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86<div class="title">AdditionTestImpl.cpp File Reference</div> </div>
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89<div class="textblock"><code>#include &quot;<a class="el" href="_addition_test_impl_8hpp_source.html">AdditionTestImpl.hpp</a>&quot;</code><br />
90<code>#include &quot;<a class="el" href="_elementwise_test_impl_8hpp_source.html">ElementwiseTestImpl.hpp</a>&quot;</code><br />
91<code>#include &lt;<a class="el" href="_quantize_helper_8hpp_source.html">QuantizeHelper.hpp</a>&gt;</code><br />
92</div>
93<p><a href="_addition_test_impl_8cpp_source.html">Go to the source code of this file.</a></p>
94<table class="memberdecls">
95<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
96Functions</h2></td></tr>
97<tr class="memitem:a5f3caae0b1541a904067544dd37655f0"><td class="memTemplParams" colspan="2">template&lt;&gt; </td></tr>
98<tr class="memitem:a5f3caae0b1541a904067544dd37655f0"><td class="memTemplItemLeft" align="right" valign="top">std::unique_ptr&lt; <a class="el" href="classarmnn_1_1_i_workload.html">armnn::IWorkload</a> &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#a5f3caae0b1541a904067544dd37655f0">CreateWorkload&lt; armnn::AdditionQueueDescriptor &gt;</a> (const <a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> &amp;info, const <a class="el" href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a> &amp;descriptor)</td></tr>
99<tr class="separator:a5f3caae0b1541a904067544dd37655f0"><td class="memSeparator" colspan="2">&#160;</td></tr>
100<tr class="memitem:a108165b4957f3790332ae0afedf37ccd"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; float, 4 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#a108165b4957f3790332ae0afedf37ccd">AdditionTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager)</td></tr>
101<tr class="separator:a108165b4957f3790332ae0afedf37ccd"><td class="memSeparator" colspan="2">&#160;</td></tr>
102<tr class="memitem:ab102e5bc3a3b04360a0f42e25ab3c898"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; float, 5 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#ab102e5bc3a3b04360a0f42e25ab3c898">Addition5dTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager)</td></tr>
103<tr class="separator:ab102e5bc3a3b04360a0f42e25ab3c898"><td class="memSeparator" colspan="2">&#160;</td></tr>
104<tr class="memitem:add789f43d728a34fccf9aea235179342"><td class="memTemplParams" colspan="2">template&lt;armnn::DataType ArmnnType, typename T = armnn::ResolveType&lt;ArmnnType&gt;&gt; </td></tr>
105<tr class="memitem:add789f43d728a34fccf9aea235179342"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; T, 4 &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#add789f43d728a34fccf9aea235179342">AdditionBroadcastTestImpl</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, float qScale, int32_t qOffset)</td></tr>
106<tr class="separator:add789f43d728a34fccf9aea235179342"><td class="memSeparator" colspan="2">&#160;</td></tr>
107<tr class="memitem:ad6a320dc43ad2384cf2d7288cf9c0823"><td class="memTemplParams" colspan="2">template&lt;armnn::DataType ArmnnType, typename T = armnn::ResolveType&lt;ArmnnType&gt;&gt; </td></tr>
108<tr class="memitem:ad6a320dc43ad2384cf2d7288cf9c0823"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; T, 4 &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#ad6a320dc43ad2384cf2d7288cf9c0823">AdditionBroadcast1ElementTestImpl</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, float qScale, int32_t qOffset)</td></tr>
109<tr class="separator:ad6a320dc43ad2384cf2d7288cf9c0823"><td class="memSeparator" colspan="2">&#160;</td></tr>
110<tr class="memitem:a9591268a5a6c7d0a0b91098deab4fe34"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; float, 4 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#a9591268a5a6c7d0a0b91098deab4fe34">AdditionBroadcastTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager)</td></tr>
111<tr class="separator:a9591268a5a6c7d0a0b91098deab4fe34"><td class="memSeparator" colspan="2">&#160;</td></tr>
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113<tr class="separator:a0946a9b1b8cf99591b03ea7f5f7e725f"><td class="memSeparator" colspan="2">&#160;</td></tr>
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117<tr class="separator:a4bff97bff3f9fb4cf473812dee810de0"><td class="memSeparator" colspan="2">&#160;</td></tr>
118<tr class="memitem:ad71ffd0e8547900b92a5d471f01cd69b"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; uint8_t, 4 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#ad71ffd0e8547900b92a5d471f01cd69b">AdditionBroadcast1ElementUint8Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager)</td></tr>
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122<tr class="memitem:a4b5e20456506426ba2e4ea9616df978f"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; uint8_t, 4 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#a4b5e20456506426ba2e4ea9616df978f">AdditionUint8Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager)</td></tr>
123<tr class="separator:a4b5e20456506426ba2e4ea9616df978f"><td class="memSeparator" colspan="2">&#160;</td></tr>
124<tr class="memitem:ae087613cdb8319fbab07d44e6eaf217d"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; int16_t, 4 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#ae087613cdb8319fbab07d44e6eaf217d">AdditionInt16Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager)</td></tr>
125<tr class="separator:ae087613cdb8319fbab07d44e6eaf217d"><td class="memSeparator" colspan="2">&#160;</td></tr>
126<tr class="memitem:aa11fe3b8a07854e2bb9dd3ccecaa96e4"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; float, 4 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#aa11fe3b8a07854e2bb9dd3ccecaa96e4">AdditionAfterMaxPoolTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager)</td></tr>
127<tr class="separator:aa11fe3b8a07854e2bb9dd3ccecaa96e4"><td class="memSeparator" colspan="2">&#160;</td></tr>
128<tr class="memitem:a557c464592942eb098f63aa0f91e4d24"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt; float, 4 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_addition_test_impl_8cpp.html#a557c464592942eb098f63aa0f91e4d24">CompareAdditionTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, <a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;refWorkloadFactory)</td></tr>
129<tr class="separator:a557c464592942eb098f63aa0f91e4d24"><td class="memSeparator" colspan="2">&#160;</td></tr>
130</table>
131<h2 class="groupheader">Function Documentation</h2>
132<a id="ab102e5bc3a3b04360a0f42e25ab3c898"></a>
133<h2 class="memtitle"><span class="permalink"><a href="#ab102e5bc3a3b04360a0f42e25ab3c898">&#9670;&nbsp;</a></span>Addition5dTest()</h2>
134
135<div class="memitem">
136<div class="memproto">
137 <table class="memname">
138 <tr>
139 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;float, 5&gt; Addition5dTest </td>
140 <td>(</td>
141 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
142 <td class="paramname"><em>workloadFactory</em>, </td>
143 </tr>
144 <tr>
145 <td class="paramkey"></td>
146 <td></td>
147 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
148 <td class="paramname"><em>memoryManager</em>&#160;</td>
149 </tr>
150 <tr>
151 <td></td>
152 <td>)</td>
153 <td></td><td></td>
154 </tr>
155 </table>
156</div><div class="memdoc">
157
158<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00089">89</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
159<div class="fragment"><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160;{</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depth = 2u;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 2u;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 2u;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 2u;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = 3u;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160;</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = { depth, batchSize, channels, height, width };</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; std::vector&lt;float&gt; input1 =</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; {</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; 2.6f, 4.0f, 4.4f, 2.7f, 4.6f, 2.8f,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; 2.3f, 1.9f, 3.4f, 2.9f, 2.2f, 4.5f,</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; 2.8f, 1.9f, 2.3f, 2.6f, 4.7f, 3.5f,</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; 0.4f, 1.5f, 2.1f, 0.7f, 5.0f, 1.1f,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; 1.0f, 2.7f, 0.0f, 0.6f, 0.8f, 0.9f,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; 1.0f, 2.6f, 0.4f, 3.8f, 0.4f, 0.8f,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; 0.5f, 4.3f, 3.1f, 4.4f, 0.7f, 1.4f,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; 0.4f, 4.4f, 0.7f, 0.6f, 4.7f, 1.2f,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; };</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160;</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; std::vector&lt;float&gt; input2 =</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; {</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; 4.4f, 3.0f, 1.0f, 0.0f, 3.9f, 3.1f,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; 1.7f, 2.9f, 1.3f, 0.4f, 0.4f, 4.3f,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; 4.5f, 0.2f, 2.2f, 4.1f, 3.9f, 3.0f,</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; 0.1f, 2.5f, 4.1f, 4.6f, 1.5f, 0.0f,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; 0.5f, 4.9f, 2.5f, 1.5f, 3.4f, 4.5f,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; 2.0f, 3.0f, 4.9f, 1.6f, 2.4f, 3.4f,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; 3.6f, 1.8f, 1.3f, 2.6f, 2.1f, 4.8f,</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; 