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100<div class="title">FullyConnectedTestImpl.cpp File Reference</div> </div>
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102<div class="contents">
103<div class="textblock"><code>#include &quot;<a class="el" href="_fully_connected_test_impl_8hpp_source.xhtml">FullyConnectedTestImpl.hpp</a>&quot;</code><br />
104<code>#include &lt;<a class="el" href="_quantize_helper_8hpp_source.xhtml">QuantizeHelper.hpp</a>&gt;</code><br />
105<code>#include &lt;<a class="el" href="_cpu_tensor_handle_8hpp_source.xhtml">backendsCommon/CpuTensorHandle.hpp</a>&gt;</code><br />
106<code>#include &lt;<a class="el" href="_data_type_utils_8hpp_source.xhtml">backendsCommon/test/DataTypeUtils.hpp</a>&gt;</code><br />
107<code>#include &lt;<a class="el" href="_tensor_copy_utils_8hpp_source.xhtml">backendsCommon/test/TensorCopyUtils.hpp</a>&gt;</code><br />
108<code>#include &lt;<a class="el" href="_workload_test_utils_8hpp_source.xhtml">backendsCommon/test/WorkloadTestUtils.hpp</a>&gt;</code><br />
109<code>#include &lt;<a class="el" href="_tensor_helpers_8hpp_source.xhtml">test/TensorHelpers.hpp</a>&gt;</code><br />
110</div>
111<p><a href="_fully_connected_test_impl_8cpp_source.xhtml">Go to the source code of this file.</a></p>
112<table class="memberdecls">
113<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
114Functions</h2></td></tr>
115<tr class="memitem:a85031832a04444e2f419a746b4c59345"><td class="memTemplParams" colspan="2">template&lt;typename T , typename B &gt; </td></tr>
116<tr class="memitem:a85031832a04444e2f419a746b4c59345"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt; T, 2 &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#a85031832a04444e2f419a746b4c59345">SimpleFullyConnectedTestImpl</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, <a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo, <a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo, <a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsDesc, <a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesDesc, boost::multi_array&lt; T, 2 &gt; &amp;weights, boost::multi_array&lt; B, 1 &gt; &amp;bias, boost::multi_array&lt; T, 4 &gt; &amp;input, bool biasEnabled, bool transposeWeights)</td></tr>
117<tr class="separator:a85031832a04444e2f419a746b4c59345"><td class="memSeparator" colspan="2">&#160;</td></tr>
118<tr class="memitem:a25b72d9cbe9cca2c89ba997e6f2cfb87"><td class="memTemplParams" colspan="2">template&lt;armnn::DataType ArmnnType, typename T &gt; </td></tr>
119<tr class="memitem:a25b72d9cbe9cca2c89ba997e6f2cfb87"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt; T, 2 &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#a25b72d9cbe9cca2c89ba997e6f2cfb87">FullyConnectedTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, bool biasEnabled)</td></tr>
120<tr class="separator:a25b72d9cbe9cca2c89ba997e6f2cfb87"><td class="memSeparator" colspan="2">&#160;</td></tr>
121<tr class="memitem:ac2fd4978ceeccf895121c47b47cbd237"><td class="memTemplParams" colspan="2">template&lt;armnn::DataType ArmnnType, typename T = armnn::ResolveType&lt;ArmnnType&gt;&gt; </td></tr>
122<tr class="memitem:ac2fd4978ceeccf895121c47b47cbd237"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt; T, 2 &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#ac2fd4978ceeccf895121c47b47cbd237">FullyConnectedLargeTestCommon</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, bool transposeWeights, float qScale=0.0f, int32_t qOffset=0)</td></tr>
123<tr class="separator:ac2fd4978ceeccf895121c47b47cbd237"><td class="memSeparator" colspan="2">&#160;</td></tr>
124<tr class="memitem:a3bcde1c62518c032c93eac1fa0ce6062"><td class="memItemLeft" align="right" valign="top">template <a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt; <a class="el" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a>&lt; <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a> &gt;, 2 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#a3bcde1c62518c032c93eac1fa0ce6062">FullyConnectedTest&lt; armnn::DataType::QAsymmU8 &gt;</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, bool biasEnabled)</td></tr>
125<tr class="separator:a3bcde1c62518c032c93eac1fa0ce6062"><td class="memSeparator" colspan="2">&#160;</td></tr>
126<tr class="memitem:a5577e592bc21307937a26abbc908353f"><td class="memItemLeft" align="right" valign="top">template <a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt; <a class="el" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a>&lt; <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a> &gt;, 2 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#a5577e592bc21307937a26abbc908353f">FullyConnectedTest&lt; armnn::DataType::QSymmS16 &gt;</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, bool biasEnabled)</td></tr>
127<tr class="separator:a5577e592bc21307937a26abbc908353f"><td class="memSeparator" colspan="2">&#160;</td></tr>
128<tr class="memitem:a9aa238fbd4c6a6d1259b31d2a51c93b8"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt; float, 2 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#a9aa238fbd4c6a6d1259b31d2a51c93b8">FullyConnectedFloat32Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, bool biasEnabled, bool transposeWeights)</td></tr>
129<tr class="separator:a9aa238fbd4c6a6d1259b31d2a51c93b8"><td class="memSeparator" colspan="2">&#160;</td></tr>
