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| author | Nikhil Raj <nikhil.raj@arm.com> | 2022-03-08 20:01:38 +0000 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-03-09 12:26:14 +0000 |
| commit | f4019872c1134c6fcc1d6993e5746f55c1e79208 (patch) | |
| tree | b07ea8bdd70d696adfa3814344e210ea67be1e8c /22.02/_fully_connected_test_impl_8cpp.xhtml | |
| parent | 0d75c02b21b919b81035205f3914ee273b93b30c (diff) | |
| download | armnn-f4019872c1134c6fcc1d6993e5746f55c1e79208.tar.gz | |
IVGCVSW-6819 Fix the directory structure and broken link to latest docu
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: I05b559d15faf92c76ff536719693b361316be4f3
Diffstat (limited to '22.02/_fully_connected_test_impl_8cpp.xhtml')
| -rw-r--r-- | 22.02/_fully_connected_test_impl_8cpp.xhtml | 563 |
1 files changed, 563 insertions, 0 deletions
diff --git a/22.02/_fully_connected_test_impl_8cpp.xhtml b/22.02/_fully_connected_test_impl_8cpp.xhtml new file mode 100644 index 0000000000..ca2dac1d85 --- /dev/null +++ b/22.02/_fully_connected_test_impl_8cpp.xhtml @@ -0,0 +1,563 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/backends/backendsCommon/test/layerTests/FullyConnectedTestImpl.cpp File Reference</title> +<link href="tabs.css" rel="stylesheet" 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top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_fully_connected_test_impl_8cpp.xhtml','');}); +</script> +<div id="doc-content"> +<!-- window showing the filter options --> +<div id="MSearchSelectWindow" + onmouseover="return searchBox.OnSearchSelectShow()" + onmouseout="return searchBox.OnSearchSelectHide()" + onkeydown="return searchBox.OnSearchSelectKey(event)"> +</div> + +<!-- iframe showing the search results (closed by default) --> +<div id="MSearchResultsWindow"> +<iframe src="javascript:void(0)" frameborder="0" + name="MSearchResults" id="MSearchResults"> +</iframe> +</div> + +<div class="header"> + <div class="summary"> +<a href="#func-members">Functions</a> </div> + <div class="headertitle"> +<div class="title">FullyConnectedTestImpl.cpp File Reference</div> </div> +</div><!--header--> +<div class="contents"> +<div class="textblock"><code>#include "<a class="el" href="_fully_connected_test_impl_8hpp_source.xhtml">FullyConnectedTestImpl.hpp</a>"</code><br /> +<code>#include <<a class="el" href="_quantize_helper_8hpp_source.xhtml">armnnUtils/QuantizeHelper.hpp</a>></code><br /> +<code>#include <<a class="el" href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml">armnn/backends/TensorHandle.hpp</a>></code><br /> +<code>#include <DataTypeUtils.hpp></code><br /> +<code>#include <<a class="el" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_source.xhtml">armnnTestUtils/TensorCopyUtils.hpp</a>></code><br /> +<code>#include <<a class="el" href="include_2armnn_test_utils_2_workload_test_utils_8hpp_source.xhtml">armnnTestUtils/WorkloadTestUtils.hpp</a>></code><br /> +<code>#include <<a class="el" href="include_2armnn_test_utils_2_tensor_helpers_8hpp_source.xhtml">armnnTestUtils/TensorHelpers.hpp</a>></code><br /> +</div> +<p><a href="_fully_connected_test_impl_8cpp_source.xhtml">Go to the source code of this file.</a></p> +<table class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> +Functions</h2></td></tr> +<tr class="memitem:af8f4ed2106c6aaf93ac0be43348a19da"><td class="memTemplParams" colspan="2">template<typename T , typename B > </td></tr> +<tr class="memitem:af8f4ed2106c6aaf93ac0be43348a19da"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 2 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#af8f4ed2106c6aaf93ac0be43348a19da">SimpleFullyConnectedTestImpl</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory, <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> weightsTensorInfo, <a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesTensorInfo, std::vector< T > &weights, std::vector< B > &bias, std::vector< T > &input, bool biasEnabled, bool transposeWeights, bool constantWeights)</td></tr> +<tr class="separator:af8f4ed2106c6aaf93ac0be43348a19da"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a59a2fc917d2bd6687858f4ace9617a97"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, typename T > </td></tr> +<tr class="memitem:a59a2fc917d2bd6687858f4ace9617a97"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 2 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#a59a2fc917d2bd6687858f4ace9617a97">FullyConnectedTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory, bool biasEnabled, bool constantWeights)</td></tr> +<tr class="separator:a59a2fc917d2bd6687858f4ace9617a97"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a72387040065b7cdcd1ab4b8068fd6b50"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> +<tr class="memitem:a72387040065b7cdcd1ab4b8068fd6b50"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 2 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#a72387040065b7cdcd1ab4b8068fd6b50">FullyConnectedLargeTestCommon</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory, bool transposeWeights, float qScale=0.0f, int32_t qOffset=0)</td></tr> +<tr class="separator:a72387040065b7cdcd1ab4b8068fd6b50"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:af9604ac7a7dd9965d3ef5d812eb57488"><td class="memItemLeft" align="right" valign="top">template <a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< <a class="el" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a>< <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a> >, 2 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#af9604ac7a7dd9965d3ef5d812eb57488">FullyConnectedTest< armnn::DataType::QAsymmU8 ></a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory, bool biasEnabled, bool constWeights)</td></tr> +<tr class="separator:af9604ac7a7dd9965d3ef5d812eb57488"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a9e126f757ea9bff73bb810ad79fa6df3"><td class="memItemLeft" align="right" valign="top">template <a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< <a class="el" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a>< <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a> >, 2 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#a9e126f757ea9bff73bb810ad79fa6df3">FullyConnectedTest< armnn::DataType::QSymmS16 ></a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory, bool biasEnabled, bool constWeights)</td></tr> +<tr class="separator:a9e126f757ea9bff73bb810ad79fa6df3"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:afb505feb224a201164ab815b8a6159cf"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 2 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#afb505feb224a201164ab815b8a6159cf">FullyConnectedFloat32Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory, bool biasEnabled, bool transposeWeights)</td></tr> +<tr class="separator:afb505feb224a201164ab815b8a6159cf"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aa50f043364dd453338261e82397c3e1b"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 2 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_fully_connected_test_impl_8cpp.xhtml#aa50f043364dd453338261e82397c3e1b">FullyConnectedLargeTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory, bool