1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
|
<!-- 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">21.02</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 and Contributors. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_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="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keywordtype">float</span> qScale = 0.0f,</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  int32_t qOffset = 0)</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>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 5;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 6;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 3;</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="comment">// NOTE: Compute Library imposes a restriction that the x and y dimension (input height and width)</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="comment">// cannot be split.</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</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="l00036"></a><span class="lineno"> 36</span>  <span class="comment">//</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</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="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="comment">// To take channel 0 of original output</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="comment">// and channel 0 and channel 1 of the split subtensor.</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth1 = inputWidth;</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight1 = inputHeight;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels1 = 1;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="comment">// To take channel 1 and 2 of the original output.</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth2 = inputWidth;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight2 = inputHeight;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels2 = 2;</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> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="comment">// Define the tensor descriptors.</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</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="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="comment">// Outputs of the original split.</span></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> outputTensorInfo1({ outputChannels1, outputHeight1, outputWidth1 }, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</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="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="comment">// Outputs of the subsequent subtensor split.</span></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> outputTensorInfo3({ outputChannels1, outputHeight1, outputWidth1 }, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</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="l00061"></a><span class="lineno"> 61</span> </div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</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="l00064"></a><span class="lineno"> 64</span>  <span class="keywordflow">if</span>(armnn::IsQuantizedType<T>())</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  {</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  inputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  outputTensorInfo1.SetQuantizationScale(qScale);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  outputTensorInfo1.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  outputTensorInfo2.SetQuantizationScale(qScale);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  outputTensorInfo2.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  outputTensorInfo3.SetQuantizationScale(qScale);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  outputTensorInfo3.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  outputTensorInfo4.SetQuantizationScale(qScale);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  outputTensorInfo4.SetQuantizationOffset(qOffset);</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> </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> ret1(outputTensorInfo1);</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> ret2(outputTensorInfo2);</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> ret3(outputTensorInfo3);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T,3></a> ret4(outputTensorInfo4);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keyword">auto</span> input = MakeTensor<T, 3>(inputTensorInfo, std::vector<T>(</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  1.0f, 2.0f, 3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  6.0f, 7.0f, 8.0f, 9.0f, 10.0f,</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  11.0f, 12.0f, 13.0f, 14.0f, 15.0f,</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  16.0f, 17.0f, 18.0f, 19.0f, 20.0f,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  21.0f, 22.0f, 23.0f, 24.0f, 25.0f,</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  26.0f, 27.0f, 28.0f, 29.0f, 30.0f,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  31.0f, 32.0f, 33.0f, 34.0f, 35.0f,</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  36.0f, 37.0f, 38.0f, 39.0f, 40.0f,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  41.0f, 42.0f, 43.0f, 44.0f, 45.0f,</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  46.0f, 47.0f, 48.0f, 49.0f, 50.0f,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  51.0f, 52.0f, 53.0f, 54.0f, 55.0f,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  56.0f, 57.0f, 58.0f, 59.0f, 60.0f,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  61.0f, 62.0f, 63.0f, 64.0f, 65.0f,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  66.0f, 67.0f, 68.0f, 69.0f, 70.0f,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  71.0f, 72.0f, 73.0f, 74.0f, 75.0f,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  76.0f, 77.0f, 78.0f, 79.0f, 80.0f,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  81.0f, 82.0f, 83.0f, 84.0f, 85.0f,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  86.0f, 87.0f, 88.0f, 89.0f, 90.0f,</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  },</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  qScale, qOffset)</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"> 109</span>  <span class="comment">// Channel 0 of the original input.</span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  ret1.outputExpected = MakeTensor<T, 3>(outputTensorInfo1, std::vector<T>(</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  1.0f, 2.0f, 3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  6.0f, 7.0f, 8.0f, 9.0f, 10.0f,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  11.0f, 12.0f, 13.0f, 14.0f, 15.0f,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  16.0f, 17.0f, 18.0f, 19.0f, 20.0f,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  21.0f, 22.0f, 23.0f, 24.0f, 25.0f,</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  26.0f, 27.0f, 28.0f, 29.0f, 30.0f,</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  },</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  qScale, qOffset)</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> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="comment">// Channel 1 & 2 of the original input.