130<tr class="memitem:a0fb6957126b671361ccdd80f3549faa9"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt; float, 2 &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#a0fb6957126b671361ccdd80f3549faa9">FullyConnectedLargeTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager, bool transposeWeights)</td></tr>
131<tr class="separator:a0fb6957126b671361ccdd80f3549faa9"><td class="memSeparator" colspan="2">&#160;</td></tr>
132</table>
133<h2 class="groupheader">Function Documentation</h2>
134<a id="a9aa238fbd4c6a6d1259b31d2a51c93b8"></a>
135<h2 class="memtitle"><span class="permalink"><a href="#a9aa238fbd4c6a6d1259b31d2a51c93b8">&#9670;&nbsp;</a></span>FullyConnectedFloat32Test()</h2>
136
137<div class="memitem">
138<div class="memproto">
139 <table class="memname">
140 <tr>
141 <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt;float, 2&gt; FullyConnectedFloat32Test </td>
142 <td>(</td>
143 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;&#160;</td>
144 <td class="paramname"><em>workloadFactory</em>, </td>
145 </tr>
146 <tr>
147 <td class="paramkey"></td>
148 <td></td>
149 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
150 <td class="paramname"><em>memoryManager</em>, </td>
151 </tr>
152 <tr>
153 <td class="paramkey"></td>
154 <td></td>
155 <td class="paramtype">bool&#160;</td>
156 <td class="paramname"><em>biasEnabled</em>, </td>
157 </tr>
158 <tr>
159 <td class="paramkey"></td>
160 <td></td>
161 <td class="paramtype">bool&#160;</td>
162 <td class="paramname"><em>transposeWeights</em>&#160;</td>
163 </tr>
164 <tr>
165 <td></td>
166 <td>)</td>
167 <td></td><td></td>
168 </tr>
169 </table>
170</div><div class="memdoc">
171
172<p class="definition">Definition at line <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml#l00247">247</a> of file <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml">FullyConnectedTestImpl.cpp</a>.</p>
173
174<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00041">LayerTestResult&lt; T, n &gt;::outputExpected</a>, and <a class="el" href="_descriptors_8cpp_source.xhtml#l00342">armnn::swap()</a>.</p>
175<div class="fragment"><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160;{</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 1;</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 1;</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 5;</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputNum = 2;</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; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = 3;</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputNum = 2;</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160;</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160; <span class="comment">// Define the tensor descriptors.</span></div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsDesc;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesDesc;</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160;</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { inputNum, inputChannels, inputHeight, inputWidth };</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { outputNum, outputChannels };</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { inputChannels, outputChannels };</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160;</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; <span class="keywordflow">if</span> (transposeWeights)</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; {</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160; <a class="code" href="namespacearmnn.xhtml#a14d7f180bf51e86850305965c3707e07">std::swap</a>(weightsShape[0], weightsShape[1]);</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;</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> biasShape[] = { outputChannels };</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160;</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(2, outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; weightsDesc = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(2, weightsShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; biasesDesc = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(1, biasShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</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.xhtml">LayerTestResult&lt;float, 2&gt;</a> result(outputTensorInfo);</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160;</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160; boost::multi_array&lt;float, 4&gt; input = MakeTensor&lt;float, 4&gt;(inputTensorInfo, std::vector&lt;float&gt;(</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; {</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; 1.0f, 2.0f, 3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160;</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; 5.0f, 4.0f, 3.0f, 2.0f, 1.0f</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; })</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; );</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; boost::multi_array&lt;float, 2&gt; weights = MakeTensor&lt;float, 2&gt;(weightsDesc, std::vector&lt;float&gt;(</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; .5f, 2.f, .5f,</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; .5f, 2.f, 1.f,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; .5f, 2.f, 2.f,</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; .5f, 2.f, 3.f,</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; .5f, 2.f, 