diff options
| author | Ryan OShea <Ryan.OShea2@arm.com> | 2020-08-25 12:35:58 +0100 |
|---|---|---|
| committer | Ryan OShea <Ryan.OShea2@arm.com> | 2020-08-25 12:35:58 +0100 |
| commit | 4840dfb7543d66652dc11c5ff39c8f5c1e2f9370 (patch) | |
| tree | e4fe9fc2d0f003ac939fdb085de2c21b64dd66fc /20.08/_conv2d_test_impl_8hpp.xhtml | |
| parent | a983e4699082a0b1ef685bab7354f2ad9cd37a44 (diff) | |
| download | armnn-4840dfb7543d66652dc11c5ff39c8f5c1e2f9370.tar.gz | |
Updating Doxygen Documentation for 20.08 release
Signed-off-by: Ryan OShea <Ryan.OShea2@arm.com>
Change-Id: I605409f8720de5353feceb161b39f8a5f0598180
Diffstat (limited to '20.08/_conv2d_test_impl_8hpp.xhtml')
| -rw-r--r-- | 20.08/_conv2d_test_impl_8hpp.xhtml | 1782 |
1 files changed, 1782 insertions, 0 deletions
diff --git a/20.08/_conv2d_test_impl_8hpp.xhtml b/20.08/_conv2d_test_impl_8hpp.xhtml new file mode 100644 index 0000000000..891dbc8fa7 --- /dev/null +++ b/20.08/_conv2d_test_impl_8hpp.xhtml @@ -0,0 +1,1782 @@ +<!-- 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/Conv2dTestImpl.hpp File Reference</title> +<link href="tabs.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="jquery.js"></script> +<script type="text/javascript" src="dynsections.js"></script> +<link href="navtree.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="resize.js"></script> +<script type="text/javascript" src="navtreedata.js"></script> +<script type="text/javascript" src="navtree.js"></script> +<script type="text/javascript"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">20.08</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_conv2d_test_impl_8hpp.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">Conv2dTestImpl.hpp File Reference</div> </div> +</div><!--header--> +<div class="contents"> +<div class="textblock"><code>#include "<a class="el" href="_layer_test_result_8hpp_source.xhtml">LayerTestResult.hpp</a>"</code><br /> +<code>#include <<a class="el" href="_resolve_type_8hpp_source.xhtml">ResolveType.hpp</a>></code><br /> +<code>#include <<a class="el" href="_types_8hpp_source.xhtml">armnn/Types.hpp</a>></code><br /> +<code>#include <<a class="el" href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.xhtml">armnn/backends/IBackendInternal.hpp</a>></code><br /> +<code>#include <<a class="el" href="_workload_factory_8hpp_source.xhtml">backendsCommon/WorkloadFactory.hpp</a>></code><br /> +</div> +<p><a href="_conv2d_test_impl_8hpp_source.xhtml">Go to the source code of this file.</a></p> +<table class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> +Functions</h2></td></tr> +<tr class="memitem:a90abce368d7f16012bef5ee461329484"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> +<tr class="memitem:a90abce368d7f16012bef5ee461329484"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a90abce368d7f16012bef5ee461329484">Convolution2d3x3Dilation3x3Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a90abce368d7f16012bef5ee461329484"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a99ef3f48cbd057e0169bc80dc77331ef"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> +<tr class="memitem:a99ef3f48cbd057e0169bc80dc77331ef"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a99ef3f48cbd057e0169bc80dc77331ef">Convolution2d2x3x3Dilation3x3Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a99ef3f48cbd057e0169bc80dc77331ef"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:acf553288e3b5060768fb91e064993678"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> +<tr class="memitem:acf553288e3b5060768fb91e064993678"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#acf553288e3b5060768fb91e064993678">Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:acf553288e3b5060768fb91e064993678"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:afb5e7d86e241292d9cb899b960da54af"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#afb5e7d86e241292d9cb899b960da54af">SimpleConvolution2d3x5Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:afb5e7d86e241292d9cb899b960da54af"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:acbe1a2adccd9e0aad14fc0ccb9266b0d"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#acbe1a2adccd9e0aad14fc0ccb9266b0d">SimpleConvolution2d3x3Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:acbe1a2adccd9e0aad14fc0ccb9266b0d"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:af4ac6874d18e1cb59873a17073512873"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#af4ac6874d18e1cb59873a17073512873">SimpleConvolution2d3x3Stride2x2Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:af4ac6874d18e1cb59873a17073512873"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ac7bae01fdca8edac70cc9bc722426b17"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#ac7bae01fdca8edac70cc9bc722426b17">SimpleConvolution2d3x3NhwcTest</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, bool biasEnabled)</td></tr> +<tr class="separator:ac7bae01fdca8edac70cc9bc722426b17"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a8ffca1c4b38a68b10ba06f4f1416660f"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a8ffca1c4b38a68b10ba06f4f1416660f">SimpleConvolution2d3x5Uint8Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a8ffca1c4b38a68b10ba06f4f1416660f"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ad45f359d9d4bee360bee857faa79d292"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#ad45f359d9d4bee360bee857faa79d292">SimpleConvolution2d3x3Uint8Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:ad45f359d9d4bee360bee857faa79d292"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a9dcd2fb98f5c3284c74f65a7c7a69da1"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a9dcd2fb98f5c3284c74f65a7c7a69da1">SimpleConvolution2d3x5QSymm16Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a9dcd2fb98f5c3284c74f65a7c7a69da1"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:abac8f73ae590a93fe91115371ae4ced3"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#abac8f73ae590a93fe91115371ae4ced3">SimpleConvolution2d3x3QSymm16Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:abac8f73ae590a93fe91115371ae4ced3"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a48884a37a6b783185c608a68cfce752f"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a48884a37a6b783185c608a68cfce752f">Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest</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, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a48884a37a6b783185c608a68cfce752f"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:af7f2cd23423130ebdd916de12bc0eb1d"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#af7f2cd23423130ebdd916de12bc0eb1d">Convolution2dAsymmetricPaddingTest</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, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:af7f2cd23423130ebdd916de12bc0eb1d"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ac7fac5767dabd650d3d8829572717064"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#ac7fac5767dabd650d3d8829572717064">Convolution1dTest</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, bool biasEnabled)</td></tr> +<tr class="separator:ac7fac5767dabd650d3d8829572717064"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a40bc412ed2a6d2f764655070c02c036b"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a40bc412ed2a6d2f764655070c02c036b">Convolution1dUint8Test</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, bool biasEnabled)</td></tr> +<tr class="separator:a40bc412ed2a6d2f764655070c02c036b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a15fe73bad57133008945807f7a5b4783"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a15fe73bad57133008945807f7a5b4783">CompareConvolution2dTest</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, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &refWorkloadFactory)</td></tr> +<tr class="separator:a15fe73bad57133008945807f7a5b4783"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a370a5216668b507284677234264a22a2"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a370a5216668b507284677234264a22a2">Convolution2dPerAxisQuantTest</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="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a370a5216668b507284677234264a22a2"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a8220b8330608ebcaf3edeb75c8988373"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a8220b8330608ebcaf3edeb75c8988373">Convolution2d3x3Stride2x2BFloat16Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> &dataLayout)</td></tr> +<tr class="separator:a8220b8330608ebcaf3edeb75c8988373"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a9708e5256eebe1d658aadf2a9da7476b"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a9708e5256eebe1d658aadf2a9da7476b">Convolution2d3x3Stride2x2BFloat16SmallValueTest</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> &dataLayout)</td></tr> +<tr class="separator:a9708e5256eebe1d658aadf2a9da7476b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a1c3398bdb48e4ce4643a1eeaf3e054a3"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> +<tr class="memitem:a1c3398bdb48e4ce4643a1eeaf3e054a3"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a1c3398bdb48e4ce4643a1eeaf3e054a3">DepthwiseConvolution2d3x3Dilation3x3Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a1c3398bdb48e4ce4643a1eeaf3e054a3"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:acffa50ae3185e3e5302909f27e7e9a02"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> +<tr class="memitem:acffa50ae3185e3e5302909f27e7e9a02"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#acffa50ae3185e3e5302909f27e7e9a02">DepthwiseConvolution2d2x3x3Dilation3x3Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:acffa50ae3185e3e5302909f27e7e9a02"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a0da6534b3a5d2f923dcd73553950129a"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> +<tr class="memitem:a0da6534b3a5d2f923dcd73553950129a"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a0da6534b3a5d2f923dcd73553950129a">DepthwiseConvolution2dMult4Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a0da6534b3a5d2f923dcd73553950129a"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:aaed50a372a6b59b20e38469856a3ce6b"><td class="memTemplParams" colspan="2">template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>> </td></tr> +<tr class="memitem:aaed50a372a6b59b20e38469856a3ce6b"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#aaed50a372a6b59b20e38469856a3ce6b">DepthwiseConvolution2dMult2Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:aaed50a372a6b59b20e38469856a3ce6b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a12fec2055d0e4a18d1e0db589a969e41"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> +<tr class="memitem:a12fec2055d0e4a18d1e0db589a969e41"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< T, 4 > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a12fec2055d0e4a18d1e0db589a969e41">CompareDepthwiseConvolution2dTest</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, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &refWorkloadFactory, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a12fec2055d0e4a18d1e0db589a969e41"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a11fbd94028ab646528b42d0c8c55eee1"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a11fbd94028ab646528b42d0c8c55eee1">DepthwiseConvolution2dTest</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a11fbd94028ab646528b42d0c8c55eee1"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a0cccb5cffee89004bc8d9fb309ed6636"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a0cccb5cffee89004bc8d9fb309ed6636">DepthwiseConvolution2dDepthNhwcTest</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, bool biasEnabled)</td></tr> +<tr class="separator:a0cccb5cffee89004bc8d9fb309ed6636"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a8b32d950a40903f502f5e1ec0dcab0bd"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a8b32d950a40903f502f5e1ec0dcab0bd">DepthwiseConvolution2dDepthMul1Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a8b32d950a40903f502f5e1ec0dcab0bd"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ab020b4a99bf905b61a1c5e03332b63a6"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#ab020b4a99bf905b61a1c5e03332b63a6">DepthwiseConvolution2dDepthMul64Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> +<tr class="separator:ab020b4a99bf905b61a1c5e03332b63a6"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:abf326cbf49ec19c6272fe7c244b7817c"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#abf326cbf49ec19c6272fe7c244b7817c">DepthwiseConvolution2dAsymmetricTest</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:abf326cbf49ec19c6272fe7c244b7817c"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a77a29527216d36bce78e88354462ede8"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a77a29527216d36bce78e88354462ede8">SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager)</td></tr> +<tr class="separator:a77a29527216d36bce78e88354462ede8"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a8076c31bd6e9eae629994a89a5fa18c3"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a8076c31bd6e9eae629994a89a5fa18c3">DepthwiseConvolution2dUint8Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a8076c31bd6e9eae629994a89a5fa18c3"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ae797be34b659db2afe183f0c762fb9b7"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#ae797be34b659db2afe183f0c762fb9b7">DepthwiseConvolution2dDepthMul1Uint8Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:ae797be34b659db2afe183f0c762fb9b7"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a2ae97c2dd6621f4972c571cf1ec2a005"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a2ae97c2dd6621f4972c571cf1ec2a005">DepthwiseConvolution2dInt16Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a2ae97c2dd6621f4972c571cf1ec2a005"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a74346a72d64f7fa3463473424c3098ab"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< int16_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a74346a72d64f7fa3463473424c3098ab">DepthwiseConvolution2dDepthMul1Int16Test</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, bool