transposeWeights)</td></tr> +<tr class="separator:aa50f043364dd453338261e82397c3e1b"><td class="memSeparator" colspan="2"> </td></tr> +</table> +<h2 class="groupheader">Function Documentation</h2> +<a id="afb505feb224a201164ab815b8a6159cf"></a> +<h2 class="memtitle"><span class="permalink"><a href="#afb505feb224a201164ab815b8a6159cf">◆ </a></span>FullyConnectedFloat32Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 2> FullyConnectedFloat32Test </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>transposeWeights</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml#l00280">280</a> of file <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml">FullyConnectedTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00053">LayerTestResult< T, n >::m_ExpectedData</a>, and <a class="el" href="_descriptors_8cpp_source.xhtml#l00350">armnn::swap()</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_cl_layer_tests_8cpp_source.xhtml#l00027">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> {</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 1;</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 1;</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 5;</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputNum = 2;</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> </div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = 3;</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputNum = 2;</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="comment">// Define the tensor descriptors.</span></div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsDesc;</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesDesc;</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> </div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { inputNum, inputChannels, inputHeight, inputWidth };</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { outputNum, outputChannels };</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { inputChannels, outputChannels };</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">if</span> (transposeWeights)</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  {</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <a class="code" href="namespacearmnn.xhtml#a14d7f180bf51e86850305965c3707e07">std::swap</a>(weightsShape[0], weightsShape[1]);</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  }</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> </div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> biasShape[] = { outputChannels };</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> </div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  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="l00313"></a><span class="lineno"> 313</span>  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="l00314"></a><span class="lineno"> 314</span>  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="l00315"></a><span class="lineno"> 315</span>  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="l00316"></a><span class="lineno"> 316</span> </div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 2></a> result(outputTensorInfo);</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> </div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  std::vector<float> input =</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  {</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  1.0f, 2.0f, 3.0f, 4.0f, 5.0f,</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  5.0f, 4.0f, 3.0f, 2.0f, 1.0f</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  };</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span> </div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  std::vector<float> weights =</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  {</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  .5f, 2.f, .5f,</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  .5f, 2.f, 1.f,</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  .5f, 2.f, 2.f,</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  .5f, 2.f, 3.f,</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  .5f, 2.f, 4.f</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  };</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> </div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">if</span> (transposeWeights)</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  {</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  weights =</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  {</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  .5f, .5f, .5f, .5f, .5f,</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  2.f, 2.f, 2.f, 2.f, 2.f,</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  .5f, 1.f, 2.f, 3.f, 4.f</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  };</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  }</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span> </div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  std::vector<float> biasValues({0.f, 0.f, 0.f});</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  {</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  biasValues = std::vector<float>({10.f, 20.f, 30.f});</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  }</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> </div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  result = SimpleFullyConnectedTestImpl<float>(</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  workloadFactory,</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  memoryManager,</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  tensorHandleFactory,</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  inputTensorInfo, outputTensorInfo,</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  weightsDesc, biasesDesc,</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  weights, biasValues, input,</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  biasEnabled, transposeWeights, true</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  );</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span> </div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  std::vector<float> expectedOutput =</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  {</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  0.5f + 1.0f + 1.5f + 2.0f + 2.5f + biasValues[0],</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  2.0f + 4.0f + 6.0f + 8.0f + 10.f + biasValues[1],</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  0.5f + 2.0f + 6.0f + 12.f + 20.f + biasValues[2],</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span> </div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  2.5f + 2.0f + 1.5f + 1.0f + 0.5f + biasValues[0],</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  10.0f + 8.0f + 6.0f + 4.0f + 2.f + biasValues[1],</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  2.5f + 4.0f + 6.0f + 6.f + 4.f + biasValues[2]</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  };</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  result.m_ExpectedData = expectedOutput;</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span> </div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> }</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 &first, OriginsDescriptor &second)</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.xhtml#l00350">Descriptors.cpp:350</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="aa50f043364dd453338261e82397c3e1b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aa50f043364dd453338261e82397c3e1b">◆ </a></span>FullyConnectedLargeTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 2> FullyConnectedLargeTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>transposeWeights</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml#l00375">375</a> of file <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml">FullyConnectedTestImpl.cpp</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_cl_layer_tests_8cpp_source.xhtml#l00027">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> {</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keywordflow">return</span> FullyConnectedLargeTestCommon<armnn::DataType::Float32>(workloadFactory,</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  memoryManager,</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  tensorHandleFactory,</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  transposeWeights);</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a72387040065b7cdcd1ab4b8068fd6b50"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a72387040065b7cdcd1ab4b8068fd6b50">◆ </a></span>FullyConnectedLargeTestCommon()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 2> FullyConnectedLargeTestCommon </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>transposeWeights</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">float </td> + <td class="paramname"><em>qScale</em> = <code>0.0f</code>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">int32_t </td> + <td class="paramname"><em>qOffset</em> = <code>0</code> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml#l00179">179</a> of file <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml">FullyConnectedTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00053">LayerTestResult< T, n >::m_ExpectedData</a>, <a class="el" href="_tensor_8cpp_source.xhtml#l00491">TensorInfo::SetQuantizationOffset()</a>, <a class="el" href="_tensor_8cpp_source.xhtml#l00475">TensorInfo::SetQuantizationScale()</a>, and <a class="el" href="_descriptors_8cpp_source.xhtml#l00350">armnn::swap()</a>.</p> +<div class="fragment"><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> {</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 1;</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 1;</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 5;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputNum = 1;</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> </div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = 1;</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputNum = 1;</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> </div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="comment">// Define the tensor descriptors.</span></div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsDesc;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesDesc;</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { inputNum, inputChannels, inputHeight, inputWidth };</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { outputNum, outputChannels };</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> weightsShape[] = { inputChannels, outputChannels };</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keywordflow">if</span> (transposeWeights)</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  {</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <a class="code" href="namespacearmnn.xhtml#a14d7f180bf51e86850305965c3707e07">std::swap</a>(weightsShape[0], weightsShape[1]);</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  }</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> </div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> biasShape[] = { outputChannels };</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> </div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, inputShape, ArmnnType);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(2, outputShape, ArmnnType);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  weightsDesc = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(2, weightsShape, ArmnnType);</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  biasesDesc = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(1, biasShape, ArmnnType);</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="keywordflow">if</span>(armnn::IsQuantizedType<T>())</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  {</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  }</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> </div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 2></a> result(outputTensorInfo);</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  std::vector<T> input = armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  {</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  1.0f, 10.0f, 100.0f, 1000.0f, 10000.0f,</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  },</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  qScale, qOffset);</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> </div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  std::vector<T> weights = armnnUtils::QuantizedVector<T>(</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  {</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  2.0f, 3.0f, 4.0f, 5.0f, 6.0f</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  },</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  qScale, qOffset);</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  std::vector<T> biasValues({900000.f});</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  result = SimpleFullyConnectedTestImpl<T>(</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  workloadFactory,</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  memoryManager,</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  tensorHandleFactory,</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  inputTensorInfo, outputTensorInfo,</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  weightsDesc, biasesDesc,</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  weights, biasValues, input,</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="keyword">true</span>, transposeWeights, true</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  );</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> </div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  result.m_ExpectedData = armnnUtils::QuantizedVector<T>({ 965432.0f }, qScale, qOffset);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> </div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> }</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 &first, OriginsDescriptor &second)</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.xhtml#l00350">Descriptors.cpp:350</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="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#l00475">Tensor.cpp:475</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<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#l00491">Tensor.cpp:491</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a59a2fc917d2bd6687858f4ace9617a97"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a59a2fc917d2bd6687858f4ace9617a97">◆ </a></span>FullyConnectedTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 2> FullyConnectedTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>constantWeights</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml#l00097">97</a> of file <a class="el" href="_fully_connected_test_impl_8cpp_source.xhtml">FullyConnectedTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_layer_support_rules_8hpp_source.xhtml#l00014">armnn::GetBiasTypeFromWeightsType()</a>, <a class="el" href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00053">LayerTestResult< T, n >::m_ExpectedData</a>, and <a class="el" href="_tensor_8cpp_source.xhtml#l00475">TensorInfo::SetQuantizationScale()</a>.