4.f</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; }));</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160;</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; <span class="keywordflow">if</span> (transposeWeights)</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; {</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; weights = MakeTensor&lt;float, 2&gt;(weightsDesc, std::vector&lt;float&gt;(</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; {</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; .5f, .5f, .5f, .5f, .5f,</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; 2.f, 2.f, 2.f, 2.f, 2.f,</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; .5f, 1.f, 2.f, 3.f, 4.f</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; }));</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;</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160;</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160; std::vector&lt;float&gt; biasValues({0.f, 0.f, 0.f});</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160; <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; {</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; biasValues = std::vector&lt;float&gt;({10.f, 20.f, 30.f});</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; }</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160; boost::multi_array&lt;float, 1&gt; bias = MakeTensor&lt;float, 1&gt;(biasesDesc, biasValues);</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160;</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; result = SimpleFullyConnectedTestImpl&lt;float&gt;(</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160; workloadFactory,</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; memoryManager,</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; inputTensorInfo, outputTensorInfo,</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160; weightsDesc, biasesDesc,</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>&#160; weights, bias, input,</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160; biasEnabled, transposeWeights</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; );</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160;</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160; result.outputExpected = MakeTensor&lt;float, 2&gt;(outputTensorInfo, std::vector&lt;float&gt;(</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160; {</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160; 0.5f + 1.0f + 1.5f + 2.0f + 2.5f + biasValues[0],</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; 2.0f + 4.0f + 6.0f + 8.0f + 10.f + biasValues[1],</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160; 0.5f + 2.0f + 6.0f + 12.f + 20.f + biasValues[2],</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160;</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; 2.5f + 2.0f + 1.5f + 1.0f + 0.5f + biasValues[0],</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160; 10.0f + 8.0f + 6.0f + 4.0f + 2.f + biasValues[1],</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; 2.5f + 4.0f + 6.0f + 6.f + 4.f + biasValues[2]</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; })</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; );</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160;</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160;}</div><div class="ttc" id="namespacearmnn_xhtml_a14d7f180bf51e86850305965c3707e07"><div class="ttname"><a href="namespacearmnn.xhtml#a14d7f180bf51e86850305965c3707e07">armnn::swap</a></div><div class="ttdeci">void swap(OriginsDescriptor &amp;first, OriginsDescriptor &amp;second)</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.xhtml#l00342">Descriptors.cpp:342</a></div></div>
176<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
177<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
178<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div>
179</div><!-- fragment -->
180</div>
181</div>
182<a id="a0fb6957126b671361ccdd80f3549faa9"></a>
183<h2 class="memtitle"><span class="permalink"><a href="#a0fb6957126b671361ccdd80f3549faa9">&#9670;&nbsp;</a></span>FullyConnectedLargeTest()</h2>
184
185<div class="memitem">
186<div class="memproto">
187 <table class="memname">
188 <tr>
189 <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt;float, 2&gt; FullyConnectedLargeTest </td>
190 <td>(</td>
191 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;&#160;</td>
192 <td class="paramname"><em>workloadFactory</em>, </td>
193 </tr>
194 <tr>
195 <td class="paramkey"></td>
196 <td></td>
197 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
198 <td class="paramname"><em>memoryManager</em>, </td>
199 </tr>
200 <tr>
201 <td class="paramkey"></td>
202 <td></td>
203 <td class="paramtype">bool&#160;</td>
204 <td class="paramname"><em>transposeWeights</em>&#160;</td>
205 </tr>
206 <tr>
207 <td></td>
208 <td>)</td>
209 <td></td><td></td>
210 </tr>
211 </table>
212</div><div class="memdoc">
213
214<p class="definition">Definition at line <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml#l00344">344</a> of file <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml">FullyConnectedTestImpl.cpp</a>.</p>
215<div class="fragment"><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>&#160;{</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160; <span class="keywordflow">return</span> FullyConnectedLargeTestCommon&lt;armnn::DataType::Float32&gt;(workloadFactory, memoryManager, transposeWeights);</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160;}</div></div><!-- fragment -->