biasEnabled, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a74346a72d64f7fa3463473424c3098ab"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a8a51827c480f827c1e29f9347d7433c3"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a8a51827c480f827c1e29f9347d7433c3">DepthwiseConvolution2dPerAxisQuantTest</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="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a8a51827c480f827c1e29f9347d7433c3"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a09705f5e38cfc0d5bccc64791eb4f231"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a09705f5e38cfc0d5bccc64791eb4f231">CompareDepthwiseConvolution2dFloatTest</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, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &refWorkloadFactory, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a09705f5e38cfc0d5bccc64791eb4f231"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a21af5850bca4df2ea0315afb407e7900"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< uint8_t, 4 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_conv2d_test_impl_8hpp.xhtml#a21af5850bca4df2ea0315afb407e7900">CompareDepthwiseConvolution2dUint8Test</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, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &refWorkloadFactory, const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> layout)</td></tr> +<tr class="separator:a21af5850bca4df2ea0315afb407e7900"><td class="memSeparator" colspan="2"> </td></tr> +</table> +<h2 class="groupheader">Function Documentation</h2> +<a id="a15fe73bad57133008945807f7a5b4783"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a15fe73bad57133008945807f7a5b4783">◆ </a></span>CompareConvolution2dTest()</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, 4> CompareConvolution2dTest </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"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>refWorkloadFactory</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="_conv2d_test_impl_8cpp_source.xhtml#l03440">3440</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03444"></a><span class="lineno"> 3444</span> {</div><div class="line"><a name="l03445"></a><span class="lineno"> 3445</span>  <span class="keywordflow">return</span> CompareConvolution2dTestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l03446"></a><span class="lineno"> 3446</span>  workloadFactory, memoryManager, refWorkloadFactory);</div><div class="line"><a name="l03447"></a><span class="lineno"> 3447</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a09705f5e38cfc0d5bccc64791eb4f231"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a09705f5e38cfc0d5bccc64791eb4f231">◆ </a></span>CompareDepthwiseConvolution2dFloatTest()</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, 4> CompareDepthwiseConvolution2dFloatTest </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"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>refWorkloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03682">3682</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03687"></a><span class="lineno"> 3687</span> {</div><div class="line"><a name="l03688"></a><span class="lineno"> 3688</span>  <span class="keywordflow">return</span> CompareDepthwiseConvolution2dTestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l03689"></a><span class="lineno"> 3689</span>  workloadFactory, memoryManager, refWorkloadFactory, layout);</div><div class="line"><a name="l03690"></a><span class="lineno"> 3690</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a12fec2055d0e4a18d1e0db589a969e41"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a12fec2055d0e4a18d1e0db589a969e41">◆ </a></span>CompareDepthwiseConvolution2dTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> CompareDepthwiseConvolution2dTest </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"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>refWorkloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +</div> +</div> +<a id="a21af5850bca4df2ea0315afb407e7900"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a21af5850bca4df2ea0315afb407e7900">◆ </a></span>CompareDepthwiseConvolution2dUint8Test()</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><uint8_t, 4> CompareDepthwiseConvolution2dUint8Test </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"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>refWorkloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03692">3692</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03697"></a><span class="lineno"> 3697</span> {</div><div class="line"><a name="l03698"></a><span class="lineno"> 3698</span>  <span class="keywordflow">return</span> CompareDepthwiseConvolution2dTestImpl<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l03699"></a><span class="lineno"> 3699</span>  workloadFactory, memoryManager, refWorkloadFactory, layout);</div><div class="line"><a name="l03700"></a><span class="lineno"> 3700</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="ac7fac5767dabd650d3d8829572717064"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ac7fac5767dabd650d3d8829572717064">◆ </a></span>Convolution1dTest()</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, 4> Convolution1dTest </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">bool </td> + <td class="paramname"><em>biasEnabled</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="_conv2d_test_impl_8cpp_source.xhtml#l03328">3328</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03332"></a><span class="lineno"> 3332</span> {</div><div class="line"><a name="l03333"></a><span class="lineno"> 3333</span>  <span class="keywordflow">return</span> Convolution1dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l03334"></a><span class="lineno"> 3334</span>  workloadFactory, memoryManager, 0.0f, 0, biasEnabled);</div><div class="line"><a name="l03335"></a><span class="lineno"> 3335</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a40bc412ed2a6d2f764655070c02c036b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a40bc412ed2a6d2f764655070c02c036b">◆ </a></span>Convolution1dUint8Test()</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><uint8_t, 4> Convolution1dUint8Test </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">bool </td> + <td class="paramname"><em>biasEnabled</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="_conv2d_test_impl_8cpp_source.xhtml#l03337">3337</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03341"></a><span class="lineno"> 3341</span> {</div><div class="line"><a name="l03342"></a><span class="lineno"> 3342</span>  <span class="keywordflow">return</span> Convolution1dTestImpl<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>(</div><div class="line"><a name="l03343"></a><span class="lineno"> 3343</span>  workloadFactory, memoryManager, 0.1f, 128, biasEnabled);</div><div class="line"><a name="l03344"></a><span class="lineno"> 3344</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="acf553288e3b5060768fb91e064993678"></a> +<h2 class="memtitle"><span class="permalink"><a href="#acf553288e3b5060768fb91e064993678">◆ </a></span>Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l01212">1212</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l01217"></a><span class="lineno"> 1217</span> {</div><div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({1, 1, 10, 10}, ArmnnType);</div><div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>  std::vector<float> inputNoQuantizedValues =</div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  {</div><div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>  1, 1, 1, 1, 1, 1, 1, 1, 1, 1,</div><div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  1, 1, 1, 1, 1, 1, 1, 1, 1, 1,</div><div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>  1, 1, 1, 1, 1, 1, 1, 1, 1, 1,</div><div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>  1, 1, 1, 1, 1, 1, 1, 1, 1, 1,</div><div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>  1, 1, 1, 1, 1, 1, 1, 1, 1, 1,</div><div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>  1, 1, 1, 1, 1, 1, 1, 1, 1, 1,</div><div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>  1, 1, 1, 1, 1, 1, 1, 1, 1, 1,</div><div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  1, 1, 1, 1, 1, 1, 1, 1, 1, 1,</div><div class="line"><a name="l01229"></a><span class="lineno"> 1229</span>  1, 1, 1, 1, 1, 1, 1, 1, 1, 1,</div><div class="line"><a name="l01230"></a><span class="lineno"> 1230</span>  1, 1, 1, 1, 1, 1, 1, 1, 1, 1</div><div class="line"><a name="l01231"></a><span class="lineno"> 1231</span>  };</div><div class="line"><a name="l01232"></a><span class="lineno"> 1232</span> </div><div class="line"><a name="l01233"></a><span class="lineno"> 1233</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelTensorInfo({ 1, 1, 2, 2}, ArmnnType);</div><div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>  std::vector<float> kernelNoQuantizedValues =</div><div class="line"><a name="l01235"></a><span class="lineno"> 1235</span>  {</div><div class="line"><a name="l01236"></a><span class="lineno"> 1236</span>  1, 2,</div><div class="line"><a name="l01237"></a><span class="lineno"> 1237</span>  3, 4</div><div class="line"><a name="l01238"></a><span class="lineno"> 1238</span>  };</div><div class="line"><a name="l01239"></a><span class="lineno"> 1239</span> </div><div class="line"><a name="l01240"></a><span class="lineno"> 1240</span>  <span class="comment">// Since the dilation rate is 2 this will dilate the kernel to be like 3x3: d(K-1)+1 --> 2 x (2-1) + 1 = 3,</span></div><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>  <span class="comment">// therefore the output will be 4x4: (I − K + 2P)/S +1 => trunc ( (10 - 3 + 2x2 ) / 3 + 1 )</span></div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>  <span class="comment">// where, dilation size = d = 2; kernel size = K = 2; input size = I = 10; padding size = P = 2; stride = S = 3</span></div><div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, 1, 4, 4}, ArmnnType);</div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>  std::vector<float> outputExpectedNoQuantizedValues =</div><div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>  {</div><div class="line"><a name="l01246"></a><span class="lineno"> 1246</span>  4, 7, 7, 3,</div><div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>  6, 10, 10, 4,</div><div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>  6, 10, 10, 4,</div><div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>  2, 3, 3, 1</div><div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>  };</div><div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>  uint32_t padLeft = 1;</div><div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>  uint32_t padTop = 1;</div><div class="line"><a name="l01253"></a><span class="lineno"> 1253</span>  uint32_t padRight = 1;</div><div class="line"><a name="l01254"></a><span class="lineno"> 1254</span>  uint32_t padBottom = 1;</div><div class="line"><a name="l01255"></a><span class="lineno"> 1255</span> </div><div class="line"><a name="l01256"></a><span class="lineno"> 1256</span>  <span class="keywordflow">return</span> Convolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>  workloadFactory,</div><div class="line"><a name="l01258"></a><span class="lineno"> 1258</span>  memoryManager,</div><div class="line"><a name="l01259"></a><span class="lineno"> 1259</span>  inputNoQuantizedValues,</div><div class="line"><a name="l01260"></a><span class="lineno"> 1260</span>  inputTensorInfo,</div><div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>  kernelNoQuantizedValues,</div><div class="line"><a name="l01262"></a><span class="lineno"> 1262</span>  kernelTensorInfo,</div><div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>  outputExpectedNoQuantizedValues,</div><div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>  outputTensorInfo,</div><div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>  2,</div><div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>  2,</div><div class="line"><a name="l01267"></a><span class="lineno"> 1267</span>  layout,</div><div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>  padLeft,</div><div class="line"><a name="l01269"></a><span class="lineno"> 1269</span>  padTop,</div><div class="line"><a name="l01270"></a><span class="lineno"> 1270</span>  padRight,</div><div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>  padBottom,</div><div class="line"><a name="l01272"></a><span class="lineno"> 1272</span>  3,</div><div class="line"><a name="l01273"></a><span class="lineno"> 1273</span>  3,</div><div class="line"><a name="l01274"></a><span class="lineno"> 1274</span>  biasEnabled</div><div class="line"><a name="l01275"></a><span class="lineno"> 1275</span>  );</div><div class="line"><a name="l01276"></a><span class="lineno"> 1276</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><!