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diff --git a/20.02/_reshape_test_impl_8hpp.xhtml b/20.02/_reshape_test_impl_8hpp.xhtml new file mode 100644 index 0000000000..b42f8f3c6b --- /dev/null +++ b/20.02/_reshape_test_impl_8hpp.xhtml @@ -0,0 +1,200 @@ +<!-- 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/ReshapeTestImpl.hpp File Reference</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script 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+<div class="title">ReshapeTestImpl.hpp File Reference</div> </div> +</div><!--header--> +<div class="contents"> +<div class="textblock"><code>#include "<a class="el" href="_layer_test_result_8hpp_source.xhtml">LayerTestResult.hpp</a>"</code><br /> +<code>#include <<a class="el" href="_resolve_type_8hpp_source.xhtml">ResolveType.hpp</a>></code><br /> +<code>#include <<a class="el" href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.xhtml">armnn/backends/IBackendInternal.hpp</a>></code><br /> +<code>#include <<a class="el" href="_workload_factory_8hpp_source.xhtml">backendsCommon/WorkloadFactory.hpp</a>></code><br /> +</div> +<p><a href="_reshape_test_impl_8hpp_source.xhtml">Go to the source code of this file.</a></p> +<table class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> +Functions</h2></td></tr> +<tr class="memitem:a27e70e33db384629f46baac2b95a71cd"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> +<tr class="memitem:a27e70e33db384629f46baac2b95a71cd"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_reshape_test_impl_8hpp.xhtml#a27e70e33db384629f46baac2b95a71cd">SimpleReshapeTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> +<tr class="separator:a27e70e33db384629f46baac2b95a71cd"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a75b012fe56435f53e13fd8ab123aef9c"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> +<tr class="memitem:a75b012fe56435f53e13fd8ab123aef9c"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 5 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_reshape_test_impl_8hpp.xhtml#a75b012fe56435f53e13fd8ab123aef9c">Reshape5dTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> +<tr class="separator:a75b012fe56435f53e13fd8ab123aef9c"><td class="memSeparator" colspan="2"> </td></tr> +</table> +<h2 class="groupheader">Function Documentation</h2> +<a id="a75b012fe56435f53e13fd8ab123aef9c"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a75b012fe56435f53e13fd8ab123aef9c">◆ </a></span>Reshape5dTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 5> Reshape5dTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_reshape_test_impl_8cpp_source.xhtml#l00109">109</a> of file <a class="el" href="_reshape_test_impl_8cpp_source.xhtml">ReshapeTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_8cpp_source.xhtml#l00259">TensorInfo::SetQuantizationScale()</a>.</p> +<div class="fragment"><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> </div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 2, 2, 8, 1, 1 };</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 2, 2, 2, 2, 2 };</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>  inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(5, inputShape, ArmnnType);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(1.0f);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(5, outputShape, ArmnnType);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(1.0f);</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">auto</span> input = ConvertToDataType<ArmnnType>(</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  {</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  0.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  24.0f, 25.0f, 26.0f, 27.0f, 28.0f, 29.0f, 30.0f, 31.0f,</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>  inputTensorInfo);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keyword">auto</span> outputExpected = ConvertToDataType<ArmnnType>(</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  0.0f, 1.0f,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  2.0f, 3.0f,</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>  4.0f, 5.0f,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  6.0f, 7.0f,</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> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  8.0f, 9.0f,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  10.0f, 11.0f,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> </div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  12.0f, 13.0f,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  14.0f, 15.0f,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> </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>  16.0f, 17.0f,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  18.0f, 19.0f,</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>  20.0f, 21.0f,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  22.0f, 23.0f,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  24.0f, 25.0f,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  26.0f, 27.0f,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  28.0f, 29.0f,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  30.0f, 31.0f,</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>  outputTensorInfo);</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>  <span class="keywordflow">return</span> SimpleReshapeTestImpl<T, 5>(</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected);</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> }</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="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><!-- fragment --> +</div> +</div> +<a id="a27e70e33db384629f46baac2b95a71cd"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a27e70e33db384629f46baac2b95a71cd">◆ </a></span>SimpleReshapeTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> SimpleReshapeTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_reshape_test_impl_8cpp_source.xhtml#l00057">57</a> of file <a class="el" href="_reshape_test_impl_8cpp_source.xhtml">ReshapeTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_8cpp_source.xhtml#l00259">TensorInfo::SetQuantizationScale()</a>.</p> +<div class="fragment"><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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { 2, 2, 3, 3 };</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { 2, 2, 9, 1 };</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, inputShape, ArmnnType);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(1.0f);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, outputShape, ArmnnType);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(1.0f);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">auto</span> input = ConvertToDataType<ArmnnType>(</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  0.0f, 1.0f, 2.0f,</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  6.0f, 7.0f, 8.0f,</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>  9.0f, 10.0f, 11.0f,</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  12.0f, 13.0f, 14.0f,</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  15.0f, 16.0f, 17.0f,</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>  18.0f, 19.0f, 20.0f,</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  21.0f, 22.0f, 23.0f,</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  24.0f, 25.0f, 26.0f,</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  27.0f, 28.0f, 29.0f,</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  30.0f, 31.0f, 32.0f,</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  33.0f, 34.0f, 35.0f,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  },</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  inputTensorInfo);</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>  <span class="keyword">auto</span> outputExpected = ConvertToDataType<ArmnnType>(</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  {</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  0.0f, 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f,</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f,</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>  18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f, 25.0f, 26.0f,</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  27.0f, 28.0f, 29.0f, 30.0f, 31.0f, 32.0f, 33.0f, 34.0f, 35.0f,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  },</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  outputTensorInfo);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> </div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordflow">return</span> SimpleReshapeTestImpl<T, 4>(</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> }</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="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><!-- fragment --> +</div> +</div> +</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="_reshape_test_impl_8hpp.xhtml">ReshapeTestImpl.hpp</a></li> + <li class="footer">Generated on Fri Mar 13 2020 16:09:15 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> |