216</div>
217</div>
218<a id="ac2fd4978ceeccf895121c47b47cbd237"></a>
219<h2 class="memtitle"><span class="permalink"><a href="#ac2fd4978ceeccf895121c47b47cbd237">&#9670;&nbsp;</a></span>FullyConnectedLargeTestCommon()</h2>
220
221<div class="memitem">
222<div class="memproto">
223 <table class="memname">
224 <tr>
225 <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt;T, 2&gt; FullyConnectedLargeTestCommon </td>
226 <td>(</td>
227 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;&#160;</td>
228 <td class="paramname"><em>workloadFactory</em>, </td>
229 </tr>
230 <tr>
231 <td class="paramkey"></td>
232 <td></td>
233 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
234 <td class="paramname"><em>memoryManager</em>, </td>
235 </tr>
236 <tr>
237 <td class="paramkey"></td>
238 <td></td>
239 <td class="paramtype">bool&#160;</td>
240 <td class="paramname"><em>transposeWeights</em>, </td>
241 </tr>
242 <tr>
243 <td class="paramkey"></td>
244 <td></td>
245 <td class="paramtype">float&#160;</td>
246 <td class="paramname"><em>qScale</em> = <code>0.0f</code>, </td>
247 </tr>
248 <tr>
249 <td class="paramkey"></td>
250 <td></td>
251 <td class="paramtype">int32_t&#160;</td>
252 <td class="paramname"><em>qOffset</em> = <code>0</code>&#160;</td>
253 </tr>
254 <tr>
255 <td></td>
256 <td>)</td>
257 <td></td><td></td>
258 </tr>
259 </table>
260</div><div class="memdoc">
261
262<p class="definition">Definition at line <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml#l00148">148</a> of file <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml">FullyConnectedTestImpl.cpp</a>.</p>
263
264<p class="reference">References <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00041">LayerTestResult&lt; T, n &gt;::outputExpected</a>, <a class="el" href="_tensor_8cpp_source.xhtml#l00275">TensorInfo::SetQuantizationOffset()</a>, <a class="el" href="_tensor_8cpp_source.xhtml#l00259">TensorInfo::SetQuantizationScale()</a>, and <a class="el" href="_descriptors_8cpp_source.xhtml#l00342">armnn::swap()</a>.</p>
265<div class="fragment"><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160;{</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 1;</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 1;</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 5;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputNum = 1;</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = 1;</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputNum = 1;</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160;</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; <span class="comment">// Define the tensor descriptors.</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsDesc;</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesDesc;</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160;</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { inputNum, inputChannels, inputHeight, inputWidth };</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { outputNum, outputChannels };</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { inputChannels, outputChannels };</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; <span class="keywordflow">if</span> (transposeWeights)</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; {</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; <a class="code" href="namespacearmnn.xhtml#a14d7f180bf51e86850305965c3707e07">std::swap</a>(weightsShape[0], weightsShape[1]);</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; }</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160;</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> biasShape[] = { outputChannels };</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160;</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, inputShape, ArmnnType);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160; outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(2, outputShape, ArmnnType);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; weightsDesc = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(2, weightsShape, ArmnnType);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; biasesDesc = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(1, biasShape, ArmnnType);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160;</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; <span class="keywordflow">if</span>(armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; {</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160; inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160; inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; }</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160;</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160; <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 2&gt;</a> result(outputTensorInfo);</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160;</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; boost::multi_array&lt;T, 4&gt; input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; armnnUtils::QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; 1.0f, 10.0f, 100.0f, 1000.0f, 10000.0f,</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; },</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; qScale, qOffset)</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;</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160; boost::multi_array&lt;T, 