</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  ret2.outputExpected = MakeTensor<T, 3>(outputTensorInfo2, std::vector<T>(</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  31.0f, 32.0f, 33.0f, 34.0f, 35.0f,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  36.0f, 37.0f, 38.0f, 39.0f, 40.0f,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  41.0f, 42.0f, 43.0f, 44.0f, 45.0f,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  46.0f, 47.0f, 48.0f, 49.0f, 50.0f,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  51.0f, 52.0f, 53.0f, 54.0f, 55.0f,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  56.0f, 57.0f, 58.0f, 59.0f, 60.0f,</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  61.0f, 62.0f, 63.0f, 64.0f, 65.0f,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  66.0f, 67.0f, 68.0f, 69.0f, 70.0f,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  71.0f, 72.0f, 73.0f, 74.0f, 75.0f,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  76.0f, 77.0f, 78.0f, 79.0f, 80.0f,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  81.0f, 82.0f, 83.0f, 84.0f, 85.0f,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  86.0f, 87.0f, 88.0f, 89.0f, 90.0f,</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>  qScale, qOffset)</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> </div><div class="line"><a name="l00142"></a><span class="lineno"> 142</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="l00143"></a><span class="lineno"> 143</span>  ret3.outputExpected = MakeTensor<T, 3>(outputTensorInfo3, std::vector<T>(</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  31.0f, 32.0f, 33.0f, 34.0f, 35.0f,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  36.0f, 37.0f, 38.0f, 39.0f, 40.0f,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  41.0f, 42.0f, 43.0f, 44.0f, 45.0f,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  46.0f, 47.0f, 48.0f, 49.0f, 50.0f,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  51.0f, 52.0f, 53.0f, 54.0f, 55.0f,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  56.0f, 57.0f, 58.0f, 59.0f, 60.0f,</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>  qScale, qOffset)</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> </div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="comment">// Channel 1 of return 2.</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  ret4.outputExpected = MakeTensor<T, 3>(outputTensorInfo4, std::vector<T>(</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  61.0f, 62.0f, 63.0f, 64.0f, 65.0f,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  66.0f, 67.0f, 68.0f, 69.0f, 70.0f,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  71.0f, 72.0f, 73.0f, 74.0f, 75.0f,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  76.0f, 77.0f, 78.0f, 79.0f, 80.0f,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  81.0f, 82.0f, 83.0f, 84.0f, 85.0f,</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  86.0f, 87.0f, 88.0f, 89.0f, 90.0f,</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  },</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  qScale, qOffset)</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> </div><div class="line"><a name="l00168"></a><span class="lineno"> 168</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="l00169"></a><span class="lineno"> 169</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="l00170"></a><span class="lineno"> 170</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="l00171"></a><span class="lineno"> 171</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="l00172"></a><span class="lineno"> 172</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="l00173"></a><span class="lineno"> 173</span> </div><div class="line"><a name="l00174"></a><span class="lineno"> 174</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="l00175"></a><span class="lineno"> 175</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="l00176"></a><span class="lineno"> 176</span> </div><div class="line"><a name="l00177"></a><span class="lineno"> 177</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="l00178"></a><span class="lineno"> 178</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="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</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="l00181"></a><span class="lineno"> 181</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="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keywordtype">bool</span> subTensorsSupported = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a37f4eba7877deb34f4d8d64c9bcb9ab5">SupportsSubTensors</a>();</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">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>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ac043991b839903b2ba9da884e4020848">CreateSubTensorHandle</a>(*inputHandle, outputTensorInfo1.GetShape(), wOrigin1.data()) :</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">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>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ac043991b839903b2ba9da884e4020848">CreateSubTensorHandle</a>(*inputHandle, outputTensorInfo2.GetShape(), wOrigin2.data()) :</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">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>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ac043991b839903b2ba9da884e4020848">CreateSubTensorHandle</a>(*outputHandle2, outputTensorInfo3.GetShape(), wOrigin3.data()) :</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">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>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ac043991b839903b2ba9da884e4020848">CreateSubTensorHandle</a>(*outputHandle2, outputTensorInfo4.GetShape(), wOrigin4.data()) :</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">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="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keywordtype">float</span> qScale, int32_t qOffset)</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> {</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</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="l00263"></a><span class="lineno"> 263</span>  <span class="keyword">auto</span> input = MakeTensor<T, 3>(</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  tensorInfo,</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  armnnUtils::QuantizedVector<T>({</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  1.0f, 2.0f, 3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  6.0f, 7.0f, 8.0f, 9.0f, 10.0f,</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  11.0f, 12.0f, 13.0f, 14.0f, 15.0f,</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  