-- fragment --> +</div> +</div> +<a id="a99ef3f48cbd057e0169bc80dc77331ef"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a99ef3f48cbd057e0169bc80dc77331ef">◆ </a></span>Convolution2d2x3x3Dilation3x3Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> Convolution2d2x3x3Dilation3x3Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l01141">1141</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l01146"></a><span class="lineno"> 1146</span> {</div><div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({1, 2, 10, 10}, ArmnnType);</div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>  std::vector<float> inputNoQuantizedValues =</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>  {</div><div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span> </div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0</div><div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>  };</div><div class="line"><a name="l01172"></a><span class="lineno"> 1172</span> </div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelTensorInfo({ 1, 2, 3, 3}, ArmnnType);</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  std::vector<float> kernelNoQuantizedValues =</div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>  {</div><div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>  1, 2, 3,</div><div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>  4, 5, 6,</div><div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>  7, 8, 9,</div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span> </div><div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  1, 2, 3,</div><div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>  4, 5, 6,</div><div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>  7, 8, 9</div><div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>  };</div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span> </div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>  <span class="comment">// Since the dilation rate is 3 this will dilate the kernel to be like 7x7,</span></div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  <span class="comment">// therefore the output will be 4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1</span></div><div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, 1, 4, 4}, ArmnnType);</div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>  std::vector<float> outputExpectedNoQuantizedValues =</div><div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>  {</div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>  12., 10., 10., 10.,</div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>  12., 10., 10., 10.,</div><div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>  12., 10., 10., 10.,</div><div class="line"><a name="l01193"></a><span class="lineno"> 1193</span>  6., 4., 4., 4.</div><div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>  };</div><div class="line"><a name="l01195"></a><span class="lineno"> 1195</span> </div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>  <span class="keywordflow">return</span> Convolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  workloadFactory,</div><div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>  memoryManager,</div><div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>  inputNoQuantizedValues,</div><div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>  inputTensorInfo,</div><div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>  kernelNoQuantizedValues,</div><div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>  kernelTensorInfo,</div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>  outputExpectedNoQuantizedValues,</div><div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  outputTensorInfo,</div><div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>  3,</div><div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>  3,</div><div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  layout,</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>  biasEnabled);</div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</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><!-- fragment --> +</div> +</div> +<a id="a90abce368d7f16012bef5ee461329484"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a90abce368d7f16012bef5ee461329484">◆ </a></span>Convolution2d3x3Dilation3x3Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> Convolution2d3x3Dilation3x3Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l01085">1085</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l01090"></a><span class="lineno"> 1090</span> {</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({1, 1, 10, 10}, ArmnnType);</div><div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>  std::vector<float> inputNoQuantizedValues =</div><div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>  {</div><div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0</div><div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>  };</div><div class="line"><a name="l01105"></a><span class="lineno"> 1105</span> </div><div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelTensorInfo({ 1, 1, 3, 3}, ArmnnType);</div><div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>  std::vector<float> kernelNoQuantizedValues =</div><div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>  {</div><div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>  1, 2, 3,</div><div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>  4, 5, 6,</div><div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  7, 8, 9</div><div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  };</div><div class="line"><a name="l01113"></a><span class="lineno"> 1113</span> </div><div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  <span class="comment">// Since the dilation rate is 3 this will dilate the kernel to be like 7x7,</span></div><div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>  <span class="comment">// therefore the output will be 4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1</span></div><div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, 1, 4, 4}, ArmnnType);</div><div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>  std::vector<float> outputExpectedNoQuantizedValues =</div><div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>  {</div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>  6., 5., 5., 5.,</div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  6., 5., 5., 5.,</div><div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>  6., 5., 5., 5.,</div><div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>  3., 2., 2., 2.</div><div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>  };</div><div class="line"><a name="l01124"></a><span class="lineno"> 1124</span> </div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  <span class="keywordflow">return</span> Convolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>  workloadFactory,</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>  memoryManager,</div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>  inputNoQuantizedValues,</div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>  inputTensorInfo,</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>  kernelNoQuantizedValues,</div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>  kernelTensorInfo,</div><div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>  outputExpectedNoQuantizedValues,</div><div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>  outputTensorInfo,</div><div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>  3,</div><div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>  3,</div><div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>  layout,</div><div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>  biasEnabled);</div><div class="line"><a name="l01138"></a><span class="lineno"> 1138</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><!-- fragment --> +</div> +</div> +<a id="a9708e5256eebe1d658aadf2a9da7476b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a9708e5256eebe1d658aadf2a9da7476b">◆ </a></span>Convolution2d3x3Stride2x2BFloat16SmallValueTest()</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, 4> Convolution2d3x3Stride2x2BFloat16SmallValueTest </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> & </td> + <td class="paramname"><em>dataLayout</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="_conv2d_test_impl_8cpp_source.xhtml#l01485">1485</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::BFloat16</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, and <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml#l00368">SimpleConvolution2dNhwcTestImpl()</a>.</p> +<div class="fragment"><div class="line"><a name="l01490"></a><span class="lineno"> 1490</span> {</div><div class="line"><a name="l01491"></a><span class="lineno"> 1491</span>  <span class="comment">// BFloat16 input and weight, Float32 output</span></div><div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a>(biasEnabled);</div><div class="line"><a name="l01493"></a><span class="lineno"> 1493</span> </div><div class="line"><a name="l01494"></a><span class="lineno"> 1494</span>  <span class="comment">// Input is a single-batch, 1 channel, 5x5 image.</span></div><div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputDesc({1, 5, 5, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>);</div><div class="line"><a name="l01496"></a><span class="lineno"> 1496</span> </div><div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>  std::vector<armnn::BFloat16> inputValues = armnnUtils::QuantizedVector<armnn::BFloat16>(</div><div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>  {</div><div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>  0.0367984f, <span class="comment">// 0.0368652</span></div><div class="line"><a name="l01500"></a><span class="lineno"> 1500</span>  0.0380895f, <span class="comment">// 0.0380859</span></div><div class="line"><a name="l01501"></a><span class="lineno"> 1501</span>  0.0420157f, <span class="comment">// 0.0419922</span></div><div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>  0.0675631f, <span class="comment">// 0.0673828</span></div><div class="line"><a name="l01503"></a><span class="lineno"> 1503</span>  0.0938920f, <span class="comment">// 0.09375</span></div><div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>  0.0476106f, <span class="comment">// 0.0476074</span></div><div class="line"><a name="l01505"></a><span class="lineno"> 1505</span>  0.1035490f, <span class="comment">// 0.103516</span></div><div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>  0.1260370f, <span class="comment">// 0.125977</span></div><div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>  0.0461647f, <span class="comment">// 0.0461426</span></div><div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>  0.0883828f, <span class="comment">// 0.0883789</span></div><div class="line"><a name="l01509"></a><span class="lineno"> 1509</span>  0.1159540f, <span class="comment">// 0.115723</span></div><div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>  0.0498519f, <span class="comment">// 0.0498047</span></div><div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>  0.0104630f, <span class="comment">// 0.010437</span></div><div class="line"><a name="l01512"></a><span class="lineno"> 1512</span>  0.0154114f, <span class="comment">// 0.0154419</span></div><div class="line"><a name="l01513"></a><span class="lineno"> 1513</span>  0.00137681f, <span class="comment">// 0.00137329</span></div><div class="line"><a name="l01514"></a><span class="lineno"> 1514</span>  0.0344238f, <span class="comment">// 0.0344616</span></div><div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>  0.0356445f, <span class="comment">// 0.0355693</span></div><div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>  0.0495605f, <span class="comment">// 0.0495018</span></div><div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>  0.0683594f, <span class="comment">// 0.0683308</span></div><div class="line"><a name="l01518"></a><span class="lineno"> 1518</span>  0.0991211f, <span class="comment">// 0.0988837</span></div><div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>  0.0461426f, <span class="comment">// 0.0461838</span></div><div class="line"><a name="l01520"></a><span class="lineno"> 1520</span>  0.0996094f, <span class="comment">// 0.0997546</span></div><div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>  0.1269530f, <span class="comment">// 0.127099</span></div><div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>  0.0393066f, <span class="comment">// 0.0392791</span></div><div class="line"><a name="l01523"></a><span class="lineno"> 1523</span>  0.103516f <span class="comment">// 0.103641</span></div><div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>  },</div><div class="line"><a name="l01525"></a><span class="lineno"> 1525</span>  1.0f, 0);</div><div class="line"><a name="l01526"></a><span class="lineno"> 1526</span> </div><div class="line"><a name="l01527"></a><span class="lineno"> 1527</span>  <span class="keyword">auto</span> input = MakeTensor<armnn::BFloat16, 4>(inputDesc, inputValues);</div><div class="line"><a name="l01528"></a><span class="lineno"> 1528</span> </div><div class="line"><a name="l01529"></a><span class="lineno"> 1529</span>  <span class="comment">// Use a 3x3 kernel.