2&gt; weights = MakeTensor&lt;T, 2&gt;(weightsDesc,</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; armnnUtils::QuantizedVector&lt;T&gt;({</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160; 2.0f, 3.0f, 4.0f, 5.0f, 6.0f</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; qScale, qOffset)</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; );</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; std::vector&lt;T&gt; biasValues({900000.f});</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; boost::multi_array&lt;T, 1&gt; bias = MakeTensor&lt;T, 1&gt;(biasesDesc, biasValues);</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; result = SimpleFullyConnectedTestImpl&lt;T&gt;(</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; workloadFactory,</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; memoryManager,</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; inputTensorInfo, outputTensorInfo,</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; weightsDesc, biasesDesc,</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; weights, bias, input,</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; <span class="keyword">true</span>, transposeWeights</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; );</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; result.outputExpected = MakeTensor&lt;T, 2&gt;(outputTensorInfo,</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; armnnUtils::QuantizedVector&lt;T&gt;({ 965432.0f }, qScale, qOffset));</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160;</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160;}</div><div class="ttc" id="namespacearmnn_xhtml_a14d7f180bf51e86850305965c3707e07"><div class="ttname"><a href="namespacearmnn.xhtml#a14d7f180bf51e86850305965c3707e07">armnn::swap</a></div><div class="ttdeci">void swap(OriginsDescriptor &amp;first, OriginsDescriptor &amp;second)</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.xhtml#l00342">Descriptors.cpp:342</a></div></div>
266<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
267<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00259">Tensor.cpp:259</a></div></div>
268<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div>
269<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#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.xhtml#l00275">Tensor.cpp:275</a></div></div>
270</div><!-- fragment -->
271</div>
272</div>
273<a id="a25b72d9cbe9cca2c89ba997e6f2cfb87"></a>
274<h2 class="memtitle"><span class="permalink"><a href="#a25b72d9cbe9cca2c89ba997e6f2cfb87">&#9670;&nbsp;</a></span>FullyConnectedTest()</h2>
275
276<div class="memitem">
277<div class="memproto">
278 <table class="memname">
279 <tr>
280 <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt;T, 2&gt; FullyConnectedTest </td>
281 <td>(</td>
282 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;&#160;</td>
283 <td class="paramname"><em>workloadFactory</em>, </td>
284 </tr>
285 <tr>
286 <td class="paramkey"></td>
287 <td></td>
288 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
289 <td class="paramname"><em>memoryManager</em>, </td>
290 </tr>
291 <tr>
292 <td class="paramkey"></td>
293 <td></td>
294 <td class="paramtype">bool&#160;</td>
295 <td class="paramname"><em>biasEnabled</em>&#160;</td>
296 </tr>
297 <tr>
298 <td></td>
299 <td>)</td>
300 <td></td><td></td>
301 </tr>
302 </table>
303</div><div class="memdoc">
304
305<p class="definition">Definition at line <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml#l00071">71</a> of file <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml">FullyConnectedTestImpl.cpp</a>.</p>
306
307<p class="reference">References <a class="el" href="_layer_support_rules_8hpp_source.xhtml#l00014">armnn::GetBiasTypeFromWeightsType()</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00041">LayerTestResult&lt; T, n &gt;::outputExpected</a>, <a class="el" href="_tensor_8cpp_source.xhtml#l00259">TensorInfo::SetQuantizationScale()</a>, and <a class="el" href="_cl_layer_tests_8cpp_source.xhtml#l00202">true</a>.</p>
308<div class="fragment"><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160;{</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 3u;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 2u;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 1u;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = inputWidth * inputHeight * inputChannels;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = 2u;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({ 1, inputChannels, inputHeight, inputWidth }, ArmnnType);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(0.1f);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; inputTensorInfo.SetQuantizationOffset(63);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, outputChannels }, ArmnnType);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(5.f);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; outputTensorInfo.SetQuantizationOffset(biasEnabled ? -50 : 10);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsDesc({ outputChannels, inputSize }, ArmnnType);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; weightsDesc.