</p> +<div class="fragment"><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> {</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 3u;</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 2u;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 1u;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  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="l00109"></a><span class="lineno"> 109</span> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = 2u;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <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="l00113"></a><span class="lineno"> 113</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(0.1f);</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  inputTensorInfo.SetQuantizationOffset(63);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> </div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, outputChannels }, ArmnnType);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(5.f);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  outputTensorInfo.SetQuantizationOffset(biasEnabled ? -50 : 10);</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsDesc({ outputChannels, inputSize }, ArmnnType);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  weightsDesc.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(0.2f);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  weightsDesc.SetQuantizationOffset(93);</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesDesc({ outputChannels }, <a class="code" href="namespacearmnn.xhtml#ada0fb4f79f3673b4ebd94a42175bf78d">GetBiasTypeFromWeightsType</a>(weightsDesc.GetDataType()).value());</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  biasesDesc.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(inputTensorInfo.GetQuantizationScale() * weightsDesc.GetQuantizationScale());</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  biasesDesc.SetQuantizationOffset(0);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 2></a> result(outputTensorInfo);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  std::vector<T> input = ConvertToDataType<ArmnnType>(</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  {</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  -1.2f, 6.1f, -3.5f,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  18.8f, -5.5f, 2.9f</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  },</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  inputTensorInfo);</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  std::vector<T> weights = ConvertToDataType<ArmnnType>(</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  {</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  -8.4f, 20.0f, -10.4f, -8, 16.4f, -11.8f,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  23.4f, 10.4f, -14.0f, -3.8f, -11.8f, 11.4f</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  },</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  weightsDesc);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> </div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  std::vector<int32_t> bias = {9250, 67500};</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> </div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  result = SimpleFullyConnectedTestImpl<T>(workloadFactory,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  memoryManager,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  tensorHandleFactory,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  inputTensorInfo,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  outputTensorInfo,</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  weightsDesc,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  biasesDesc,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  weights,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  bias,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  input,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  biasEnabled,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keyword">true</span>,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  constantWeights);</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> </div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  {</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  result.m_ExpectedData = ConvertToDataType<ArmnnType>({80.f, 1460.f}, outputTensorInfo);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  }</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  {</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  result.m_ExpectedData = ConvertToDataType<ArmnnType>({-107.04f, 110.f}, outputTensorInfo);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  }</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ada0fb4f79f3673b4ebd94a42175bf78d"><div class="ttname"><a href="namespacearmnn.xhtml#ada0fb4f79f3673b4ebd94a42175bf78d">armnn::GetBiasTypeFromWeightsType</a></div><div class="ttdeci">armnn::Optional< armnn::DataType > GetBiasTypeFromWeightsType(armnn::Optional< armnn::DataType > weightsType)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_support_rules_8hpp_source.xhtml#l00014">LayerSupportRules.