2.0f, 4.3f, 4.0f, 0.2f, 0.6f, 4.4f,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; };</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; std::vector&lt;float&gt; output =</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; 7.0f, 7.0f, 5.4f, 2.7f, 8.5f, 5.9f,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; 4.0f, 4.8f, 4.7f, 3.3f, 2.6f, 8.8f,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; 7.3f, 2.1f, 4.5f, 6.7f, 8.6f, 6.5f,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; 0.5f, 4.0f, 6.2f, 5.3f, 6.5f, 1.1f,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160;</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; 1.5f, 7.6f, 2.5f, 2.1f, 4.2f, 5.4f,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; 3.0f, 5.6f, 5.3f, 5.4f, 2.8f, 4.2f,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160;</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; 4.1f, 6.1f, 4.4f, 7.0f, 2.8f, 6.2f,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; 2.4f, 8.7f, 4.7f, 0.8f, 5.3f, 5.6f,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; };</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <span class="keywordflow">return</span> ElementwiseTestHelper&lt;5, armnn::AdditionQueueDescriptor, armnn::DataType::Float32&gt;(</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; workloadFactory,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; memoryManager,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; shape,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; input1,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; shape,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; input2,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; shape,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; output);</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160;}</div></div><!-- fragment -->
160</div>
161</div>
162<a id="aa11fe3b8a07854e2bb9dd3ccecaa96e4"></a>
163<h2 class="memtitle"><span class="permalink"><a href="#aa11fe3b8a07854e2bb9dd3ccecaa96e4">&#9670;&nbsp;</a></span>AdditionAfterMaxPoolTest()</h2>
164
165<div class="memitem">
166<div class="memproto">
167 <table class="memname">
168 <tr>
169 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;float, 4&gt; AdditionAfterMaxPoolTest </td>
170 <td>(</td>
171 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
172 <td class="paramname"><em>workloadFactory</em>, </td>
173 </tr>
174 <tr>
175 <td class="paramkey"></td>
176 <td></td>
177 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
178 <td class="paramname"><em>memoryManager</em>&#160;</td>
179 </tr>
180 <tr>
181 <td></td>
182 <td>)</td>
183 <td></td><td></td>
184 </tr>
185 </table>
186</div><div class="memdoc">
187
188<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00454">454</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
189
190<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.html#l01088">IWorkloadFactory::CreateAddition()</a>, <a class="el" href="_workload_factory_8cpp_source.html#l01323">IWorkloadFactory::CreatePooling2d()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_workload_data_8hpp_source.html#l00049">QueueDescriptorWithParameters&lt; LayerDescriptor &gt;::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.html#l00359">Pooling2dDescriptor::m_PoolHeight</a>, <a class="el" href="_descriptors_8hpp_source.html#l00347">Pooling2dDescriptor::m_PoolType</a>, <a class="el" href="_descriptors_8hpp_source.html#l00357">Pooling2dDescriptor::m_PoolWidth</a>, <a class="el" href="_descriptors_8hpp_source.html#l00361">Pooling2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.html#l00363">Pooling2dDescriptor::m_StrideY</a>, and <a class="el" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::Max</a>.</p>
191
192<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.html#l01057">BOOST_AUTO_TEST_CASE()</a>.</p>
193<div class="fragment"><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>&#160;{</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>&#160; boost::ignore_unused(memoryManager);</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>&#160;</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>&#160; <span class="comment">// Create Initial Tensor</span></div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>&#160; <span class="comment">// 1, 2, 3</span></div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>&#160; <span class="comment">// 4, 5, 6</span></div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>&#160; <span class="comment">// 7, 8, 9</span></div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>&#160;</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> poolingInputTensorInfo({ 1, 1, 3, 3}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> poolingOutputTensorInfo({ 1, 1, 2, 2}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>&#160;</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>&#160; boost::multi_array&lt;float, 4&gt; poolingInput = MakeTensor&lt;float,4&gt;(poolingInputTensorInfo,</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>&#160; {1, 2, 3,</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>&#160; 4, 5, 6,</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>&#160; 7, 8, 9</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>&#160; });</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>&#160;</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; poolingInputHandle =</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>&#160; workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(poolingInputTensorInfo);</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; poolingOutputHandle =</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>&#160; workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(poolingOutputTensorInfo);</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>&#160;</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>&#160; <span class="comment">// Apply MaxPool poolSize = 1x1, stride=2x2</span></div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>&#160; <span class="comment">// Result =</span></div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>&#160; <span class="comment">// 1, 3</span></div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>&#160; <span class="comment">// 7, 9</span></div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a> descriptor;</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">m_PoolHeight</a> = 1;</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">m_PoolWidth</a> = 1;</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">m_PoolType</a> = <a class="code" href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::PoolingAlgorithm::Max</a>;</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>&#160;</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>&#160; <a class="code" href="structarmnn_1_1_pooling2d_queue_descriptor.html">armnn::Pooling2dQueueDescriptor</a> queueDescriptor;</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>&#160; queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a> = descriptor;</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>&#160; AddInputToWorkload(queueDescriptor, workloadInfo, poolingInputTensorInfo, poolingInputHandle.get());</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>&#160; AddOutputToWorkload(queueDescriptor, workloadInfo, poolingOutputTensorInfo, poolingOutputHandle.get());</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>&#160;</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>&#160; <span class="comment">// Create the MaxPool</span></div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a6e95afd9a55700cbf6f9e8db8089f2f2">CreatePooling2d</a>(queueDescriptor, workloadInfo);</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>&#160;</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>&#160; 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<span class="comment">// with the initial tensor.</span></div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>&#160; <span class="comment">// 12, 16</span></div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>&#160; <span class="comment">// 24, 28</span></div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>&#160;</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> addInputTensorInfo({ 1,1,2,2}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> addOutputTensorInfo({ 1,1,2,2}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>&#160;</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>&#160; boost::multi_array&lt;float, 4&gt; addInput = MakeTensor&lt;float,4&gt;(addInputTensorInfo,</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>&#160; {12, 16,</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>&#160; 24, 28,</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>&#160; });</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>&#160;</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>&#160; <span class="comment">// Expected output tensor after MaxPool and Addition.