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(0.2f);</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; weightsDesc.SetQuantizationOffset(93);</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesDesc({ outputChannels }, <a class="code" href="namespacearmnn.xhtml#a83c4a275acf59f62b8387f389d0929d5">GetBiasTypeFromWeightsType</a>(weightsDesc.GetDataType()).value());</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; biasesDesc.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(inputTensorInfo.GetQuantizationScale() * weightsDesc.GetQuantizationScale());</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; biasesDesc.SetQuantizationOffset(0);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 2&gt;</a> result(outputTensorInfo);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo, ConvertToDataType&lt;ArmnnType&gt;(</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; {</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; -1.2f, 6.1f, -3.5f,</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; 18.8f, -5.5f, 2.9f</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; },</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; inputTensorInfo));</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; <span class="keyword">auto</span> weights = MakeTensor&lt;T, 2&gt;(weightsDesc, ConvertToDataType&lt;ArmnnType&gt;(</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; {</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; -8.4f, 20.0f, -10.4f, -8, 16.4f, -11.8f,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; 23.4f, 10.4f, -14.0f, -3.8f, -11.8f, 11.4f</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; },</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; weightsDesc));</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; <span class="keyword">auto</span> bias = MakeTensor&lt;int32_t, 1&gt;(biasesDesc, std::vector&lt;int32_t&gt;{9250, 67500});</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; result = SimpleFullyConnectedTestImpl&lt;T&gt;(</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; workloadFactory,</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; memoryManager,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; inputTensorInfo, outputTensorInfo,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; weightsDesc, biasesDesc,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; weights, bias, input,</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; biasEnabled, <a class="code" href="_cl_layer_tests_8cpp.xhtml#a37f1c3ccc9fc906be85185350dd83d48">true</a></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; <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; {</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; result.outputExpected = MakeTensor&lt;T, 2&gt;(outputTensorInfo,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; ConvertToDataType&lt;ArmnnType&gt;({80.f, 1460.f}, outputTensorInfo));</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; }</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <span class="keywordflow">else</span></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; result.outputExpected = MakeTensor&lt;T, 2&gt;(outputTensorInfo,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; ConvertToDataType&lt;ArmnnType&gt;({-107.04f, 110.f}, outputTensorInfo));</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; }</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160;}</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
309<div class="ttc" id="_cl_layer_tests_8cpp_xhtml_a37f1c3ccc9fc906be85185350dd83d48"><div class="ttname"><a href="_cl_layer_tests_8cpp.xhtml#a37f1c3ccc9fc906be85185350dd83d48">true</a></div><div class="ttdeci">DataLayout::NCHW DataLayout::NCHW DataLayout::NHWC DataLayout::NHWC true</div><div class="ttdef"><b>Definition:</b> <a href="_cl_layer_tests_8cpp_source.xhtml#l00202">ClLayerTests.cpp:202</a></div></div>
310<div class="ttc" id="namespacearmnn_xhtml_a83c4a275acf59f62b8387f389d0929d5"><div class="ttname"><a href="namespacearmnn.xhtml#a83c4a275acf59f62b8387f389d0929d5">armnn::GetBiasTypeFromWeightsType</a></div><div class="ttdeci">armnn::Optional&lt; armnn::DataType &gt; GetBiasTypeFromWeightsType(armnn::Optional&lt; armnn::DataType &gt; weightsType)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_support_rules_8hpp_source.xhtml#l00014">LayerSupportRules.hpp:14</a></div></div>
311<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00259">Tensor.cpp:259</a></div></div>
312<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div>
313</div><!-- fragment -->
314</div>
315</div>
316<a id="a3bcde1c62518c032c93eac1fa0ce6062"></a>
317<h2 class="memtitle"><span class="permalink"><a href="#a3bcde1c62518c032c93eac1fa0ce6062">&#9670;&nbsp;</a></span>FullyConnectedTest< armnn::DataType::QAsymmU8 >()</h2>
318
319<div class="memitem">
320<div class="memproto">
321 <table class="memname">
322 <tr>
323 <td class="memname">template <a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt;<a class="el" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a>&lt;<a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>&gt;, 2&gt; <a class="el" href="_fully_connected_test_impl_8hpp.xhtml#a25b72d9cbe9cca2c89ba997e6f2cfb87">FullyConnectedTest</a>&lt; <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a> &gt; </td>
324 <td>(</td>
325 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;&#160;</td>
326 <td class="paramname"><em>workloadFactory</em>, </td>
327 </tr>
328 <tr>
329 <td class="paramkey"></td>
330 <td></td>