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00475">Tensor.cpp:475</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="af9604ac7a7dd9965d3ef5d812eb57488"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af9604ac7a7dd9965d3ef5d812eb57488">◆ </a></span>FullyConnectedTest< armnn::DataType::QAsymmU8 >()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">template <a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><<a class="el" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a><<a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>>, 2> <a class="el" href="_fully_connected_test_impl_8hpp.xhtml#a59a2fc917d2bd6687858f4ace9617a97">FullyConnectedTest</a>< <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a> > </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>constWeights</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +</div> +</div> +<a id="a9e126f757ea9bff73bb810ad79fa6df3"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a9e126f757ea9bff73bb810ad79fa6df3">◆ </a></span>FullyConnectedTest< armnn::DataType::QSymmS16 >()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname">template <a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><<a class="el" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a><<a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>>, 2> <a class="el" href="_fully_connected_test_impl_8hpp.xhtml#a59a2fc917d2bd6687858f4ace9617a97">FullyConnectedTest</a>< <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a> > </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>constWeights</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +</div> +</div> +<a id="af8f4ed2106c6aaf93ac0be43348a19da"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af8f4ed2106c6aaf93ac0be43348a19da">◆ </a></span>SimpleFullyConnectedTestImpl()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 2> SimpleFullyConnectedTestImpl </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> </td> + <td class="paramname"><em>inputTensorInfo</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> </td> + <td class="paramname"><em>outputTensorInfo</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> </td> + <td class="paramname"><em>weightsTensorInfo</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> </td> + <td class="paramname"><em>biasesTensorInfo</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">std::vector< T > & </td> + <td class="paramname"><em>weights</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">std::vector< B > & </td> + <td class="paramname"><em>bias</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">std::vector< T > & </td> + <td class="paramname"><em>input</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>transposeWeights</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">bool </td> + <td class="paramname"><em>constantWeights</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_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> + +<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="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01541">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e">armnn::FullyConnected</a>, <a class="el" href="_tensor_8hpp_source.xhtml#l00196">TensorInfo::GetNumElements()</a>, and <a class="el" href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00052">LayerTestResult< T, n >::m_ActualData</a>.</p> +<div class="fragment"><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> {</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  std::unique_ptr<armnn::ITensorHandle> input0Handle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  std::unique_ptr<armnn::ITensorHandle> input1Handle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(weightsTensorInfo);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  std::vector<T> actualOutput(outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <a class="code" href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml">armnn::FullyConnectedQueueDescriptor</a> data;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> weightsTensor(weightsTensorInfo);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> biasTensor(biasesTensorInfo);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&weightsTensor, weights.data());</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&biasTensor, bias.data());</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> </div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  AddInputToWorkload(data, info, inputTensorInfo, input0Handle.get());</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  AddInputToWorkload(data, info, weightsTensorInfo, input1Handle.get());</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// Need to set as layer members will be null when creating the workload because the optimization hasn't been run.</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  data.m_Weight = &weightsTensor;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  data.m_Bias = &biasTensor;</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  data.m_Parameters.m_BiasEnabled = biasEnabled;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  data.m_Parameters.m_TransposeWeightMatrix = transposeWeights;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  data.m_Parameters.m_ConstantWeights = constantWeights;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  std::unique_ptr<armnn::ITensorHandle> input2Handle = <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  {</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  input2Handle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(biasesTensorInfo);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  AddInputToWorkload(data, info, biasesTensorInfo, input2Handle.get());</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  }</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e">armnn::LayerType::FullyConnected</a>,</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  data,</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  info);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 2></a> result(outputTensorInfo);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  input0Handle->Allocate();</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  input1Handle->Allocate();</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  outputHandle->Allocate();</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(input0Handle.get(), input.data());</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(input1Handle.get(), weights.data());</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordflow">if</span> (biasEnabled)</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  {</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  input2Handle->Allocate();</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(input2Handle.get(), bias.data());</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  }</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  ExecuteWorkload(*workload, memoryManager);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  result.m_ActualData = actualOutput;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> }</div><div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acab78faff25393e9defd1911cb58133e">armnn::LayerType::FullyConnected</a></div></div> +<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="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00168">WorkloadData.hpp:168</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.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> +<div class="ttc" id="classarmnn_1_1_scoped_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml#l00115">TensorHandle.hpp:115</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ab5dfed8358e500ed523d78090ec78e88"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="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 TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a13060ebb89d2c21a7a5d897e99cccf72"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01541">WorkloadFactory.cpp:1541</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00196">Tensor.hpp:196</a></div></div> +</div><!-- fragment --> +</div> +</div> +</div><!-- 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