</span></div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>&#160; <a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float,4&gt;</a> addRet(addOutputTensorInfo);</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>&#160; addRet.outputExpected = MakeTensor&lt;float, 4&gt;(addOutputTensorInfo, std::vector&lt;float&gt;(</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>&#160; {</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>&#160; 13, 19,</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>&#160; 31, 37</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>&#160; }));</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>&#160;</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; addInputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(addInputTensorInfo);</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; addOutputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(addOutputTensorInfo);</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>&#160;</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>&#160; <a class="code" href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a> data;</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>&#160;</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>&#160; <span class="comment">// Add the output of the MaxPool and the new tensor</span></div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>&#160; AddInputToWorkload(data, info, poolingOutputTensorInfo, poolingOutputHandle.get());</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>&#160; AddInputToWorkload(data, info, addInputTensorInfo, addInputHandle.get());</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>&#160; AddOutputToWorkload(data, info, addOutputTensorInfo, addOutputHandle.get());</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>&#160;</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; addWorkload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(data, info);</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>&#160;</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>&#160; poolingInputHandle-&gt;Allocate();</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>&#160; poolingOutputHandle-&gt;Allocate();</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>&#160; addInputHandle-&gt;Allocate();</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>&#160; addOutputHandle-&gt;Allocate();</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>&#160;</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(poolingInputHandle.get(), &amp;poolingInput[0][0][0][0]);</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;resultMaxPool[0][0][0][0], poolingOutputHandle.get());</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>&#160;</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(poolingOutputHandle.get(), &amp;resultMaxPool[0][0][0][0]);</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(addInputHandle.get(), &amp;addInput[0][0][0][0]);</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>&#160;</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>&#160; workload-&gt;PostAllocationConfigure();</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>&#160; workload-&gt;Execute();</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>&#160; addWorkload-&gt;PostAllocationConfigure();</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>&#160; addWorkload-&gt;Execute();</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>&#160;</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;addRet.output[0][0][0][0], addOutputHandle.get());</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>&#160;</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>&#160; <span class="keywordflow">return</span> addRet;</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>&#160;}</div><div class="ttc" id="namespacearmnn_html_ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.html#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::ArgMinMaxFunction::Max</a></div></div>
194<div class="ttc" id="_tensor_copy_utils_8cpp_html_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#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.html#l00009">TensorCopyUtils.cpp:9</a></div></div>
195<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a5699e8606c37d18c03910b242cd1b010"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a5699e8606c37d18c03910b242cd1b010">armnn::Pooling2dDescriptor::m_PoolHeight</a></div><div class="ttdeci">uint32_t m_PoolHeight</div><div class="ttdoc">Pooling height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00359">Descriptors.hpp:359</a></div></div>
196<div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
197<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_html_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.html#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00049">WorkloadData.hpp:49</a></div></div>
198<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
199<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr&lt; ITensorHandle &gt; CreateTensorHandle(const TensorInfo &amp;tensorInfo, const bool IsMemoryManaged=true) const =0</div></div>
200<div class="ttc" id="struct_layer_test_result_html"><div class="ttname"><a href="struct_layer_test_result.html">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.html#l00029">LayerTestResult.hpp:29</a></div></div>
201<div class="ttc" id="_tensor_copy_utils_8cpp_html_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#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.html#l00014">TensorCopyUtils.cpp:14</a></div></div>
202<div class="ttc" id="structarmnn_1_1_workload_info_html"><div class="ttname"><a href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.html#l00016">WorkloadInfo.hpp:16</a></div></div>
203<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
204<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a6d8fb685cc1ff224f25aa127fcf62c86"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a6d8fb685cc1ff224f25aa127fcf62c86">armnn::Pooling2dDescriptor::m_PoolWidth</a></div><div class="ttdeci">uint32_t m_PoolWidth</div><div class="ttdoc">Pooling width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00357">Descriptors.hpp:357</a></div></div>
205<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a6e95afd9a55700cbf6f9e8db8089f2f2"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a6e95afd9a55700cbf6f9e8db8089f2f2">armnn::IWorkloadFactory::CreatePooling2d</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreatePooling2d(const Pooling2dQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01323">WorkloadFactory.cpp:1323</a></div></div>
206<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateAddition(const AdditionQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01088">WorkloadFactory.cpp:1088</a></div></div>
207<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Pooling2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00363">Descriptors.hpp:363</a></div></div>
208<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_a0031997bf43bd2747656c31e4977793a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#a0031997bf43bd2747656c31e4977793a">armnn::Pooling2dDescriptor::m_PoolType</a></div><div class="ttdeci">PoolingAlgorithm m_PoolType</div><div class="ttdoc">The pooling algorithm to use (Max. Average, L2). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00347">Descriptors.hpp:347</a></div></div>
209<div class="ttc" id="structarmnn_1_1_addition_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00216">WorkloadData.hpp:216</a></div></div>
210<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00313">Descriptors.hpp:313</a></div></div>
211<div class="ttc" id="structarmnn_1_1_pooling2d_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_pooling2d_queue_descriptor.html">armnn::Pooling2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00162">WorkloadData.hpp:162</a></div></div>
212<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Pooling2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00361">Descriptors.hpp:361</a></div></div>
213</div><!-- fragment -->
214</div>
215</div>
216<a id="a97579bb78890452730fff4d1e3e6fb4a"></a>
217<h2 class="memtitle"><span class="permalink"><a href="#a97579bb78890452730fff4d1e3e6fb4a">&#9670;&nbsp;</a></span>AdditionBroadcast1ElementInt16Test()</h2>
218
219<div class="memitem">
220<div class="memproto">
221 <table class="memname">
222 <tr>
223 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;int16_t, 4&gt; AdditionBroadcast1ElementInt16Test </td>
224 <td>(</td>
225 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
226 <td class="paramname"><em>workloadFactory</em>, </td>
227 </tr>
228 <tr>
229 <td class="paramkey"></td>
230 <td></td>
231 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
232 <td class="paramname"><em>memoryManager</em>&#160;</td>
233 </tr>
234 <tr>
235 <td></td>
236 <td>)</td>
237 <td></td><td></td>
238 </tr>
239 </table>
240</div><div class="memdoc">
241
242<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00362">362</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
243<div class="fragment"><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>&#160;{</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>&#160; <span class="keywordflow">return</span> AdditionBroadcast1ElementTestImpl&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>&#160; workloadFactory, memoryManager, 0.1333333f, 0);</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>&#160;}</div></div><!-- fragment -->
244</div>
245</div>
246<a id="a4bff97bff3f9fb4cf473812dee810de0"></a>
247<h2 class="memtitle"><span class="permalink"><a href="#a4bff97bff3f9fb4cf473812dee810de0">&#9670;&nbsp;</a></span>AdditionBroadcast1ElementTest()</h2>
248
249<div class="memitem">
250<div class="memproto">
251 <table class="memname">
252 <tr>
253 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;float, 4&gt; AdditionBroadcast1ElementTest </td>
254 <td>(</td>
255 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
256 <td class="paramname"><em>workloadFactory</em>, </td>
257 </tr>
258 <tr>
259 <td class="paramkey"></td>
260 <td></td>
261 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
262 <td class="paramname"><em>memoryManager</em>&#160;</td>
263 </tr>
264 <tr>
265 <td></td>
266 <td>)</td>
267 <td></td><td></td>
268 </tr>
269 </table>
270</div><div class="memdoc">
271
272<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00346">346</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