</span></div><div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({1, 3, 3, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>);</div><div class="line"><a name="l01531"></a><span class="lineno"> 1531</span> </div><div class="line"><a name="l01532"></a><span class="lineno"> 1532</span>  std::vector<armnn::BFloat16> kernelValues = armnnUtils::QuantizedVector<armnn::BFloat16>(</div><div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>  {</div><div class="line"><a name="l01534"></a><span class="lineno"> 1534</span>  -0.126184f, <span class="comment">// -0.125977</span></div><div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>  -0.150468f, <span class="comment">// -0.150391</span></div><div class="line"><a name="l01536"></a><span class="lineno"> 1536</span>  -0.101412f, <span class="comment">// -0.101562</span></div><div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>  -0.0586369f,<span class="comment">// -0.0585938</span></div><div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>  -0.0865864f,<span class="comment">// -0.0864258</span></div><div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>  -0.0435089f,<span class="comment">// -0.043457</span></div><div class="line"><a name="l01540"></a><span class="lineno"> 1540</span>  0.0347555f, <span class="comment">// 0.034668</span></div><div class="line"><a name="l01541"></a><span class="lineno"> 1541</span>  0.0323111f, <span class="comment">// 0.0322266</span></div><div class="line"><a name="l01542"></a><span class="lineno"> 1542</span>  0.0385381f <span class="comment">// 0.0385742</span></div><div class="line"><a name="l01543"></a><span class="lineno"> 1543</span>  },</div><div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>  1.0f, 0);</div><div class="line"><a name="l01545"></a><span class="lineno"> 1545</span> </div><div class="line"><a name="l01546"></a><span class="lineno"> 1546</span>  <span class="keyword">auto</span> kernel = MakeTensor<armnn::BFloat16, 4>(kernelDesc, kernelValues);</div><div class="line"><a name="l01547"></a><span class="lineno"> 1547</span> </div><div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>  <span class="comment">// Expected output is a single-batch, 1 channel, 3x3 image.</span></div><div class="line"><a name="l01549"></a><span class="lineno"> 1549</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputDesc({1, 3, 3, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01550"></a><span class="lineno"> 1550</span> </div><div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>  <span class="comment">// Expected output (with results if calculated as FP32 in the comments)</span></div><div class="line"><a name="l01552"></a><span class="lineno"> 1552</span>  <span class="keyword">const</span> std::vector<float> outputData =</div><div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>  {</div><div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>  0.000686645508f, <span class="comment">// 0.000685</span></div><div class="line"><a name="l01555"></a><span class="lineno"> 1555</span>  0.000640869141f, <span class="comment">// 0.000639</span></div><div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>  -0.00759887695f, <span class="comment">// -0.007631</span></div><div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>  -0.02734375f, <span class="comment">// -0.027388</span></div><div class="line"><a name="l01558"></a><span class="lineno"> 1558</span>  -0.0356445312f, <span class="comment">// -0.035737</span></div><div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>  -0.0145874023f, <span class="comment">// -0.014568</span></div><div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>  -0.0170898438f, <span class="comment">// -0.017124</span></div><div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>  -0.0373535156f, <span class="comment">// -0.037431</span></div><div class="line"><a name="l01562"></a><span class="lineno"> 1562</span>  -0.0346679688f <span class="comment">// -0.034808</span></div><div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>  };</div><div class="line"><a name="l01564"></a><span class="lineno"> 1564</span> </div><div class="line"><a name="l01565"></a><span class="lineno"> 1565</span>  boost::multi_array<float, 4> expectedOutput = MakeTensor<float, 4>(outputDesc, outputData);</div><div class="line"><a name="l01566"></a><span class="lineno"> 1566</span> </div><div class="line"><a name="l01567"></a><span class="lineno"> 1567</span>  uint32_t padLeft = 1;</div><div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>  uint32_t padTop = 1;</div><div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>  uint32_t padRight = 1;</div><div class="line"><a name="l01570"></a><span class="lineno"> 1570</span>  uint32_t padBottom = 1;</div><div class="line"><a name="l01571"></a><span class="lineno"> 1571</span>  uint32_t strideX = 2;</div><div class="line"><a name="l01572"></a><span class="lineno"> 1572</span>  uint32_t strideY = 2;</div><div class="line"><a name="l01573"></a><span class="lineno"> 1573</span> </div><div class="line"><a name="l01574"></a><span class="lineno"> 1574</span>  <span class="keywordflow">return</span> <a class="code" href="_conv2d_test_impl_8cpp.xhtml#a13be450008f6c2f7560e82fa855295f1">SimpleConvolution2dNhwcTestImpl</a></div><div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>  <<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, <a class="code" href="classarmnn_1_1_b_float16.xhtml">armnn::BFloat16</a>, float, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, <span class="keywordtype">float</span>>(</div><div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>  workloadFactory,</div><div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>  memoryManager,</div><div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>  input,</div><div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>  kernel,</div><div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>  boost::multi_array<float, 1>(),</div><div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>  expectedOutput,</div><div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>  dataLayout,</div><div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>  1.0f,</div><div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>  0,</div><div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>  padLeft,</div><div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>  padTop,</div><div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>  padRight,</div><div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>  padBottom,</div><div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>  strideX,</div><div class="line"><a name="l01590"></a><span class="lineno"> 1590</span>  strideY);</div><div class="line"><a name="l01591"></a><span class="lineno"> 1591</span> }</div><div class="ttc" id="_conv2d_test_impl_8cpp_xhtml_a13be450008f6c2f7560e82fa855295f1"><div class="ttname"><a href="_conv2d_test_impl_8cpp.xhtml#a13be450008f6c2f7560e82fa855295f1">SimpleConvolution2dNhwcTestImpl</a></div><div class="ttdeci">LayerTestResult< O, 4 > SimpleConvolution2dNhwcTestImpl(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const boost::multi_array< T, 4 > &input, const boost::multi_array< T, 4 > &kernel, const boost::multi_array< B, 1 > &bias, const boost::multi_array< O, 4 > &outputExpected, const armnn::DataLayout dataLayout, float qScale, int32_t qOffset, uint32_t padLeft=1, uint32_t padTop=1, uint32_t padRight=1, uint32_t padBottom=1, uint32_t strideX=1, uint32_t strideY=1)</div><div class="ttdef"><b>Definition:</b> <a href="_conv2d_test_impl_8cpp_source.xhtml#l00368">Conv2dTestImpl.cpp:368</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_b_float16_xhtml"><div class="ttname"><a href="classarmnn_1_1_b_float16.xhtml">armnn::BFloat16</a></div><div class="ttdef"><b>Definition:</b> <a href="_b_float16_8hpp_source.xhtml#l00014">BFloat16.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</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><!-- fragment --> +</div> +</div> +<a id="a8220b8330608ebcaf3edeb75c8988373"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a8220b8330608ebcaf3edeb75c8988373">◆ </a></span>Convolution2d3x3Stride2x2BFloat16Test()</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, 4> Convolution2d3x3Stride2x2BFloat16Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> & </td> + <td class="paramname"><em>dataLayout</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="_conv2d_test_impl_8cpp_source.xhtml#l01377">1377</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::BFloat16</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, and <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml#l00368">SimpleConvolution2dNhwcTestImpl()</a>.</p> +<div class="fragment"><div class="line"><a name="l01382"></a><span class="lineno"> 1382</span> {</div><div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>  <span class="comment">// BFloat16 input and weight, Float32 output</span></div><div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a>(biasEnabled);</div><div class="line"><a name="l01385"></a><span class="lineno"> 1385</span> </div><div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>  <span class="comment">// Input is a single-batch, 1 channel, 5x5 image.</span></div><div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputDesc({1, 5, 5, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>);</div><div class="line"><a name="l01388"></a><span class="lineno"> 1388</span> </div><div class="line"><a name="l01389"></a><span class="lineno"> 1389</span>  std::vector<armnn::BFloat16> inputValues = armnnUtils::QuantizedVector<armnn::BFloat16>(</div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>  {</div><div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>  10.0367984f, <span class="comment">// 10.0625</span></div><div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>  2.0380895f, <span class="comment">// 2.03125</span></div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>  15.0420157f, <span class="comment">// 15.0625</span></div><div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>  22.0675631f, <span class="comment">// 22.125</span></div><div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>  8.0938920f, <span class="comment">// 8.125</span></div><div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>  5.0476106f, <span class="comment">// 5.0625</span></div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>  80.1035490f, <span class="comment">// 80</span></div><div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>  100.1260370f, <span class="comment">// 100</span></div><div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>  55.0461647f, <span class="comment">// 55</span></div><div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>  120.0883828f, <span class="comment">// 120</span></div><div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>  9.1159540f, <span class="comment">// 9.125</span></div><div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>  90.0498519f, <span class="comment">// 90</span></div><div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>  200.0104630f, <span class="comment">// 200</span></div><div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>  30.0154114f, <span class="comment">// 30</span></div><div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>  75.00137681f, <span class="comment">// 75</span></div><div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>  30.0344238f, <span class="comment">// 30</span></div><div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>  25.0356445f, <span class="comment">// 25</span></div><div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>  130.0495605f, <span class="comment">// 130</span></div><div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>  60.0683594f, <span class="comment">// 60</span></div><div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>  35.0991211f, <span class="comment">// 35</span></div><div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>  8.0461426f, <span class="comment">// 8.0625</span></div><div class="line"><a name="l01412"></a><span class="lineno"> 1412</span>  12.0996094f, <span class="comment">// 12.125</span></div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>  98.1269530f, <span class="comment">// 98</span></div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>  125.0393066f, <span class="comment">// 125</span></div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>  5.103516f <span class="comment">// 5.0937</span></div><div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>  },</div><div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>  1.0f, 0);</div><div class="line"><a name="l01418"></a><span class="lineno"> 1418</span> </div><div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>  <span class="keyword">auto</span> input = MakeTensor<armnn::BFloat16, 4>(inputDesc, inputValues);</div><div class="line"><a name="l01420"></a><span class="lineno"> 1420</span> </div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>  <span class="comment">// Use a 3x3 kernel.</span></div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelDesc({1, 3, 3, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>);</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span> </div><div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>  std::vector<armnn::BFloat16> kernelValues = armnnUtils::QuantizedVector<armnn::BFloat16>(</div><div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>  {</div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>  -0.126184f, <span class="comment">// -0.125977</span></div><div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>  -0.150468f, <span class="comment">// -0.150391</span></div><div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>  -0.101412f, <span class="comment">// -0.101562</span></div><div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>  -0.0586369f,<span class="comment">// -0.0585938</span></div><div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>  -0.0865864f,<span class="comment">// -0.0864258</span></div><div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>  -0.0435089f,<span class="comment">// -0.043457</span></div><div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>  0.0347555f, <span class="comment">// 0.034668</span></div><div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>  0.0323111f, <span class="comment">// 0.0322266</span></div><div class="line"><a name="l01434"></a><span class="lineno"> 1434</span>  0.0385381f <span class="comment">// 0.0385742</span></div><div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>  },</div><div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>  1.0f, 0);</div><div class="line"><a name="l01437"></a><span class="lineno"> 1437</span> </div><div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>  <span class="keyword">auto</span> kernel = MakeTensor<armnn::BFloat16, 4>(kernelDesc, kernelValues);</div><div class="line"><a name="l01439"></a><span class="lineno"> 1439</span> </div><div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>  <span class="comment">// Expected output is a single-batch, 1 channel, 3x3 image.