16.0f, 17.0f, 18.0f, 19.0f, 20.0f,</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  21.0f, 22.0f, 23.0f, 24.0f, 25.0f,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  26.0f, 27.0f, 28.0f, 29.0f, 30.0f,</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> </div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  31.0f, 32.0f, 33.0f, 34.0f, 35.0f,</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  36.0f, 37.0f, 38.0f, 39.0f, 40.0f,</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  41.0f, 42.0f, 43.0f, 44.0f, 45.0f,</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  46.0f, 47.0f, 48.0f, 49.0f, 50.0f,</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  51.0f, 52.0f, 53.0f, 54.0f, 55.0f,</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  56.0f, 57.0f, 58.0f, 59.0f, 60.0f,</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> </div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  61.0f, 62.0f, 63.0f, 64.0f, 65.0f,</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  66.0f, 67.0f, 68.0f, 69.0f, 70.0f,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  71.0f, 72.0f, 73.0f, 74.0f, 75.0f,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  76.0f, 77.0f, 78.0f, 79.0f, 80.0f,</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  81.0f, 82.0f, 83.0f, 84.0f, 85.0f,</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  86.0f, 87.0f, 88.0f, 89.0f, 90.0f,</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  },</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  qScale, qOffset));</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> </div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  std::vector<unsigned int> origin = { 0, 0, 0 };</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</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="l00291"></a><span class="lineno"> 291</span> </div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> subTensorsSupported = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a37f4eba7877deb34f4d8d64c9bcb9ab5">SupportsSubTensors</a>();</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">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>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ac043991b839903b2ba9da884e4020848">CreateSubTensorHandle</a>(*inputHandle, tensorInfo.GetShape(), origin.data()) :</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">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#ae9776e5eacfa84e930e37360085ba492"> 325</a></span> std::vector<LayerTestResult<float,3>> <a class="code" href="_splitter_test_impl_8cpp.xhtml#a65ba472fb1d6550f1ae5fb937b23d0c5">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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> {</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="keywordflow">return</span> SplitterTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> }</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> </div><div class="line"><a name="l00333"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#a3b0e76c29b1a16c11e33c4ccae8dc292"> 333</a></span> std::vector<LayerTestResult<armnn::Half,3>> <a class="code" href="_splitter_test_impl_8cpp.xhtml#a273653c7436f5a92b9e32d15825983f0">SplitterFloat16Test</a>(</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</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="l00336"></a><span class="lineno"> 336</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</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>  <span class="keywordflow">return</span> SplitterTestCommon<armnn::DataType::Float16>(workloadFactory, memoryManager, tensorHandleFactory);</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span> }</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span> </div><div class="line"><a name="l00341"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#afaae5d80b31a8b4fe4792ec52d976132"> 341</a></span> std::vector<LayerTestResult<uint8_t,3>> <a class="code" href="_splitter_test_impl_8cpp.xhtml#a10c1752ab78fd2f7fc58fda5e2836015">SplitterUint8Test</a>(</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</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="l00344"></a><span class="lineno"> 344</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> {</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keywordflow">return</span> SplitterTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, tensorHandleFactory, 1.0f, 0);</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> }</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span> </div><div class="line"><a name="l00349"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#a3749192defff68ea558cc116a691ad83"> 349</a></span> std::vector<LayerTestResult<int16_t,3>> <a class="code" href="_splitter_test_impl_8cpp.xhtml#a0fa291bb2b9b182a286e600a3b990c16">SplitterInt16Test</a>(</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</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="l00352"></a><span class="lineno"> 352</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> {</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keywordflow">return</span> SplitterTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 1.0f, 0);</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> }</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> </div><div class="line"><a name="l00357"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#aaa54cb9a063b9453f453622c4521a035"> 357</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 3></a> <a class="code" href="_splitter_test_impl_8cpp.xhtml#aaa54cb9a063b9453f453622c4521a035">CopyViaSplitterFloat32Test</a>(</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</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="l00360"></a><span class="lineno"> 360</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span> {</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">return</span> CopyViaSplitterTestImpl<armnn::DataType::Float32>(workloadFactory,</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  memoryManager,</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  tensorHandleFactory,</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  0.0f,</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  0);</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span> }</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> </div><div class="line"><a name="l00369"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#a1ff233f3179fa9ce3a80ae456bbb9e8b"> 369</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#a1ff233f3179fa9ce3a80ae456bbb9e8b">CopyViaSplitterFloat16Test</a>(</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</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="l00372"></a><span class="lineno"> 372</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> {</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordflow">return</span> CopyViaSplitterTestImpl<armnn::DataType::Float16>(workloadFactory,</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  