273<div class="fragment"><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160;{</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160; <span class="keywordflow">return</span> AdditionBroadcast1ElementTestImpl&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>&#160; workloadFactory, memoryManager, 0.0f, 0);</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>&#160;}</div></div><!-- fragment -->
274</div>
275</div>
276<a id="ad6a320dc43ad2384cf2d7288cf9c0823"></a>
277<h2 class="memtitle"><span class="permalink"><a href="#ad6a320dc43ad2384cf2d7288cf9c0823">&#9670;&nbsp;</a></span>AdditionBroadcast1ElementTestImpl()</h2>
278
279<div class="memitem">
280<div class="memproto">
281 <table class="memname">
282 <tr>
283 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;T, 4&gt; AdditionBroadcast1ElementTestImpl </td>
284 <td>(</td>
285 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
286 <td class="paramname"><em>workloadFactory</em>, </td>
287 </tr>
288 <tr>
289 <td class="paramkey"></td>
290 <td></td>
291 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
292 <td class="paramname"><em>memoryManager</em>, </td>
293 </tr>
294 <tr>
295 <td class="paramkey"></td>
296 <td></td>
297 <td class="paramtype">float&#160;</td>
298 <td class="paramname"><em>qScale</em>, </td>
299 </tr>
300 <tr>
301 <td class="paramkey"></td>
302 <td></td>
303 <td class="paramtype">int32_t&#160;</td>
304 <td class="paramname"><em>qOffset</em>&#160;</td>
305 </tr>
306 <tr>
307 <td></td>
308 <td>)</td>
309 <td></td><td></td>
310 </tr>
311 </table>
312</div><div class="memdoc">
313
314<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00245">245</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
315
316<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.html#l01088">IWorkloadFactory::CreateAddition()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="_layer_test_result_8hpp_source.html#l00040">LayerTestResult&lt; T, n &gt;::output</a>, <a class="el" href="_layer_test_result_8hpp_source.html#l00041">LayerTestResult&lt; T, n &gt;::outputExpected</a>, <a class="el" href="_tensor_8cpp_source.html#l00275">TensorInfo::SetQuantizationOffset()</a>, and <a class="el" href="_tensor_8cpp_source.html#l00259">TensorInfo::SetQuantizationScale()</a>.</p>
317<div class="fragment"><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160;{</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160; boost::ignore_unused(memoryManager);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo1 = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({1, 3, 2, 3}, ArmnnType);</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo2 = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({1, 1, 1, 1}, ArmnnType);</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({1, 3, 2, 3}, ArmnnType);</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160;</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; <span class="keywordflow">if</span> (armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; {</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; inputTensorInfo1.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; inputTensorInfo1.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; inputTensorInfo2.SetQuantizationScale(qScale);</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; inputTensorInfo2.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; outputTensorInfo.SetQuantizationScale(qScale);</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; outputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; }</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160;</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; <span class="keyword">auto</span> input1 = MakeTensor&lt;T, 4&gt;(inputTensorInfo1, armnnUtils::QuantizedVector&lt;T&gt;(</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; {</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; 0.0f, 1.0f, 2.0f,</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; 3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; 6.0f, 7.0f, 8.0f,</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; 9.0f, 10.0f, 11.0f,</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; 12.0f, 13.0f, 14.0f,</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; 15.0f, 16.0f, 17.0f,</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>&#160; },</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160;</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160; <span class="keyword">auto</span> input2 = MakeTensor&lt;T, 4&gt;(inputTensorInfo2, armnnUtils::QuantizedVector&lt;T&gt;(</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; {</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; 0.5f,</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; },</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160;</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; <a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T,4&gt;</a> ret(outputTensorInfo);</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; ret.outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo, armnnUtils::QuantizedVector&lt;T&gt;(</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; {</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; 0.5f, 1.5f, 2.5f,</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; 3.5f, 4.5f, 5.5f,</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; 6.5f, 7.5f, 8.5f,</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; 9.5f, 10.5f, 11.5f,</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; 12.5f, 13.5f, 14.5f,</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; 15.5f, 16.5f, 17.5f,</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; },</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160;</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle1 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo1);</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle2 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo2);</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160;</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; <a class="code" href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a> data;</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get());</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get());</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(data, info);</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160;</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; inputHandle1-&gt;Allocate();</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; inputHandle2-&gt;Allocate();</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; outputHandle-&gt;Allocate();</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160;</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle1.get(), &amp;input1[0][0][0][0]);</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle2.get(), &amp;input2[0][0][0][0]);</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160;</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160; workload-&gt;PostAllocationConfigure();</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; workload-&gt;Execute();</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160;</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;ret.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160;</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160; <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160;}</div><div class="ttc" id="_tensor_copy_utils_8cpp_html_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#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.html#l00009">TensorCopyUtils.cpp:9</a></div></div>
318<div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
319<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
320<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr&lt; ITensorHandle &gt; CreateTensorHandle(const TensorInfo &amp;tensorInfo, const bool IsMemoryManaged=true) const =0</div></div>
321<div class="ttc" id="struct_layer_test_result_html"><div class="ttname"><a href="struct_layer_test_result.html">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.html#l00029">LayerTestResult.hpp:29</a></div></div>
322<div class="ttc" id="_tensor_copy_utils_8cpp_html_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#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.html#l00014">TensorCopyUtils.cpp:14</a></div></div>
323<div class="ttc" id="structarmnn_1_1_workload_info_html"><div class="ttname"><a href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.html#l00016">WorkloadInfo.hpp:16</a></div></div>
324<div class="ttc" id="classarmnn_1_1_tensor_info_html_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#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.html#l00259">Tensor.cpp:259</a></div></div>
325<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateAddition(const AdditionQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01088">WorkloadFactory.cpp:1088</a></div></div>
326<div class="ttc" id="structarmnn_1_1_addition_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00216">WorkloadData.hpp:216</a></div></div>
327<div class="ttc" id="classarmnn_1_1_tensor_info_html_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00275">Tensor.cpp:275</a></div></div>
328</div><!-- fragment -->
329</div>
330</div>
331<a id="ad71ffd0e8547900b92a5d471f01cd69b"></a>
332<h2 class="memtitle"><span class="permalink"><a href="#ad71ffd0e8547900b92a5d471f01cd69b">&#9670;&nbsp;</a></span>AdditionBroadcast1ElementUint8Test()</h2>
333
334<div class="memitem">
335<div class="memproto">
336 <table class="memname">
337 <tr>
338 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;uint8_t, 4&gt; AdditionBroadcast1ElementUint8Test </td>
339 <td>(</td>
340 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
341 <td class="paramname"><em>workloadFactory</em>, </td>
342 </tr>
343 <tr>
344 <td class="paramkey"></td>
345 <td></td>