</span></div><div class="line"><a name="l01441"></a><span class="lineno"> 1441</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputDesc({1, 3, 3, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01442"></a><span class="lineno"> 1442</span> </div><div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>  <span class="comment">// Expected output (with results if calculated as FP32 in the comments)</span></div><div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>  <span class="keyword">const</span> std::vector<float> outputData =</div><div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>  {</div><div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>  2.296875f, <span class="comment">// 2.29240716</span></div><div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>  5.75f, <span class="comment">// 5.75851926</span></div><div class="line"><a name="l01448"></a><span class="lineno"> 1448</span>  3.78125f, <span class="comment">// 3.79855026</span></div><div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>  -11.625f, <span class="comment">// -11.65498118</span></div><div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>  -47.25f, <span class="comment">// -47.27316893</span></div><div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>  -30.0f, <span class="comment">// -30.04771684</span></div><div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>  -8.25f, <span class="comment">// -8.28126168</span></div><div class="line"><a name="l01453"></a><span class="lineno"> 1453</span>  -43.5f, <span class="comment">// -43.46531337</span></div><div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>  -20.625f <span class="comment">// -20.63477281</span></div><div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>  };</div><div class="line"><a name="l01456"></a><span class="lineno"> 1456</span> </div><div class="line"><a name="l01457"></a><span class="lineno"> 1457</span>  boost::multi_array<float, 4> expectedOutput = MakeTensor<float, 4>(outputDesc, outputData);</div><div class="line"><a name="l01458"></a><span class="lineno"> 1458</span> </div><div class="line"><a name="l01459"></a><span class="lineno"> 1459</span>  uint32_t padLeft = 1;</div><div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>  uint32_t padTop = 1;</div><div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>  uint32_t padRight = 1;</div><div class="line"><a name="l01462"></a><span class="lineno"> 1462</span>  uint32_t padBottom = 1;</div><div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>  uint32_t strideX = 2;</div><div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>  uint32_t strideY = 2;</div><div class="line"><a name="l01465"></a><span class="lineno"> 1465</span> </div><div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>  <span class="keywordflow">return</span> <a class="code" href="_conv2d_test_impl_8cpp.xhtml#a13be450008f6c2f7560e82fa855295f1">SimpleConvolution2dNhwcTestImpl</a></div><div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>  <<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, <a class="code" href="classarmnn_1_1_b_float16.xhtml">armnn::BFloat16</a>, float, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, <span class="keywordtype">float</span>>(</div><div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>  workloadFactory,</div><div class="line"><a name="l01469"></a><span class="lineno"> 1469</span>  memoryManager,</div><div class="line"><a name="l01470"></a><span class="lineno"> 1470</span>  input,</div><div class="line"><a name="l01471"></a><span class="lineno"> 1471</span>  kernel,</div><div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>  boost::multi_array<float, 1>(),</div><div class="line"><a name="l01473"></a><span class="lineno"> 1473</span>  expectedOutput,</div><div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>  dataLayout,</div><div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>  1.0f,</div><div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>  0,</div><div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>  padLeft,</div><div class="line"><a name="l01478"></a><span class="lineno"> 1478</span>  padTop,</div><div class="line"><a name="l01479"></a><span class="lineno"> 1479</span>  padRight,</div><div class="line"><a name="l01480"></a><span class="lineno"> 1480</span>  padBottom,</div><div class="line"><a name="l01481"></a><span class="lineno"> 1481</span>  strideX,</div><div class="line"><a name="l01482"></a><span class="lineno"> 1482</span>  strideY);</div><div class="line"><a name="l01483"></a><span class="lineno"> 1483</span> }</div><div class="ttc" id="_conv2d_test_impl_8cpp_xhtml_a13be450008f6c2f7560e82fa855295f1"><div class="ttname"><a href="_conv2d_test_impl_8cpp.xhtml#a13be450008f6c2f7560e82fa855295f1">SimpleConvolution2dNhwcTestImpl</a></div><div class="ttdeci">LayerTestResult< O, 4 > SimpleConvolution2dNhwcTestImpl(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const boost::multi_array< T, 4 > &input, const boost::multi_array< T, 4 > &kernel, const boost::multi_array< B, 1 > &bias, const boost::multi_array< O, 4 > &outputExpected, const armnn::DataLayout dataLayout, float qScale, int32_t qOffset, uint32_t padLeft=1, uint32_t padTop=1, uint32_t padRight=1, uint32_t padBottom=1, uint32_t strideX=1, uint32_t strideY=1)</div><div class="ttdef"><b>Definition:</b> <a href="_conv2d_test_impl_8cpp_source.xhtml#l00368">Conv2dTestImpl.cpp:368</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_b_float16_xhtml"><div class="ttname"><a href="classarmnn_1_1_b_float16.xhtml">armnn::BFloat16</a></div><div class="ttdef"><b>Definition:</b> <a href="_b_float16_8hpp_source.xhtml#l00014">BFloat16.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</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><!-- fragment --> +</div> +</div> +<a id="a48884a37a6b783185c608a68cfce752f"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a48884a37a6b783185c608a68cfce752f">◆ </a></span>Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest()</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, 4> Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest </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"><a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03318">3318</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml#l00870">Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon()</a>, and <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>.</p> +<div class="fragment"><div class="line"><a name="l03322"></a><span class="lineno"> 3322</span> {</div><div class="line"><a name="l03323"></a><span class="lineno"> 3323</span>  <span class="keywordflow">return</span> <a class="code" href="_conv2d_test_impl_8cpp.xhtml#a35ad1225c524b4594b461e613695ee4a">Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon</a></div><div class="line"><a name="l03324"></a><span class="lineno"> 3324</span>  <<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>, armnn::DataType::Float32>(</div><div class="line"><a name="l03325"></a><span class="lineno"> 3325</span>  workloadFactory, memoryManager, layout, 0.0f, 0);</div><div class="line"><a name="l03326"></a><span class="lineno"> 3326</span> }</div><div class="ttc" id="_conv2d_test_impl_8cpp_xhtml_a35ad1225c524b4594b461e613695ee4a"><div class="ttname"><a href="_conv2d_test_impl_8cpp.xhtml#a35ad1225c524b4594b461e613695ee4a">Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::DataLayout layout, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_conv2d_test_impl_8cpp_source.xhtml#l00870">Conv2dTestImpl.cpp:870</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><!-- fragment --> +</div> +</div> +<a id="af7f2cd23423130ebdd916de12bc0eb1d"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af7f2cd23423130ebdd916de12bc0eb1d">◆ </a></span>Convolution2dAsymmetricPaddingTest()</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, 4> Convolution2dAsymmetricPaddingTest </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"><a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03309">3309</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03313"></a><span class="lineno"> 3313</span> {</div><div class="line"><a name="l03314"></a><span class="lineno"> 3314</span>  <span class="keywordflow">return</span> SimpleConvolution2dAsymmetricPaddingTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l03315"></a><span class="lineno"> 3315</span>  workloadFactory, memoryManager, layout, 0.0f, 0);</div><div class="line"><a name="l03316"></a><span class="lineno"> 3316</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a370a5216668b507284677234264a22a2"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a370a5216668b507284677234264a22a2">◆ </a></span>Convolution2dPerAxisQuantTest()</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><uint8_t, 4> Convolution2dPerAxisQuantTest </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="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03346">3346</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_deprecated_8hpp_source.xhtml#l00033">ARMNN_NO_DEPRECATE_WARN_BEGIN</a>, <a class="el" href="_deprecated_8hpp_source.xhtml#l00034">ARMNN_NO_DEPRECATE_WARN_END</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#l01302">IWorkloadFactory::CreateConvolution2d()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00446">Convolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00448">Convolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00436">Convolution2dDescriptor::m_PadBottom</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00430">Convolution2dDescriptor::m_PadLeft</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00432">Convolution2dDescriptor::m_PadRight</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00434">Convolution2dDescriptor::m_PadTop</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00049">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00438">Convolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00440">Convolution2dDescriptor::m_StrideY</a>, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00041">LayerTestResult< T, n >::output</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00042">LayerTestResult< T, n >::outputExpected</a>, and <a class="el" href="_data_layout_utils_8hpp_source.xhtml#l00026">PermuteTensorNhwcToNchw()</a>.</p> +<div class="fragment"><div class="line"><a name="l03350"></a><span class="lineno"> 3350</span> {</div><div class="line"><a name="l03351"></a><span class="lineno"> 3351</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l03352"></a><span class="lineno"> 3352</span> </div><div class="line"><a name="l03353"></a><span class="lineno"> 3353</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> inputType = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>;</div><div class="line"><a name="l03354"></a><span class="lineno"> 3354</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> kernelType = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>;</div><div class="line"><a name="l03355"></a><span class="lineno"> 3355</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> biasType = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>;</div><div class="line"><a name="l03356"></a><span class="lineno"> 3356</span> </div><div class="line"><a name="l03357"></a><span class="lineno"> 3357</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo ({ 1, 3, 1, 2 }, inputType, 0.5f, 128);</div><div class="line"><a name="l03358"></a><span class="lineno"> 3358</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 3, 1, 3 }, inputType, 1.0f, 128);</div><div class="line"><a name="l03359"></a><span class="lineno"> 3359</span> </div><div class="line"><a name="l03360"></a><span class="lineno"> 3360</span>  <span class="keyword">const</span> std::vector<float> quantScales{ 0.5f, 0.75f, 1.0f };</div><div class="line"><a name="l03361"></a><span class="lineno"> 3361</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantDimension = 0;</div><div class="line"><a name="l03362"></a><span class="lineno"> 3362</span> </div><div class="line"><a name="l03363"></a><span class="lineno"> 3363</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> kernelInfo({ 3, 1, 1, 2 }, kernelType, quantScales, quantDimension);</div><div class="line"><a name="l03364"></a><span class="lineno"> 3364</span> </div><div class="line"><a name="l03365"></a><span class="lineno"> 3365</span>  <span class="keyword">const</span> std::vector<float> biasQuantScales{ 0.25f, 0.375f, 0.5f };</div><div class="line"><a name="l03366"></a><span class="lineno"> 3366</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> biasInfo({ 3 }, biasType, biasQuantScales, quantDimension);</div><div class="line"><a name="l03367"></a><span class="lineno"> 3367</span> </div><div class="line"><a name="l03368"></a><span class="lineno"> 3368</span>  std::vector<uint8_t> inputData =</div><div class="line"><a name="l03369"></a><span class="lineno"> 3369</span>  {</div><div class="line"><a name="l03370"></a><span class="lineno"> 3370</span>  138, 108, 138, 108, 138, 108</div><div class="line"><a name="l03371"></a><span class="lineno"> 3371</span>  };</div><div class="line"><a name="l03372"></a><span class="lineno"> 3372</span> </div><div class="line"><a name="l03373"></a><span class="lineno"> 3373</span>  std::vector<int8_t> kernelData =</div><div class="line"><a name="l03374"></a><span class="lineno"> 