331 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
332 <td class="paramname"><em>memoryManager</em>, </td>
333 </tr>
334 <tr>
335 <td class="paramkey"></td>
336 <td></td>
337 <td class="paramtype">bool&#160;</td>
338 <td class="paramname"><em>biasEnabled</em>&#160;</td>
339 </tr>
340 <tr>
341 <td></td>
342 <td>)</td>
343 <td></td><td></td>
344 </tr>
345 </table>
346</div><div class="memdoc">
347
348</div>
349</div>
350<a id="a5577e592bc21307937a26abbc908353f"></a>
351<h2 class="memtitle"><span class="permalink"><a href="#a5577e592bc21307937a26abbc908353f">&#9670;&nbsp;</a></span>FullyConnectedTest< armnn::DataType::QSymmS16 >()</h2>
352
353<div class="memitem">
354<div class="memproto">
355 <table class="memname">
356 <tr>
357 <td class="memname">template <a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt;<a class="el" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a>&lt;<a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>&gt;, 2&gt; <a class="el" href="_fully_connected_test_impl_8hpp.xhtml#a25b72d9cbe9cca2c89ba997e6f2cfb87">FullyConnectedTest</a>&lt; <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a> &gt; </td>
358 <td>(</td>
359 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;&#160;</td>
360 <td class="paramname"><em>workloadFactory</em>, </td>
361 </tr>
362 <tr>
363 <td class="paramkey"></td>
364 <td></td>
365 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
366 <td class="paramname"><em>memoryManager</em>, </td>
367 </tr>
368 <tr>
369 <td class="paramkey"></td>
370 <td></td>
371 <td class="paramtype">bool&#160;</td>
372 <td class="paramname"><em>biasEnabled</em>&#160;</td>
373 </tr>
374 <tr>
375 <td></td>
376 <td>)</td>
377 <td></td><td></td>
378 </tr>
379 </table>
380</div><div class="memdoc">
381
382</div>
383</div>
384<a id="a85031832a04444e2f419a746b4c59345"></a>
385<h2 class="memtitle"><span class="permalink"><a href="#a85031832a04444e2f419a746b4c59345">&#9670;&nbsp;</a></span>SimpleFullyConnectedTestImpl()</h2>
386
387<div class="memitem">
388<div class="memproto">
389 <table class="memname">
390 <tr>
391 <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt;T, 2&gt; SimpleFullyConnectedTestImpl </td>
392 <td>(</td>
393 <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;&#160;</td>
394 <td class="paramname"><em>workloadFactory</em>, </td>
395 </tr>
396 <tr>
397 <td class="paramkey"></td>
398 <td></td>
399 <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
400 <td class="paramname"><em>memoryManager</em>, </td>
401 </tr>
402 <tr>
403 <td class="paramkey"></td>
404 <td></td>
405 <td class="paramtype"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>&#160;</td>
406 <td class="paramname"><em>inputTensorInfo</em>, </td>
407 </tr>
408 <tr>
409 <td class="paramkey"></td>
410 <td></td>
411 <td class="paramtype"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>&#160;</td>
412 <td class="paramname"><em>outputTensorInfo</em>, </td>
413 </tr>
414 <tr>
415 <td class="paramkey"></td>
416 <td></td>
417 <td class="paramtype"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>&#160;</td>
418 <td class="paramname"><em>weightsDesc</em>, </td>
419 </tr>
420 <tr>
421 <td class="paramkey"></td>
422 <td></td>
423 <td class="paramtype"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>&#160;</td>
424 <td class="paramname"><em>biasesDesc</em>, </td>
425 </tr>
426 <tr>
427 <td class="paramkey"></td>
428 <td></td>
429 <td class="paramtype">boost::multi_array&lt; T, 2 &gt; &amp;&#160;</td>
430 <td class="paramname"><em>weights</em>, </td>
431 </tr>
432 <tr>
433 <td class="paramkey"></td>
434 <td></td>
435 <td class="paramtype">boost::multi_array&lt; B, 1 &gt; &amp;&#160;</td>
436 <td class="paramname"><em>bias</em>, </td>
437 </tr>
438 <tr>
439 <td class="paramkey"></td>
440 <td></td>
441 <td class="paramtype">boost::multi_array&lt; T, 4 &gt; &amp;&#160;</td>
442 <td class="paramname"><em>input</em>, </td>
443 </tr>
444 <tr>
445 <td class="paramkey"></td>
446 <td></td>
447 <td class="paramtype">bool&#160;</td>
448 <td class="paramname"><em>biasEnabled</em>, </td>
449 </tr>
450 <tr>
451 <td class="paramkey"></td>
452 <td></td>
453 <td class="paramtype">bool&#160;</td>
454 <td class="paramname"><em>transposeWeights</em>&#160;</td>
455 </tr>
456 <tr>
457 <td></td>
458 <td>)</td>
459 <td></td><td></td>
460 </tr>
461 </table>
462</div><div class="memdoc">
463
464<p class="definition">Definition at line <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml#l00024">24</a> of file <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml">FullyConnectedTestImpl.cpp</a>.</p>
465
466<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01225">IWorkloadFactory::CreateFullyConnected()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00150">FullyConnectedQueueDescriptor::m_Bias</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00386">FullyConnectedDescriptor::m_BiasEnabled</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00049">QueueDescriptorWithParameters&lt; LayerDescriptor &gt;::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00388">FullyConnectedDescriptor::m_TransposeWeightMatrix</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00149">FullyConnectedQueueDescriptor::m_Weight</a>, and <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00040">LayerTestResult&lt; T, n &gt;::output</a>.</p>