346 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
347 <td class="paramname"><em>memoryManager</em>&#160;</td>
348 </tr>
349 <tr>
350 <td></td>
351 <td>)</td>
352 <td></td><td></td>
353 </tr>
354 </table>
355</div><div class="memdoc">
356
357<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00354">354</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
358<div class="fragment"><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>&#160;{</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>&#160; <span class="keywordflow">return</span> AdditionBroadcast1ElementTestImpl&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>&#160; workloadFactory, memoryManager, 0.1333333f, 128);</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>&#160;}</div></div><!-- fragment -->
359</div>
360</div>
361<a id="a470ed90260ed36c02adc91df184fcc82"></a>
362<h2 class="memtitle"><span class="permalink"><a href="#a470ed90260ed36c02adc91df184fcc82">&#9670;&nbsp;</a></span>AdditionBroadcastInt16Test()</h2>
363
364<div class="memitem">
365<div class="memproto">
366 <table class="memname">
367 <tr>
368 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;int16_t, 4&gt; AdditionBroadcastInt16Test </td>
369 <td>(</td>
370 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
371 <td class="paramname"><em>workloadFactory</em>, </td>
372 </tr>
373 <tr>
374 <td class="paramkey"></td>
375 <td></td>
376 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
377 <td class="paramname"><em>memoryManager</em>&#160;</td>
378 </tr>
379 <tr>
380 <td></td>
381 <td>)</td>
382 <td></td><td></td>
383 </tr>
384 </table>
385</div><div class="memdoc">
386
387<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00338">338</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
388<div class="fragment"><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160;{</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; <span class="keywordflow">return</span> AdditionBroadcastTestImpl&lt;armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; workloadFactory, memoryManager, 2.f, 0);</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160;}</div></div><!-- fragment -->
389</div>
390</div>
391<a id="a9591268a5a6c7d0a0b91098deab4fe34"></a>
392<h2 class="memtitle"><span class="permalink"><a href="#a9591268a5a6c7d0a0b91098deab4fe34">&#9670;&nbsp;</a></span>AdditionBroadcastTest()</h2>
393
394<div class="memitem">
395<div class="memproto">
396 <table class="memname">
397 <tr>
398 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;float, 4&gt; AdditionBroadcastTest </td>
399 <td>(</td>
400 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
401 <td class="paramname"><em>workloadFactory</em>, </td>
402 </tr>
403 <tr>
404 <td class="paramkey"></td>
405 <td></td>
406 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
407 <td class="paramname"><em>memoryManager</em>&#160;</td>
408 </tr>
409 <tr>
410 <td></td>
411 <td>)</td>
412 <td></td><td></td>
413 </tr>
414 </table>
415</div><div class="memdoc">
416
417<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00322">322</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
418<div class="fragment"><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160;{</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160; <span class="keywordflow">return</span> AdditionBroadcastTestImpl&lt;armnn::DataType::Float32&gt;(</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; workloadFactory, memoryManager, 0.0f, 0);</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160;}</div></div><!-- fragment -->
419</div>
420</div>
421<a id="add789f43d728a34fccf9aea235179342"></a>
422<h2 class="memtitle"><span class="permalink"><a href="#add789f43d728a34fccf9aea235179342">&#9670;&nbsp;</a></span>AdditionBroadcastTestImpl()</h2>
423
424<div class="memitem">
425<div class="memproto">
426 <table class="memname">
427 <tr>
428 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;T, 4&gt; AdditionBroadcastTestImpl </td>
429 <td>(</td>
430 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
431 <td class="paramname"><em>workloadFactory</em>, </td>
432 </tr>
433 <tr>
434 <td class="paramkey"></td>
435 <td></td>
436 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
437 <td class="paramname"><em>memoryManager</em>, </td>
438 </tr>
439 <tr>
440 <td class="paramkey"></td>
441 <td></td>
442 <td class="paramtype">float&#160;</td>
443 <td class="paramname"><em>qScale</em>, </td>
444 </tr>
445 <tr>
446 <td class="paramkey"></td>
447 <td></td>
448 <td class="paramtype">int32_t&#160;</td>
449 <td class="paramname"><em>qOffset</em>&#160;</td>
450 </tr>
451 <tr>
452 <td></td>
453 <td>)</td>
454 <td></td><td></td>
455 </tr>
456 </table>
457</div><div class="memdoc">
458
459<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00162">162</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
460
461<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.html#l01088">IWorkloadFactory::CreateAddition()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="_layer_test_result_8hpp_source.html#l00040">LayerTestResult&lt; T, n &gt;::output</a>, <a class="el" href="_layer_test_result_8hpp_source.html#l00041">LayerTestResult&lt; T, n &gt;::outputExpected</a>, <a class="el" href="_tensor_8cpp_source.html#l00275">TensorInfo::SetQuantizationOffset()</a>, and <a class="el" href="_tensor_8cpp_source.html#l00259">TensorInfo::SetQuantizationScale()</a>.</p>
462<div class="fragment"><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160;{</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; boost::ignore_unused(memoryManager);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo1 = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({1, 3, 2, 1}, ArmnnType);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo2 = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({1, 1, 2, 3}, ArmnnType);</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({1, 3, 2, 3}, ArmnnType);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160;</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; <span class="keywordflow">if</span> (armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; {</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; inputTensorInfo1.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; inputTensorInfo1.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; inputTensorInfo2.SetQuantizationScale(qScale);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160; inputTensorInfo2.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; outputTensorInfo.SetQuantizationScale(qScale);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; outputTensorInfo.SetQuantizationOffset(qOffset);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; }</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160;</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; <span class="keyword">auto</span> input1 = MakeTensor&lt;T, 4&gt;(inputTensorInfo1, armnnUtils::QuantizedVector&lt;T&gt;(</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; {</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; 0.0f,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; 1.0f,</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160; 2.0f,</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; 3.0f,</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160;</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; 4.0f,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; 5.0f,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160; },</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; <span class="keyword">auto</span> input2 = MakeTensor&lt;T, 4&gt;(inputTensorInfo2, armnnUtils::QuantizedVector&lt;T&gt;(</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; {</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; 0.5f, 1.5f, 2.5f,</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; 3.5f, 4.5f, 5.5f,</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; },</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160;</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; <a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;T,4&gt;</a> ret(outputTensorInfo);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160; ret.outputExpected = MakeTensor&lt;T, 4&gt;(outputTensorInfo, armnnUtils::QuantizedVector&lt;T&gt;(</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; {</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; 0.5f, 1.5f, 2.5f,</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; 4.5f, 5.5f, 6.5f,</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160;</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; 2.5f, 3.5f, 4.5f,</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; 6.5f, 7.5f, 8.5f,</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160;</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; 4.5f, 5.5f, 6.5f,</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; 8.5f, 9.5f, 10.5f,</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; },</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; qScale, qOffset));</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160;</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle1 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo1);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle2 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo2);</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160;</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; <a class="code" href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a> data;</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get());</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get());</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160;</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(data, info);</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160;</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; inputHandle1-&gt;Allocate();</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; inputHandle2-&gt;Allocate();</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; outputHandle-&gt;Allocate();</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160;</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle1.get(), &amp;input1[0][0][0][0]);</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle2.get(), &amp;input2[0][0][0][0]);</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160;</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160; workload-&gt;PostAllocationConfigure();</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160; workload-&gt;Execute();</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160;</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;ret.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160;</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160;}</div><div class="ttc" id="_tensor_copy_utils_8cpp_html_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#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.html#l00009">TensorCopyUtils.cpp:9</a></div></div>