3374</span>  {</div><div class="line"><a name="l03375"></a><span class="lineno"> 3375</span>  1, 2, 1, 2, 1, 2</div><div class="line"><a name="l03376"></a><span class="lineno"> 3376</span>  };</div><div class="line"><a name="l03377"></a><span class="lineno"> 3377</span> </div><div class="line"><a name="l03378"></a><span class="lineno"> 3378</span>  std::vector<int32_t> biasData =</div><div class="line"><a name="l03379"></a><span class="lineno"> 3379</span>  {</div><div class="line"><a name="l03380"></a><span class="lineno"> 3380</span>  4, 4, 4</div><div class="line"><a name="l03381"></a><span class="lineno"> 3381</span>  };</div><div class="line"><a name="l03382"></a><span class="lineno"> 3382</span> </div><div class="line"><a name="l03383"></a><span class="lineno"> 3383</span>  std::vector<uint8_t> expectedOutputData =</div><div class="line"><a name="l03384"></a><span class="lineno"> 3384</span>  {</div><div class="line"><a name="l03385"></a><span class="lineno"> 3385</span>  121, 118, 115, 121, 118, 115, 121, 118, 115</div><div class="line"><a name="l03386"></a><span class="lineno"> 3386</span>  };</div><div class="line"><a name="l03387"></a><span class="lineno"> 3387</span> </div><div class="line"><a name="l03388"></a><span class="lineno"> 3388</span>  <span class="keywordflow">if</span> (layout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div><div class="line"><a name="l03389"></a><span class="lineno"> 3389</span>  {</div><div class="line"><a name="l03390"></a><span class="lineno"> 3390</span>  <a class="code" href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(inputInfo, inputData);</div><div class="line"><a name="l03391"></a><span class="lineno"> 3391</span>  <a class="code" href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(kernelInfo, kernelData);</div><div class="line"><a name="l03392"></a><span class="lineno"> 3392</span>  <a class="code" href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(outputInfo, expectedOutputData);</div><div class="line"><a name="l03393"></a><span class="lineno"> 3393</span>  }</div><div class="line"><a name="l03394"></a><span class="lineno"> 3394</span> </div><div class="line"><a name="l03395"></a><span class="lineno"> 3395</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l03396"></a><span class="lineno"> 3396</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l03397"></a><span class="lineno"> 3397</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l03398"></a><span class="lineno"> 3398</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 0;</div><div class="line"><a name="l03399"></a><span class="lineno"> 3399</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 0;</div><div class="line"><a name="l03400"></a><span class="lineno"> 3400</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 0;</div><div class="line"><a name="l03401"></a><span class="lineno"> 3401</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l03402"></a><span class="lineno"> 3402</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l03403"></a><span class="lineno"> 3403</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = layout;</div><div class="line"><a name="l03404"></a><span class="lineno"> 3404</span> </div><div class="line"><a name="l03405"></a><span class="lineno"> 3405</span>  <a class="code" href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l03406"></a><span class="lineno"> 3406</span>  std::unique_ptr<ITensorHandle> inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputInfo);</div><div class="line"><a name="l03407"></a><span class="lineno"> 3407</span>  std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputInfo);</div><div class="line"><a name="l03408"></a><span class="lineno"> 3408</span>  <a class="code" href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="line"><a name="l03409"></a><span class="lineno"> 3409</span> </div><div class="line"><a name="l03410"></a><span class="lineno"> 3410</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l03411"></a><span class="lineno"> 3411</span>  <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">ScopedCpuTensorHandle</a> weightTensor(kernelInfo);</div><div class="line"><a name="l03412"></a><span class="lineno"> 3412</span>  <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">ScopedCpuTensorHandle</a> biasTensor(biasInfo);</div><div class="line"><a name="l03413"></a><span class="lineno"> 3413</span> </div><div class="line"><a name="l03414"></a><span class="lineno"> 3414</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&weightTensor, kernelData.data());</div><div class="line"><a name="l03415"></a><span class="lineno"> 3415</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&biasTensor, biasData.data());</div><div class="line"><a name="l03416"></a><span class="lineno"> 3416</span> </div><div class="line"><a name="l03417"></a><span class="lineno"> 3417</span>  <a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">Convolution2dQueueDescriptor</a> queueDescriptor;</div><div class="line"><a name="l03418"></a><span class="lineno"> 3418</span>  queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a> = descriptor;</div><div class="line"><a name="l03419"></a><span class="lineno"> 3419</span>  queueDescriptor.m_Weight = &weightTensor;</div><div class="line"><a name="l03420"></a><span class="lineno"> 3420</span>  queueDescriptor.m_Bias = &biasTensor;</div><div class="line"><a name="l03421"></a><span class="lineno"> 3421</span> </div><div class="line"><a name="l03422"></a><span class="lineno"> 3422</span>  AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get());</div><div class="line"><a name="l03423"></a><span class="lineno"> 3423</span>  AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get());</div><div class="line"><a name="l03424"></a><span class="lineno"> 3424</span> </div><div class="line"><a name="l03425"></a><span class="lineno"> 3425</span>  std::unique_ptr<IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a2184995027cd2c9f9980206de9658855">CreateConvolution2d</a>(queueDescriptor, workloadInfo);</div><div class="line"><a name="l03426"></a><span class="lineno"> 3426</span>  inputHandle->Allocate();</div><div class="line"><a name="l03427"></a><span class="lineno"> 3427</span>  outputHandle->Allocate();</div><div class="line"><a name="l03428"></a><span class="lineno"> 3428</span> </div><div class="line"><a name="l03429"></a><span class="lineno"> 3429</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputData.data());</div><div class="line"><a name="l03430"></a><span class="lineno"> 3430</span> </div><div class="line"><a name="l03431"></a><span class="lineno"> 3431</span>  ExecuteWorkload(*workload, memoryManager);</div><div class="line"><a name="l03432"></a><span class="lineno"> 3432</span> </div><div class="line"><a name="l03433"></a><span class="lineno"> 3433</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> ret(outputInfo);</div><div class="line"><a name="l03434"></a><span class="lineno"> 3434</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(ret.output.origin(), outputHandle.get());</div><div class="line"><a name="l03435"></a><span class="lineno"> 3435</span>  ret.outputExpected = MakeTensor<uint8_t, 4>(outputInfo, expectedOutputData);</div><div class="line"><a name="l03436"></a><span class="lineno"> 3436</span> </div><div class="line"><a name="l03437"></a><span class="lineno"> 3437</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l03438"></a><span class="lineno"> 3438</span> }</div><div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::Convolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00436">Descriptors.hpp:436</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::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#l00446">Descriptors.hpp:446</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00448">Descriptors.hpp:448</a></div></div> +<div class="ttc" id="_deprecated_8hpp_xhtml_ab66a241a0ed3ee89c866e777b035d0ed"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_BEGIN</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00033">Deprecated.hpp:33</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="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00400">Descriptors.hpp:400</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::Convolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00432">Descriptors.hpp:432</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div> +<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> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::Convolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00434">Descriptors.hpp:434</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00438">Descriptors.hpp:438</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00032">Types.hpp:32</a></div></div> +<div class="ttc" id="_deprecated_8hpp_xhtml_ad762b11b48e5c1d1c1743f529485728a"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_END</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00034">Deprecated.hpp:34</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div> +<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> +<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00440">Descriptors.hpp:440</a></div></div> +<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< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0</div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">armnn::Convolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00174">WorkloadData.hpp:174</a></div></div> +<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> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00030">LayerTestResult.hpp:30</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Convolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00430">Descriptors.hpp:430</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a2184995027cd2c9f9980206de9658855"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a2184995027cd2c9f9980206de9658855">armnn::IWorkloadFactory::CreateConvolution2d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateConvolution2d(const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01302">WorkloadFactory.cpp:1302</a></div></div> +<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="_data_layout_utils_8hpp_xhtml_a1452f049aef30409b3b649af2be7ff82"><div class="ttname"><a href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a></div><div class="ttdeci">void PermuteTensorNhwcToNchw(armnn::TensorInfo &tensorInfo, std::vector< T > &tensorData)</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_utils_8hpp_source.xhtml#l00026">DataLayoutUtils.hpp:26</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="acffa50ae3185e3e5302909f27e7e9a02"></a> +<h2 class="memtitle"><span class="permalink"><a href="#acffa50ae3185e3e5302909f27e7e9a02">◆ </a></span>DepthwiseConvolution2d2x3x3Dilation3x3Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> DepthwiseConvolution2d2x3x3Dilation3x3Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l02651">2651</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l02656"></a><span class="lineno"> 2656</span> {</div><div class="line"><a name="l02657"></a><span class="lineno"> 2657</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({1, 2, 10, 10}, ArmnnType);</div><div class="line"><a name="l02658"></a><span class="lineno"> 2658</span>  std::vector<float> inputNoQuantizedValues =</div><div class="line"><a name="l02659"></a><span class="lineno"> 2659</span>  {</div><div class="line"><a name="l02660"></a><span class="lineno"> 2660</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02661"></a><span class="lineno"> 2661</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02662"></a><span class="lineno"> 2662</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02663"></a><span class="lineno"> 2663</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l02664"></a><span class="lineno"> 2664</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l02665"></a><span class="lineno"> 2665</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l02666"></a><span class="lineno"> 2666</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02667"></a><span class="lineno"> 2667</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02668"></a><span class="lineno"> 2668</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02669"></a><span class="lineno"> 2669</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02670"></a><span class="lineno"> 2670</span> </div><div class="line"><a name="l02671"></a><span class="lineno"> 2671</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02672"></a><span class="lineno"> 2672</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02673"></a><span class="lineno"> 2673</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02674"></a><span class="lineno"> 2674</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l02675"></a><span class="lineno"> 2675</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l02676"></a><span class="lineno"> 2676</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l02677"></a><span class="lineno"> 2677</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02678"></a><span class="lineno"> 2678</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02679"></a><span class="lineno"> 2679</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02680"></a><span class="lineno"> 2680</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0</div><div class="line"><a name="l02681"></a><span class="lineno"> 2681</span>  };</div><div class="line"><a name="l02682"></a><span class="lineno"> 2682</span> </div><div class="line"><a name="l02683"></a><span class="lineno"> 2683</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelTensorInfo({ 1, 2, 3, 3}, ArmnnType);</div><div class="line"><a name="l02684"></a><span class="lineno"> 2684</span>  std::vector<float> kernelNoQuantizedValues =</div><div