITensorHandle &parent, TensorShape const &subTensorShape, unsigned int const *subTensorOrigin) const =0</div></div> +<div class="ttc" id="structarmnn_1_1_splitter_queue_descriptor_1_1_view_origin_xhtml"><div class="ttname"><a href="structarmnn_1_1_splitter_queue_descriptor_1_1_view_origin.xhtml">armnn::SplitterQueueDescriptor::ViewOrigin</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00085">WorkloadData.hpp:85</a></div></div> +<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_af17e5820f33c37402a85c966b469a52a"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#af17e5820f33c37402a85c966b469a52a">CopyViaSplitterFloat16Test</a></div><div class="ttdeci">LayerTestResult< armnn::Half, 3 > CopyViaSplitterFloat16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00360">SplitterTestImpl.cpp:360</a></div></div> +<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_a453db2afb43ae787956ad61d8a066590"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a453db2afb43ae787956ad61d8a066590">SplitterFloat16Test</a></div><div class="ttdeci">std::vector< LayerTestResult< armnn::Half, 3 > > SplitterFloat16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00332">SplitterTestImpl.cpp:332</a></div></div> +<div class="ttc" id="_resolve_type_8hpp_xhtml"><div class="ttname"><a href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a></div></div> +<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_a1eac36c98897fbaa8d475f3a915758bb"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a1eac36c98897fbaa8d475f3a915758bb">SplitterUint8Test</a></div><div class="ttdeci">std::vector< LayerTestResult< uint8_t, 3 > > SplitterUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00339">SplitterTestImpl.cpp:339</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="_tensor_helpers_8hpp_xhtml"><div class="ttname"><a href="_tensor_helpers_8hpp.xhtml">TensorHelpers.hpp</a></div></div> +<div class="ttc" id="_splitter_test_impl_8hpp_xhtml"><div class="ttname"><a href="_splitter_test_impl_8hpp.xhtml">SplitterTestImpl.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_backend_internal_xhtml_a693b40e6b94e958836aeb0410ca186bd"><div class="ttname"><a href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a></div><div class="ttdeci">std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.xhtml#l00090">IBackendInternal.hpp:90</a></div></div> +<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_ab5fc5e347f35600b9c89932ba7f4f8b2"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#ab5fc5e347f35600b9c89932ba7f4f8b2">SplitterInt16Test</a></div><div class="ttdeci">std::vector< LayerTestResult< int16_t, 3 > > SplitterInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00346">SplitterTestImpl.cpp:346</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00259">Tensor.cpp:259</a></div></div> +<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_splitter_queue_descriptor_xhtml_ab1794eb3e74c9700cd3d500fc06dc2e5"><div class="ttname"><a href="structarmnn_1_1_splitter_queue_descriptor.xhtml#ab1794eb3e74c9700cd3d500fc06dc2e5">armnn::SplitterQueueDescriptor::m_ViewOrigins</a></div><div class="ttdeci">std::vector< ViewOrigin > m_ViewOrigins</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00096">WorkloadData.hpp:96</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0</div></div> +<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_ac95add95bf20160322f853e3bf4eff81"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#ac95add95bf20160322f853e3bf4eff81">CopyViaSplitterFloat32Test</a></div><div class="ttdeci">LayerTestResult< float, 3 > CopyViaSplitterFloat32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00353">SplitterTestImpl.cpp:353</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div> +<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_ae5c9cb5a3ad371cee5b3e04f79106b74"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#ae5c9cb5a3ad371cee5b3e04f79106b74">CopyViaSplitterInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 3 > CopyViaSplitterInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00374">SplitterTestImpl.cpp:374</a></div></div> +<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a37f4eba7877deb34f4d8d64c9bcb9ab5"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a37f4eba7877deb34f4d8d64c9bcb9ab5">armnn::IWorkloadFactory::SupportsSubTensors</a></div><div class="ttdeci">virtual bool SupportsSubTensors() const =0</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="dir_28bfe507f7e135bdae07c2a6b7f66696.xhtml">test</a></li><li class="navelem"><a class="el" href="dir_99a30439342d160875b21dac3498ad7f.xhtml">layerTests</a></li><li class="navelem"><a class="el" href="_splitter_test_impl_8cpp.xhtml">SplitterTestImpl.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> |