463<div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
464<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
465<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr&lt; ITensorHandle &gt; CreateTensorHandle(const TensorInfo &amp;tensorInfo, const bool IsMemoryManaged=true) const =0</div></div>
466<div class="ttc" id="struct_layer_test_result_html"><div class="ttname"><a href="struct_layer_test_result.html">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.html#l00029">LayerTestResult.hpp:29</a></div></div>
467<div class="ttc" id="_tensor_copy_utils_8cpp_html_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#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.html#l00014">TensorCopyUtils.cpp:14</a></div></div>
468<div class="ttc" id="structarmnn_1_1_workload_info_html"><div class="ttname"><a href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.html#l00016">WorkloadInfo.hpp:16</a></div></div>
469<div class="ttc" id="classarmnn_1_1_tensor_info_html_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#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.html#l00259">Tensor.cpp:259</a></div></div>
470<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateAddition(const AdditionQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01088">WorkloadFactory.cpp:1088</a></div></div>
471<div class="ttc" id="structarmnn_1_1_addition_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00216">WorkloadData.hpp:216</a></div></div>
472<div class="ttc" id="classarmnn_1_1_tensor_info_html_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00275">Tensor.cpp:275</a></div></div>
473</div><!-- fragment -->
474</div>
475</div>
476<a id="a0946a9b1b8cf99591b03ea7f5f7e725f"></a>
477<h2 class="memtitle"><span class="permalink"><a href="#a0946a9b1b8cf99591b03ea7f5f7e725f">&#9670;&nbsp;</a></span>AdditionBroadcastUint8Test()</h2>
478
479<div class="memitem">
480<div class="memproto">
481 <table class="memname">
482 <tr>
483 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;uint8_t, 4&gt; AdditionBroadcastUint8Test </td>
484 <td>(</td>
485 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
486 <td class="paramname"><em>workloadFactory</em>, </td>
487 </tr>
488 <tr>
489 <td class="paramkey"></td>
490 <td></td>
491 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
492 <td class="paramname"><em>memoryManager</em>&#160;</td>
493 </tr>
494 <tr>
495 <td></td>
496 <td>)</td>
497 <td></td><td></td>
498 </tr>
499 </table>
500</div><div class="memdoc">
501
502<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00330">330</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
503<div class="fragment"><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160;{</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160; <span class="keywordflow">return</span> AdditionBroadcastTestImpl&lt;armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; workloadFactory, memoryManager, 2.f, 0);</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160;}</div></div><!-- fragment -->
504</div>
505</div>
506<a id="ae087613cdb8319fbab07d44e6eaf217d"></a>
507<h2 class="memtitle"><span class="permalink"><a href="#ae087613cdb8319fbab07d44e6eaf217d">&#9670;&nbsp;</a></span>AdditionInt16Test()</h2>
508
509<div class="memitem">
510<div class="memproto">
511 <table class="memname">
512 <tr>
513 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;int16_t, 4&gt; AdditionInt16Test </td>
514 <td>(</td>
515 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
516 <td class="paramname"><em>workloadFactory</em>, </td>
517 </tr>
518 <tr>
519 <td class="paramkey"></td>
520 <td></td>
521 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
522 <td class="paramname"><em>memoryManager</em>&#160;</td>
523 </tr>
524 <tr>
525 <td></td>
526 <td>)</td>
527 <td></td><td></td>
528 </tr>
529 </table>
530</div><div class="memdoc">
531
532<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00412">412</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
533<div class="fragment"><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>&#160;{</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape0[] = { 1, 2, 2, 3 };</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape1[] = { 1, 2, 2, 3 };</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>&#160;</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>&#160; std::vector&lt;int16_t&gt; input0 =</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>&#160; {</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>&#160; 63, 35, 77, 70, 56, 112, <span class="comment">// 441, 245, 539, 490, 392, 184</span></div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>&#160; 203, 28, 252, 168, 245, 91 <span class="comment">// 1421, 196, 1764, 1176, 1715, 637</span></div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>&#160; };</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>&#160;</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>&#160; std::vector&lt;int16_t&gt; input1 =</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>&#160; {</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>&#160; 21, 7, 175, 231, 175, 210, <span class="comment">// 126, 28, 1204, 1596, 1204, 1449</span></div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>&#160; 126, 161, 63, 21, 105, 126 <span class="comment">// 861, 1106, 420, 126, 714, 861</span></div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>&#160; };</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>&#160;</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>&#160; std::vector&lt;int16_t&gt; output =</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>&#160; {</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>&#160; 84, 42, 252, 301, 231, 322, <span class="comment">// 588, 294, 1764, 2107(clamped), 1617, 2254(clamped)</span></div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>&#160; 329, 189, 315, 189, 350, 217, <span class="comment">// 2303(clamped), 1323, 2205(clamped), 1323, 2450(clamped), 1519</span></div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>&#160; };</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>&#160;</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>&#160; <span class="keywordflow">return</span> ElementwiseTestHelper&lt;4, armnn::AdditionQueueDescriptor, armnn::DataType::QSymmS16&gt;(</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>&#160; workloadFactory,</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>&#160; memoryManager,</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>&#160; shape0,</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>&#160; input0,</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>&#160; 7.0f,</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>&#160; 0,</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>&#160; shape1,</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>&#160; input1,</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>&#160; 7.0f,</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>&#160; 0,</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>&#160; shape0,</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>&#160; output,</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>&#160; 7.0f,</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>&#160; 0);</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>&#160;}</div></div><!-- fragment -->
534</div>
535</div>
536<a id="a108165b4957f3790332ae0afedf37ccd"></a>
537<h2 class="memtitle"><span class="permalink"><a href="#a108165b4957f3790332ae0afedf37ccd">&#9670;&nbsp;</a></span>AdditionTest()</h2>
538
539<div class="memitem">
540<div class="memproto">
541 <table class="memname">
542 <tr>
543 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;float,4&gt; AdditionTest </td>
544 <td>(</td>
545 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
546 <td class="paramname"><em>workloadFactory</em>, </td>
547 </tr>
548 <tr>
549 <td class="paramkey"></td>
550 <td></td>
551 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
552 <td class="paramname"><em>memoryManager</em>&#160;</td>
553 </tr>
554 <tr>
555 <td></td>
556 <td>)</td>
557 <td></td><td></td>
558 </tr>
559 </table>
560</div><div class="memdoc">
561
562<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00021">21</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