class="line"><a name="l02685"></a><span class="lineno"> 2685</span>  {</div><div class="line"><a name="l02686"></a><span class="lineno"> 2686</span>  1, 2, 3,</div><div class="line"><a name="l02687"></a><span class="lineno"> 2687</span>  4, 5, 6,</div><div class="line"><a name="l02688"></a><span class="lineno"> 2688</span>  7, 8, 9,</div><div class="line"><a name="l02689"></a><span class="lineno"> 2689</span> </div><div class="line"><a name="l02690"></a><span class="lineno"> 2690</span>  1, 2, 3,</div><div class="line"><a name="l02691"></a><span class="lineno"> 2691</span>  4, 5, 6,</div><div class="line"><a name="l02692"></a><span class="lineno"> 2692</span>  7, 8, 9</div><div class="line"><a name="l02693"></a><span class="lineno"> 2693</span>  };</div><div class="line"><a name="l02694"></a><span class="lineno"> 2694</span> </div><div class="line"><a name="l02695"></a><span class="lineno"> 2695</span>  <span class="comment">// Since the dilation rate is 3 this will dilate the kernel to be like 7x7,</span></div><div class="line"><a name="l02696"></a><span class="lineno"> 2696</span>  <span class="comment">// therefore the output will be 2x4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1</span></div><div class="line"><a name="l02697"></a><span class="lineno"> 2697</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, 2, 4, 4}, ArmnnType);</div><div class="line"><a name="l02698"></a><span class="lineno"> 2698</span>  std::vector<float> outputExpectedNoQuantizedValues =</div><div class="line"><a name="l02699"></a><span class="lineno"> 2699</span>  {</div><div class="line"><a name="l02700"></a><span class="lineno"> 2700</span>  6., 5., 5., 5.,</div><div class="line"><a name="l02701"></a><span class="lineno"> 2701</span>  6., 5., 5., 5.,</div><div class="line"><a name="l02702"></a><span class="lineno"> 2702</span>  6., 5., 5., 5.,</div><div class="line"><a name="l02703"></a><span class="lineno"> 2703</span>  3., 2., 2., 2.,</div><div class="line"><a name="l02704"></a><span class="lineno"> 2704</span> </div><div class="line"><a name="l02705"></a><span class="lineno"> 2705</span>  6., 5., 5., 5.,</div><div class="line"><a name="l02706"></a><span class="lineno"> 2706</span>  6., 5., 5., 5.,</div><div class="line"><a name="l02707"></a><span class="lineno"> 2707</span>  6., 5., 5., 5.,</div><div class="line"><a name="l02708"></a><span class="lineno"> 2708</span>  3., 2., 2., 2.</div><div class="line"><a name="l02709"></a><span class="lineno"> 2709</span>  };</div><div class="line"><a name="l02710"></a><span class="lineno"> 2710</span> </div><div class="line"><a name="l02711"></a><span class="lineno"> 2711</span>  <span class="keywordflow">return</span> DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l02712"></a><span class="lineno"> 2712</span>  workloadFactory,</div><div class="line"><a name="l02713"></a><span class="lineno"> 2713</span>  memoryManager,</div><div class="line"><a name="l02714"></a><span class="lineno"> 2714</span>  inputNoQuantizedValues,</div><div class="line"><a name="l02715"></a><span class="lineno"> 2715</span>  inputTensorInfo,</div><div class="line"><a name="l02716"></a><span class="lineno"> 2716</span>  kernelNoQuantizedValues,</div><div class="line"><a name="l02717"></a><span class="lineno"> 2717</span>  kernelTensorInfo,</div><div class="line"><a name="l02718"></a><span class="lineno"> 2718</span>  outputExpectedNoQuantizedValues,</div><div class="line"><a name="l02719"></a><span class="lineno"> 2719</span>  outputTensorInfo,</div><div class="line"><a name="l02720"></a><span class="lineno"> 2720</span>  3,</div><div class="line"><a name="l02721"></a><span class="lineno"> 2721</span>  3,</div><div class="line"><a name="l02722"></a><span class="lineno"> 2722</span>  layout,</div><div class="line"><a name="l02723"></a><span class="lineno"> 2723</span>  biasEnabled);</div><div class="line"><a name="l02724"></a><span class="lineno"> 2724</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><!-- fragment --> +</div> +</div> +<a id="a1c3398bdb48e4ce4643a1eeaf3e054a3"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a1c3398bdb48e4ce4643a1eeaf3e054a3">◆ </a></span>DepthwiseConvolution2d3x3Dilation3x3Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> DepthwiseConvolution2d3x3Dilation3x3Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l02595">2595</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l02600"></a><span class="lineno"> 2600</span> {</div><div class="line"><a name="l02601"></a><span class="lineno"> 2601</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({1, 1, 10, 10}, ArmnnType);</div><div class="line"><a name="l02602"></a><span class="lineno"> 2602</span>  std::vector<float> inputNoQuantizedValues =</div><div class="line"><a name="l02603"></a><span class="lineno"> 2603</span>  {</div><div class="line"><a name="l02604"></a><span class="lineno"> 2604</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02605"></a><span class="lineno"> 2605</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02606"></a><span class="lineno"> 2606</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02607"></a><span class="lineno"> 2607</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l02608"></a><span class="lineno"> 2608</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l02609"></a><span class="lineno"> 2609</span>  0, 0, 0, 0, 1, 1, 1, 0, 0, 0,</div><div class="line"><a name="l02610"></a><span class="lineno"> 2610</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02611"></a><span class="lineno"> 2611</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02612"></a><span class="lineno"> 2612</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0,</div><div class="line"><a name="l02613"></a><span class="lineno"> 2613</span>  0, 0, 0, 0, 0, 0, 0, 0, 0, 0</div><div class="line"><a name="l02614"></a><span class="lineno"> 2614</span>  };</div><div class="line"><a name="l02615"></a><span class="lineno"> 2615</span> </div><div class="line"><a name="l02616"></a><span class="lineno"> 2616</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelTensorInfo({ 1, 1, 3, 3}, ArmnnType);</div><div class="line"><a name="l02617"></a><span class="lineno"> 2617</span>  std::vector<float> kernelNoQuantizedValues =</div><div class="line"><a name="l02618"></a><span class="lineno"> 2618</span>  {</div><div class="line"><a name="l02619"></a><span class="lineno"> 2619</span>  1, 2, 3,</div><div class="line"><a name="l02620"></a><span class="lineno"> 2620</span>  4, 5, 6,</div><div class="line"><a name="l02621"></a><span class="lineno"> 2621</span>  7, 8, 9</div><div class="line"><a name="l02622"></a><span class="lineno"> 2622</span>  };</div><div class="line"><a name="l02623"></a><span class="lineno"> 2623</span> </div><div class="line"><a name="l02624"></a><span class="lineno"> 2624</span>  <span class="comment">// Since the dilation rate is 3 this will dilate the kernel to be like 7x7,</span></div><div class="line"><a name="l02625"></a><span class="lineno"> 2625</span>  <span class="comment">// therefore the output will be 4x4: (I−K+2P)/S +1 => (10-7 +0)/1 +1</span></div><div class="line"><a name="l02626"></a><span class="lineno"> 2626</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, 1, 4, 4}, ArmnnType);</div><div class="line"><a name="l02627"></a><span class="lineno"> 2627</span>  std::vector<float> outputExpectedNoQuantizedValues =</div><div class="line"><a name="l02628"></a><span class="lineno"> 2628</span>  {</div><div class="line"><a name="l02629"></a><span class="lineno"> 2629</span>  6., 5., 5., 5.,</div><div class="line"><a name="l02630"></a><span class="lineno"> 2630</span>  6., 5., 5., 5.,</div><div class="line"><a name="l02631"></a><span class="lineno"> 2631</span>  6., 5., 5., 5.,</div><div class="line"><a name="l02632"></a><span class="lineno"> 2632</span>  3., 2., 2., 2.</div><div class="line"><a name="l02633"></a><span class="lineno"> 2633</span>  };</div><div class="line"><a name="l02634"></a><span class="lineno"> 2634</span> </div><div class="line"><a name="l02635"></a><span class="lineno"> 2635</span>  <span class="keywordflow">return</span> DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l02636"></a><span class="lineno"> 2636</span>  workloadFactory,</div><div class="line"><a name="l02637"></a><span class="lineno"> 2637</span>  memoryManager,</div><div class="line"><a name="l02638"></a><span class="lineno"> 2638</span>  inputNoQuantizedValues,</div><div class="line"><a name="l02639"></a><span class="lineno"> 2639</span>  inputTensorInfo,</div><div class="line"><a name="l02640"></a><span class="lineno"> 2640</span>  kernelNoQuantizedValues,</div><div class="line"><a name="l02641"></a><span class="lineno"> 2641</span>  kernelTensorInfo,</div><div class="line"><a name="l02642"></a><span class="lineno"> 2642</span>  outputExpectedNoQuantizedValues,</div><div class="line"><a name="l02643"></a><span class="lineno"> 2643</span>  outputTensorInfo,</div><div class="line"><a name="l02644"></a><span class="lineno"> 2644</span>  3,</div><div class="line"><a name="l02645"></a><span class="lineno"> 2645</span>  3,</div><div class="line"><a name="l02646"></a><span class="lineno"> 2646</span>  layout,</div><div class="line"><a name="l02647"></a><span class="lineno"> 2647</span>  biasEnabled);</div><div class="line"><a name="l02648"></a><span class="lineno"> 2648</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><!-- fragment --> +</div> +</div> +<a id="abf326cbf49ec19c6272fe7c244b7817c"></a> +<h2 class="memtitle"><span class="permalink"><a href="#abf326cbf49ec19c6272fe7c244b7817c">◆ </a></span>DepthwiseConvolution2dAsymmetricTest()</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, 4> DepthwiseConvolution2dAsymmetricTest </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03510">3510</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03515"></a><span class="lineno"> 3515</span> {</div><div class="line"><a name="l03516"></a><span class="lineno"> 3516</span>  <span class="keywordflow">return</span> DepthwiseConvolution2dAsymmetricTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l03517"></a><span class="lineno"> 3517</span>  workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout);</div><div class="line"><a name="l03518"></a><span class="lineno"> 3518</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a74346a72d64f7fa3463473424c3098ab"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a74346a72d64f7fa3463473424c3098ab">◆ </a></span>DepthwiseConvolution2dDepthMul1Int16Test()</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><int16_t, 4> DepthwiseConvolution2dDepthMul1Int16Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03562">3562</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03567"></a><span class="lineno"> 3567</span> {</div><div class="line"><a name="l03568"></a><span class="lineno"> 3568</span>  <span class="keywordflow">return</span> DepthwiseConvolution2dDepthMul1TestImpl<armnn::DataType::QSymmS16, armnn::DataType::Signed32>(</div><div class="line"><a name="l03569"></a><span class="lineno"> 3569</span>  workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);</div><div class="line"><a name="l03570"></a><span class="lineno"> 3570</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a8b32d950a40903f502f5e1ec0dcab0bd"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a8b32d950a40903f502f5e1ec0dcab0bd">◆ </a></span>DepthwiseConvolution2dDepthMul1Test()</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, 4> DepthwiseConvolution2dDepthMul1Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03468">3468</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03473"></a><span class="lineno"> 3473</span> {</div><div class="line"><a name="l03474"></a><span class="lineno"> 3474</span>  <span class="keywordflow">return</span> DepthwiseConvolution2dDepthMul1TestImpl<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l03475"></a><span class="lineno"> 3475</span>  workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout);</div><div class="line"><a name="l03476"></a><span class="lineno"> 3476</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="ae797be34b659db2afe183f0c762fb9b7"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ae797be34b659db2afe183f0c762fb9b7">◆ </a></span>DepthwiseConvolution2dDepthMul1Uint8Test()</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><uint8_t, 4> DepthwiseConvolution2dDepthMul1Uint8Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03530">3530</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03535"></a><span class="lineno"> 3535</span> {</div><div class="line"><a name="l03536"></a><span class="lineno"> 3536</span>  <span class="keywordflow">return</span> DepthwiseConvolution2dDepthMul1TestImpl<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>(</div><div class="line"><a name="l03537"></a><span class="lineno"> 3537</span>  workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);</div><div class="line"><a name="l03538"></a><span class="lineno"> 3538</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="ab020b4a99bf905b61a1c5e03332b63a6"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ab020b4a99bf905b61a1c5e03332b63a6">◆ </a></span>DepthwiseConvolution2dDepthMul64Test()</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, 4> DepthwiseConvolution2dDepthMul64Test </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml#l03478">3478</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, and <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>.