467<div class="fragment"><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; <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; std::unique_ptr&lt;armnn::ITensorHandle&gt; outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <a class="code" href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml">armnn::FullyConnectedQueueDescriptor</a> data;</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">armnn::ScopedCpuTensorHandle</a> weightsTensor(weightsDesc);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">armnn::ScopedCpuTensorHandle</a> biasTensor(biasesDesc);</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; <a class="code" href="_tensor_copy_utils_8cpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&amp;weightsTensor, &amp;weights[0][0]);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&amp;biasTensor, &amp;bias[0]);</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; AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; data.<a class="code" href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">m_Weight</a> = &amp;weightsTensor;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; data.<a class="code" href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml#ab3437cee6b0687812104fc1b37cbe8b3">m_Bias</a> = &amp;biasTensor;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = biasEnabled;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#a281fcaec86e17c97f7b8402633f6b55a">m_TransposeWeightMatrix</a> = transposeWeights;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a1c193739520e08f686b347ff795ad2fe">CreateFullyConnected</a>(data, info);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 2&gt;</a> result(outputTensorInfo);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; inputHandle-&gt;Allocate();</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; outputHandle-&gt;Allocate();</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &amp;input[0][0][0][0]);</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; ExecuteWorkload(*workload, memoryManager);</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; <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;result.output[0][0], outputHandle.get());</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160;}</div><div class="ttc" id="structarmnn_1_1_fully_connected_queue_descriptor_xhtml_a3369b66d9316a773a41711e3f590c041"><div class="ttname"><a href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml#a3369b66d9316a773a41711e3f590c041">armnn::FullyConnectedQueueDescriptor::m_Weight</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Weight</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00149">WorkloadData.hpp:149</a></div></div>
468<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml_a281fcaec86e17c97f7b8402633f6b55a"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml#a281fcaec86e17c97f7b8402633f6b55a">armnn::FullyConnectedDescriptor::m_TransposeWeightMatrix</a></div><div class="ttdeci">bool m_TransposeWeightMatrix</div><div class="ttdoc">Enable/disable transpose weight matrix. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00388">Descriptors.hpp:388</a></div></div>
469<div class="ttc" id="structarmnn_1_1_fully_connected_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml">armnn::FullyConnectedQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00141">WorkloadData.hpp:141</a></div></div>
470<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &amp;&amp;...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div>
471<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#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.xhtml#l00049">WorkloadData.hpp:49</a></div></div>
472<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::FullyConnectedDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00386">Descriptors.hpp:386</a></div></div>
473<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00019">TensorCopyUtils.cpp:19</a></div></div>
474<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div>
475<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr&lt; ITensorHandle &gt; CreateTensorHandle(const TensorInfo &amp;tensorInfo, const bool IsMemoryManaged=true) const =0</div></div>
476<div class="ttc" id="classarmnn_1_1_scoped_cpu_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">armnn::ScopedCpuTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.xhtml#l00106">CpuTensorHandle.hpp:106</a></div></div>
477<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
478<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div>
479<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div>
480<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a1c193739520e08f686b347ff795ad2fe"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a1c193739520e08f686b347ff795ad2fe">armnn::IWorkloadFactory::CreateFullyConnected</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateFullyConnected(const FullyConnectedQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01225">WorkloadFactory.cpp:1225</a></div></div>
481<div class="ttc" id="structarmnn_1_1_fully_connected_queue_descriptor_xhtml_ab3437cee6b0687812104fc1b37cbe8b3"><div class="ttname"><a href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml#ab3437cee6b0687812104fc1b37cbe8b3">armnn::FullyConnectedQueueDescriptor::m_Bias</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Bias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00150">WorkloadData.hpp:150</a></div></div>
482<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div>
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