563<div class="fragment"><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;{</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 2u;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 2u;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 2u;</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = 3u;</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = { batchSize, channels, height, width };</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; std::vector&lt;float&gt; input1 =</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; {</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; 0.0f, 2.0f, 1.0f,</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; 0.2f, 1.0f, 2.0f,</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; 1.0f, 2.0f, 1.0f,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; 0.2f, 1.0f, 2.0f,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; 0.0f, 2.0f, 1.0f,</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; 4.2f, 1.0f, 2.0f,</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; 0.0f, 0.0f, 1.0f,</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; 0.2f, 1.0f, 2.0f,</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; };</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; std::vector&lt;float&gt; input2 =</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; 1.0f, 2.0f, 1.0f,</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; 0.0f, 1.0f, 2.0f,</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; 1.0f, 2.0f, -2.0f,</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; 0.2f, 1.0f, 2.0f,</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; 0.0f, 2.0f, 1.0f,</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; 4.2f, 0.0f, -3.0f,</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; 0.0f, 0.0f, 1.0f,</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; 0.7f, 1.0f, 5.0f,</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; };</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; std::vector&lt;float&gt; output</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; {</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; 1.0f, 4.0f, 2.0f,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; 0.2f, 2.0f, 4.0f,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; 2.0f, 4.0f, -1.0f,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; 0.4f, 2.0f, 4.0f,</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; 0.0f, 4.0f, 2.0f,</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; 8.4f, 1.0f, -1.0f,</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; 0.0f, 0.0f, 2.0f,</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; 0.9f, 2.0f, 7.0f,</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; };</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keywordflow">return</span> ElementwiseTestHelper&lt;4, armnn::AdditionQueueDescriptor, armnn::DataType::Float32&gt;(</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; workloadFactory,</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; memoryManager,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; shape,</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; input1,</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; shape,</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; input2,</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; shape,</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; output);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160;}</div></div><!-- fragment -->
564</div>
565</div>
566<a id="a4b5e20456506426ba2e4ea9616df978f"></a>
567<h2 class="memtitle"><span class="permalink"><a href="#a4b5e20456506426ba2e4ea9616df978f">&#9670;&nbsp;</a></span>AdditionUint8Test()</h2>
568
569<div class="memitem">
570<div class="memproto">
571 <table class="memname">
572 <tr>
573 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;uint8_t, 4&gt; AdditionUint8Test </td>
574 <td>(</td>
575 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
576 <td class="paramname"><em>workloadFactory</em>, </td>
577 </tr>
578 <tr>
579 <td class="paramkey"></td>
580 <td></td>
581 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
582 <td class="paramname"><em>memoryManager</em>&#160;</td>
583 </tr>
584 <tr>
585 <td></td>
586 <td>)</td>
587 <td></td><td></td>
588 </tr>
589 </table>
590</div><div class="memdoc">
591
592<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00370">370</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
593<div class="fragment"><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>&#160;{</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape0[] = { 1, 2, 2, 3 };</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape1[] = { 1, 2, 2, 3 };</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>&#160;</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>&#160; std::vector&lt;uint8_t&gt; input0(</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>&#160; {</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>&#160; 63, 35, 77, 70, 56, 112, <span class="comment">// 420, 224, 518, 469, 371, 763</span></div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>&#160; 203, 28, 252, 168, 245, 91 <span class="comment">// 1400, 175, 1743, 1155, 1694, 616</span></div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>&#160; });</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>&#160;</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>&#160; std::vector&lt;uint8_t&gt; input1(</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>&#160; {</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>&#160; 21, 7, 175, 231, 175, 210, <span class="comment">// 126, 28, 1204, 1596, 1204, 1449</span></div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>&#160; 126, 161, 63, 21, 105, 126 <span class="comment">// 861, 1106, 420, 126, 714, 861</span></div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>&#160; });</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>&#160;</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>&#160; std::vector&lt;uint8_t&gt; output(</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>&#160; {</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>&#160; 81, 39, 249, 255, 228, 255, <span class="comment">// 546, 252, 1722, 2065(clamped), 1575, 2212(clamped)</span></div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>&#160; 255, 186, 255, 186, 255, 214, <span class="comment">// 2261(clamped), 1281, 2163(clamped), 1281, 2408(clamped), 1477</span></div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>&#160; });</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>&#160;</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>&#160; <span class="keywordflow">return</span> ElementwiseTestHelper&lt;4, armnn::AdditionQueueDescriptor, armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>&#160; workloadFactory,</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>&#160; memoryManager,</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>&#160; shape0,</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>&#160; input0,</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>&#160; 7.0f,</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>&#160; 3,</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>&#160; shape1,</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>&#160; input1,</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>&#160; 7.0f,</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>&#160; 3,</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>&#160; shape0,</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>&#160; output,</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>&#160; 7.0f,</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>&#160; 3);</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>&#160;}</div></div><!-- fragment -->
594</div>
595</div>
596<a id="a557c464592942eb098f63aa0f91e4d24"></a>
597<h2 class="memtitle"><span class="permalink"><a href="#a557c464592942eb098f63aa0f91e4d24">&#9670;&nbsp;</a></span>CompareAdditionTest()</h2>
598
599<div class="memitem">
600<div class="memproto">
601 <table class="memname">
602 <tr>
603 <td class="memname"><a class="el" href="struct_layer_test_result.html">LayerTestResult</a>&lt;float,4&gt; CompareAdditionTest </td>
604 <td>(</td>
605 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
606 <td class="paramname"><em>workloadFactory</em>, </td>
607 </tr>
608 <tr>
609 <td class="paramkey"></td>
610 <td></td>
611 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.html#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
612 <td class="paramname"><em>memoryManager</em>, </td>
613 </tr>
614 <tr>
615 <td class="paramkey"></td>
616 <td></td>
617 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
618 <td class="paramname"><em>refWorkloadFactory</em>&#160;</td>
619 </tr>
620 <tr>
621 <td></td>
622 <td>)</td>
623 <td></td><td></td>
624 </tr>
625 </table>
626</div><div class="memdoc">
627
628<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00561">561</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
629
630<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.html#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.html#l01088">IWorkloadFactory::CreateAddition()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, and <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>.</p>