memoryManager,</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  tensorHandleFactory,</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  0.0f,</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  0);</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> }</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div><div class="line"><a name="l00381"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#a288952c7a06bf77dfaddaf70ba03f2f5"> 381</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#a288952c7a06bf77dfaddaf70ba03f2f5">CopyViaSplitterUint8Test</a>(</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</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="l00384"></a><span class="lineno"> 384</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> {</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="keywordflow">return</span> CopyViaSplitterTestImpl<armnn::DataType::QAsymmU8>(workloadFactory,</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  memoryManager,</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  tensorHandleFactory,</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  1.0f,</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  0);</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> }</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span> </div><div class="line"><a name="l00393"></a><span class="lineno"><a class="line" href="_splitter_test_impl_8hpp.xhtml#a432bea508d3e2565091bb27aacb883ff"> 393</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#a432bea508d3e2565091bb27aacb883ff">CopyViaSplitterInt16Test</a>(</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</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="l00396"></a><span class="lineno"> 396</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span> {</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keywordflow">return</span> CopyViaSplitterTestImpl<armnn::DataType::QSymmS16>(workloadFactory,</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  memoryManager,</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  tensorHandleFactory,</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  1.0f,</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  0);</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span> }</div><div class="ttc" id="_splitter_test_impl_8cpp_xhtml_a65ba472fb1d6550f1ae5fb937b23d0c5"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a65ba472fb1d6550f1ae5fb937b23d0c5">SplitterFloat32Test</a></div><div class="ttdeci">std::vector< LayerTestResult< float, 3 > > SplitterFloat32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</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="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#l01650">WorkloadFactory.cpp:1650</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#l00101">WorkloadData.hpp:101</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#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_aaa54cb9a063b9453f453622c4521a035"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#aaa54cb9a063b9453f453622c4521a035">CopyViaSplitterFloat32Test</a></div><div class="ttdeci">LayerTestResult< float, 3 > CopyViaSplitterFloat32Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00357">SplitterTestImpl.cpp:357</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#l00022">WorkloadFactory.hpp:22</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_a10c1752ab78fd2f7fc58fda5e2836015"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a10c1752ab78fd2f7fc58fda5e2836015">SplitterUint8Test</a></div><div class="ttdeci">std::vector< LayerTestResult< uint8_t, 3 > > SplitterUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00341">SplitterTestImpl.cpp:341</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_ac043991b839903b2ba9da884e4020848"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#ac043991b839903b2ba9da884e4020848">armnn::ITensorHandleFactory::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#l00103">WorkloadData.hpp:103</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="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_8cpp_xhtml_a288952c7a06bf77dfaddaf70ba03f2f5"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a288952c7a06bf77dfaddaf70ba03f2f5">CopyViaSplitterUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 3 > CopyViaSplitterUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00381">SplitterTestImpl.cpp:381</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#l00092">IBackendInternal.hpp:92</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#l00464">Tensor.cpp:464</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a37f4eba7877deb34f4d8d64c9bcb9ab5"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a37f4eba7877deb34f4d8d64c9bcb9ab5">armnn::ITensorHandleFactory::SupportsSubTensors</a></div><div class="ttdeci">virtual bool SupportsSubTensors() const =0</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#l00114">WorkloadData.hpp:114</a></div></div>
<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_a273653c7436f5a92b9e32d15825983f0"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a273653c7436f5a92b9e32d15825983f0">SplitterFloat16Test</a></div><div class="ttdeci">std::vector< LayerTestResult< armnn::Half, 3 > > SplitterFloat16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00333">SplitterTestImpl.cpp:333</a></div></div>
<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_a432bea508d3e2565091bb27aacb883ff"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a432bea508d3e2565091bb27aacb883ff">CopyViaSplitterInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 3 > CopyViaSplitterInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00393">SplitterTestImpl.cpp:393</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="classarmnn_1_1_i_tensor_handle_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00041">ITensorHandleFactory.hpp:41</a></div></div>
<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_a0fa291bb2b9b182a286e600a3b990c16"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a0fa291bb2b9b182a286e600a3b990c16">SplitterInt16Test</a></div><div class="ttdeci">std::vector< LayerTestResult< int16_t, 3 > > SplitterInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00349">SplitterTestImpl.cpp:349</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#l00030">LayerTestResult.hpp:30</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div>
<div class="ttc" id="_splitter_test_impl_8cpp_xhtml_a1ff233f3179fa9ce3a80ae456bbb9e8b"><div class="ttname"><a href="_splitter_test_impl_8cpp.xhtml#a1ff233f3179fa9ce3a80ae456bbb9e8b">CopyViaSplitterFloat16Test</a></div><div class="ttdeci">LayerTestResult< armnn::Half, 3 > CopyViaSplitterFloat16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_splitter_test_impl_8cpp_source.xhtml#l00369">SplitterTestImpl.cpp:369</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><!-- 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 Thu Feb 25 2021 17:27:51 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>
|