631<div class="fragment"><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>&#160;{</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>&#160; boost::ignore_unused(memoryManager);</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 4;</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 1;</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 2;</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = 3;</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>&#160;</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputTensorInfo1, inputTensorInfo2;</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>&#160;</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = {batchSize, channels, height, width};</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>&#160;</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>&#160; inputTensorInfo1 = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, shape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>&#160; inputTensorInfo2 = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, shape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>&#160; outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>(4, shape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>&#160;</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>&#160; <span class="keyword">auto</span> input1 = MakeRandomTensor&lt;float, 4&gt;(inputTensorInfo1, 1232);</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>&#160; <span class="keyword">auto</span> input2 = MakeRandomTensor&lt;float, 4&gt;(inputTensorInfo2, 456);</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>&#160;</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>&#160; <a class="code" href="struct_layer_test_result.html">LayerTestResult&lt;float,4&gt;</a> ret(outputTensorInfo);</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>&#160;</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle1 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo1);</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle2 = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo2);</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>&#160;</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle1Ref = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo1);</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle2Ref = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo2);</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandleRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>&#160;</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>&#160; <a class="code" href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a> data;</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>&#160; AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get());</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>&#160; AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get());</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>&#160; AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>&#160;</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>&#160; <a class="code" href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a> refData = data;</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> refInfo = info;</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>&#160; SetWorkloadInput(refData, refInfo, 0, inputTensorInfo1, inputHandle1Ref.get());</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>&#160; SetWorkloadInput(refData, refInfo, 1, inputTensorInfo2, inputHandle2Ref.get());</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>&#160; SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get());</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>&#160;</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(data, info);</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; workloadRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(refData, refInfo);</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>&#160;</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>&#160; inputHandle1-&gt;Allocate();</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>&#160; inputHandle2-&gt;Allocate();</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>&#160; outputHandle-&gt;Allocate();</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>&#160; inputHandle1Ref-&gt;Allocate();</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>&#160; inputHandle2Ref-&gt;Allocate();</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>&#160; outputHandleRef-&gt;Allocate();</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>&#160;</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle1.get(), &amp;input1[0][0][0][0]);</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle2.get(), &amp;input2[0][0][0][0]);</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle1Ref.get(), &amp;input1[0][0][0][0]);</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle2Ref.get(), &amp;input2[0][0][0][0]);</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>&#160;</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>&#160; workload-&gt;PostAllocationConfigure();</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>&#160; workload-&gt;Execute();</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>&#160; workloadRef-&gt;PostAllocationConfigure();</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>&#160; workloadRef-&gt;Execute();</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>&#160;</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;ret.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.html#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;ret.outputExpected[0][0][0][0], outputHandleRef.get());</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>&#160;</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>&#160; <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>&#160;}</div><div class="ttc" id="_tensor_copy_utils_8cpp_html_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#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.html#l00009">TensorCopyUtils.cpp:9</a></div></div>
632<div class="ttc" id="namespacearmnn_html_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.html#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
633<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
634<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr&lt; ITensorHandle &gt; CreateTensorHandle(const TensorInfo &amp;tensorInfo, const bool IsMemoryManaged=true) const =0</div></div>
635<div class="ttc" id="struct_layer_test_result_html"><div class="ttname"><a href="struct_layer_test_result.html">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.html#l00029">LayerTestResult.hpp:29</a></div></div>
636<div class="ttc" id="_tensor_copy_utils_8cpp_html_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.html#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.html#l00014">TensorCopyUtils.cpp:14</a></div></div>
637<div class="ttc" id="structarmnn_1_1_workload_info_html"><div class="ttname"><a href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.html#l00016">WorkloadInfo.hpp:16</a></div></div>
638<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
639<div class="ttc" id="classarmnn_1_1_i_workload_factory_html_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateAddition(const AdditionQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01088">WorkloadFactory.cpp:1088</a></div></div>
640<div class="ttc" id="structarmnn_1_1_addition_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00216">WorkloadData.hpp:216</a></div></div>
641</div><!-- fragment -->
642</div>
643</div>
644<a id="a5f3caae0b1541a904067544dd37655f0"></a>
645<h2 class="memtitle"><span class="permalink"><a href="#a5f3caae0b1541a904067544dd37655f0">&#9670;&nbsp;</a></span>CreateWorkload< armnn::AdditionQueueDescriptor >()</h2>
646
647<div class="memitem">
648<div class="memproto">
649 <table class="memname">
650 <tr>
651 <td class="memname">std::unique_ptr&lt;<a class="el" href="classarmnn_1_1_i_workload.html">armnn::IWorkload</a>&gt; <a class="el" href="_elementwise_unary_test_impl_8hpp.html#aa50938ed8f91e09acd4af904dcf5543a">CreateWorkload</a>&lt; <a class="el" href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a> &gt; </td>
652 <td>(</td>
653 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a> &amp;&#160;</td>
654 <td class="paramname"><em>workloadFactory</em>, </td>
655 </tr>
656 <tr>
657 <td class="paramkey"></td>
658 <td></td>
659 <td class="paramtype">const <a class="el" href="structarmnn_1_1_workload_info.html">armnn::WorkloadInfo</a> &amp;&#160;</td>
660 <td class="paramname"><em>info</em>, </td>
661 </tr>
662 <tr>
663 <td class="paramkey"></td>
664 <td></td>
665 <td class="paramtype">const <a class="el" href="structarmnn_1_1_addition_queue_descriptor.html">armnn::AdditionQueueDescriptor</a> &amp;&#160;</td>
666 <td class="paramname"><em>descriptor</em>&#160;</td>
667 </tr>
668 <tr>
669 <td></td>
670 <td>)</td>
671 <td></td><td></td>
672 </tr>
673 </table>
674</div><div class="memdoc">
675
676<p class="definition">Definition at line <a class="el" href="_addition_test_impl_8cpp_source.html#l00013">13</a> of file <a class="el" href="_addition_test_impl_8cpp_source.html">AdditionTestImpl.cpp</a>.</p>
677<div class="fragment"><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;{</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; <span class="keywordflow">return</span> workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">CreateAddition</a>(descriptor, info);</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_i_workload_factory_html_acf187617ed4cdd6625b396d6b194923e"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#acf187617ed4cdd6625b396d6b194923e">armnn::IWorkloadFactory::CreateAddition</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateAddition(const AdditionQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01088">WorkloadFactory.cpp:1088</a></div></div>
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686 <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.html">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.html">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.html">backendsCommon</a></li><li class="navelem"><a class="el" href="dir_28bfe507f7e135bdae07c2a6b7f66696.html">test</a></li><li class="navelem"><a class="el" href="dir_99a30439342d160875b21dac3498ad7f.html">layerTests</a></li><li class="navelem"><a class="el" href="_addition_test_impl_8cpp.html">AdditionTestImpl.cpp</a></li>
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