</p> +<div class="fragment"><div class="line"><a name="l03481"></a><span class="lineno"> 3481</span> {</div><div class="line"><a name="l03482"></a><span class="lineno"> 3482</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({ 1, 1, 2, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l03483"></a><span class="lineno"> 3483</span>  <span class="keyword">auto</span> input = MakeTensor<float, 4>(inputTensorInfo, { 1.f, 2.f, 3.f, 4.f });</div><div class="line"><a name="l03484"></a><span class="lineno"> 3484</span> </div><div class="line"><a name="l03485"></a><span class="lineno"> 3485</span>  std::vector<float> kernelData;</div><div class="line"><a name="l03486"></a><span class="lineno"> 3486</span>  std::vector<float> singleDepthKernel{ 1.f, -1.f, -1.f, 1.f };</div><div class="line"><a name="l03487"></a><span class="lineno"> 3487</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < 64; ++i)</div><div class="line"><a name="l03488"></a><span class="lineno"> 3488</span>  {</div><div class="line"><a name="l03489"></a><span class="lineno"> 3489</span>  kernelData.insert(kernelData.end(), singleDepthKernel.begin(), singleDepthKernel.end());</div><div class="line"><a name="l03490"></a><span class="lineno"> 3490</span>  }</div><div class="line"><a name="l03491"></a><span class="lineno"> 3491</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelTensorInfo({ 64, 1, 2, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l03492"></a><span class="lineno"> 3492</span>  <span class="keyword">auto</span> kernel = MakeTensor<float, 4>(kernelTensorInfo, kernelData);</div><div class="line"><a name="l03493"></a><span class="lineno"> 3493</span> </div><div class="line"><a name="l03494"></a><span class="lineno"> 3494</span>  std::vector<float> expectedOutputData(64, 0.f);</div><div class="line"><a name="l03495"></a><span class="lineno"> 3495</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, 64, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l03496"></a><span class="lineno"> 3496</span>  <span class="keyword">auto</span> expectedOutput = MakeTensor<float, 4>(outputTensorInfo, expectedOutputData);</div><div class="line"><a name="l03497"></a><span class="lineno"> 3497</span> </div><div class="line"><a name="l03498"></a><span class="lineno"> 3498</span>  <span class="keywordflow">return</span> DepthwiseConvolution2dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l03499"></a><span class="lineno"> 3499</span>  workloadFactory,</div><div class="line"><a name="l03500"></a><span class="lineno"> 3500</span>  memoryManager,</div><div class="line"><a name="l03501"></a><span class="lineno"> 3501</span>  input,</div><div class="line"><a name="l03502"></a><span class="lineno"> 3502</span>  kernel,</div><div class="line"><a name="l03503"></a><span class="lineno"> 3503</span>  boost::multi_array<float, 1>(),</div><div class="line"><a name="l03504"></a><span class="lineno"> 3504</span>  expectedOutput,</div><div class="line"><a name="l03505"></a><span class="lineno"> 3505</span>  0.f,</div><div class="line"><a name="l03506"></a><span class="lineno"> 3506</span>  0,</div><div class="line"><a name="l03507"></a><span class="lineno"> 3507</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>);</div><div class="line"><a name="l03508"></a><span class="lineno"> 3508</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_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a0cccb5cffee89004bc8d9fb309ed6636"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a0cccb5cffee89004bc8d9fb309ed6636">◆ </a></span>DepthwiseConvolution2dDepthNhwcTest()</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, 4> DepthwiseConvolution2dDepthNhwcTest </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">bool </td> + <td class="paramname"><em>biasEnabled</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="_conv2d_test_impl_8cpp_source.xhtml#l03459">3459</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03463"></a><span class="lineno"> 3463</span> {</div><div class="line"><a name="l03464"></a><span class="lineno"> 3464</span>  <span class="keywordflow">return</span> DepthwiseConvolution2dNhwcTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l03465"></a><span class="lineno"> 3465</span>  workloadFactory, memoryManager, 0.0f, 0, biasEnabled);</div><div class="line"><a name="l03466"></a><span class="lineno"> 3466</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a2ae97c2dd6621f4972c571cf1ec2a005"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a2ae97c2dd6621f4972c571cf1ec2a005">◆ </a></span>DepthwiseConvolution2dInt16Test()</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><int16_t, 4> DepthwiseConvolution2dInt16Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03552">3552</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03557"></a><span class="lineno"> 3557</span> {</div><div class="line"><a name="l03558"></a><span class="lineno"> 3558</span>  <span class="keywordflow">return</span> DepthwiseConvolution2dTestImpl<armnn::DataType::QSymmS16, armnn::DataType::Signed32>(</div><div class="line"><a name="l03559"></a><span class="lineno"> 3559</span>  workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);</div><div class="line"><a name="l03560"></a><span class="lineno"> 3560</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="aaed50a372a6b59b20e38469856a3ce6b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#aaed50a372a6b59b20e38469856a3ce6b">◆ </a></span>DepthwiseConvolution2dMult2Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> DepthwiseConvolution2dMult2Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l02819">2819</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l02824"></a><span class="lineno"> 2824</span> {</div><div class="line"><a name="l02825"></a><span class="lineno"> 2825</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({1, 2, 3, 3}, ArmnnType);</div><div class="line"><a name="l02826"></a><span class="lineno"> 2826</span>  std::vector<float> inputNoQuantizedValues =</div><div class="line"><a name="l02827"></a><span class="lineno"> 2827</span>  {</div><div class="line"><a name="l02828"></a><span class="lineno"> 2828</span>  10.0, 10.0, 10.0,</div><div class="line"><a name="l02829"></a><span class="lineno"> 2829</span>  10.0, 10.0, 10.0,</div><div class="line"><a name="l02830"></a><span class="lineno"> 2830</span>  10.0, 10.0, 10.0,</div><div class="line"><a name="l02831"></a><span class="lineno"> 2831</span> </div><div class="line"><a name="l02832"></a><span class="lineno"> 2832</span>  21.0, 22.0, 23.0,</div><div class="line"><a name="l02833"></a><span class="lineno"> 2833</span>  24.0, 25.0, 26.0,</div><div class="line"><a name="l02834"></a><span class="lineno"> 2834</span>  27.0, 28.0, 29.0</div><div class="line"><a name="l02835"></a><span class="lineno"> 2835</span>  };</div><div class="line"><a name="l02836"></a><span class="lineno"> 2836</span> </div><div class="line"><a name="l02837"></a><span class="lineno"> 2837</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelTensorInfo({ 2, 2, 2, 2}, ArmnnType);</div><div class="line"><a name="l02838"></a><span class="lineno"> 2838</span> </div><div class="line"><a name="l02839"></a><span class="lineno"> 2839</span>  std::vector<float> kernelNoQuantizedValues =</div><div class="line"><a name="l02840"></a><span class="lineno"> 2840</span>  {</div><div class="line"><a name="l02841"></a><span class="lineno"> 2841</span>  0.25f, 0.25f,</div><div class="line"><a name="l02842"></a><span class="lineno"> 2842</span>  0.25f, 0.25f,</div><div class="line"><a name="l02843"></a><span class="lineno"> 2843</span> </div><div class="line"><a name="l02844"></a><span class="lineno"> 2844</span>  0.2f , 0.0f,</div><div class="line"><a name="l02845"></a><span class="lineno"> 2845</span>  0.0f , 0.0f,</div><div class="line"><a name="l02846"></a><span class="lineno"> 2846</span> </div><div class="line"><a name="l02847"></a><span class="lineno"> 2847</span>  0.0f , 0.0f,</div><div class="line"><a name="l02848"></a><span class="lineno"> 2848</span>  0.0f , 0.1f,</div><div class="line"><a name="l02849"></a><span class="lineno"> 2849</span> </div><div class="line"><a name="l02850"></a><span class="lineno"> 2850</span>  0.0f , 0.3f,</div><div class="line"><a name="l02851"></a><span class="lineno"> 2851</span>  0.0f , 0.0f</div><div class="line"><a name="l02852"></a><span class="lineno"> 2852</span> </div><div class="line"><a name="l02853"></a><span class="lineno"> 2853</span>  };</div><div class="line"><a name="l02854"></a><span class="lineno"> 2854</span> </div><div class="line"><a name="l02855"></a><span class="lineno"> 2855</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, 4, 2, 2}, ArmnnType);</div><div class="line"><a name="l02856"></a><span class="lineno"> 2856</span>  std::vector<float> outputExpectedNoQuantizedValues =</div><div class="line"><a name="l02857"></a><span class="lineno"> 2857</span>  {</div><div class="line"><a name="l02858"></a><span class="lineno"> 2858</span>  10.f, 10.f,</div><div class="line"><a name="l02859"></a><span class="lineno"> 2859</span>  10.f, 10.f,</div><div class="line"><a name="l02860"></a><span class="lineno"> 2860</span> </div><div class="line"><a name="l02861"></a><span class="lineno"> 2861</span>  1.f, 1.f,</div><div class="line"><a name="l02862"></a><span class="lineno"> 2862</span>  1.f, 1.f,</div><div class="line"><a name="l02863"></a><span class="lineno"> 2863</span> </div><div class="line"><a name="l02864"></a><span class="lineno"> 2864</span>  4.2000003f, 4.4f,</div><div class="line"><a name="l02865"></a><span class="lineno"> 2865</span>  4.8f, 5.f,</div><div class="line"><a name="l02866"></a><span class="lineno"> 2866</span> </div><div class="line"><a name="l02867"></a><span class="lineno"> 2867</span>  6.6000004f, 6.9f,</div><div class="line"><a name="l02868"></a><span class="lineno"> 2868</span>  7.5000005f, 7.8f</div><div class="line"><a name="l02869"></a><span class="lineno"> 2869</span>  };</div><div class="line"><a name="l02870"></a><span class="lineno"> 2870</span> </div><div class="line"><a name="l02871"></a><span class="lineno"> 2871</span> </div><div class="line"><a name="l02872"></a><span class="lineno"> 2872</span>  <span class="keywordflow">return</span> DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l02873"></a><span class="lineno"> 2873</span>  workloadFactory,</div><div class="line"><a name="l02874"></a><span class="lineno"> 2874</span>  memoryManager,</div><div class="line"><a name="l02875"></a><span class="lineno"> 2875</span>  inputNoQuantizedValues,</div><div class="line"><a name="l02876"></a><span class="lineno"> 2876</span>  inputTensorInfo,</div><div class="line"><a name="l02877"></a><span class="lineno"> 2877</span>  kernelNoQuantizedValues,</div><div class="line"><a name="l02878"></a><span class="lineno"> 2878</span>  kernelTensorInfo,</div><div class="line"><a name="l02879"></a><span class="lineno"> 2879</span>  outputExpectedNoQuantizedValues,</div><div class="line"><a name="l02880"></a><span class="lineno"> 2880</span>  outputTensorInfo,</div><div class="line"><a name="l02881"></a><span class="lineno"> 2881</span>  1,</div><div class="line"><a name="l02882"></a><span class="lineno"> 2882</span>  1,</div><div class="line"><a name="l02883"></a><span class="lineno"> 2883</span>  layout,</div><div class="line"><a name="l02884"></a><span class="lineno"> 2884</span>  biasEnabled);</div><div class="line"><a name="l02885"></a><span class="lineno"> 2885</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><!-- fragment --> +</div> +</div> +<a id="a0da6534b3a5d2f923dcd73553950129a"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a0da6534b3a5d2f923dcd73553950129a">◆ </a></span>DepthwiseConvolution2dMult4Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><T, 4> DepthwiseConvolution2dMult4Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l02727">2727</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l02732"></a><span class="lineno"> 2732</span> {</div><div class="line"><a name="l02733"></a><span class="lineno"> 2733</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({1, 2, 3, 3}, ArmnnType);</div><div class="line"><a name="l02734"></a><span class="lineno"> 2734</span>  std::vector<float> inputNoQuantizedValues =</div><div class="line"><a name="l02735"></a><span class="lineno"> 2735</span>  {</div><div class="line"><a name="l02736"></a><span class="lineno"> 2736</span>  10.0, 10.0, 10.0,</div><div class="line"><a name="l02737"></a><span class="lineno"> 2737</span>  10.0, 10.0, 10.0,</div><div class="line"><a name="l02738"></a><span class="lineno"> 2738</span>  10.0, 10.0, 10.0,</div><div class="line"><a name="l02739"></a><span class="lineno"> 2739</span> </div><div class="line"><a name="l02740"></a><span class="lineno"> 2740</span>  21.0, 22.0, 23.0,</div><div class="line"><a name="l02741"></a><span class="lineno"> 2741</span>  24.0, 25.0, 26.0,</div><div class="line"><a name="l02742"></a><span class="lineno"> 2742</span>  27.0, 28.0, 29.0</div><div class="line"><a name="l02743"></a><span class="lineno"> 2743</span>  };</div><div class="line"><a name="l02744"></a><span class="lineno"> 2744</span> </div><div class="line"><a name="l02745"></a><span class="lineno"> 2745</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> kernelTensorInfo({ 4, 2, 2, 2}, ArmnnType);</div><div class="line"><a name="l02746"></a><span class="lineno"> 2746</span> </div><div class="line"><a name="l02747"></a><span class="lineno"> 2747</span>  std::vector<float> kernelNoQuantizedValues =</div><div class="line"><a name="l02748"></a><span class="lineno"> 2748</span>  {</div><div class="line"><a name="l02749"></a><span class="lineno"> 2749</span>  0.25f, 0.25f,</div><div class="line"><a name="l02750"></a><span class="lineno"> 2750</span>  0.25f, 0.25f,</div><div class="line"><a name="l02751"></a><span class="lineno"> 2751</span> </div><div class="line"><a name="l02752"></a><span class="lineno"> 2752</span>  0.25f, 0.25f,</div><div class="line"><a name="l02753"></a><span class="lineno"> 2753</span>  0.25f, 0.25f,</div><div class="line"><a name="l02754"></a><span class="lineno"> 2754</span> </div><div class="line"><a name="l02755"></a><span class="lineno"> 2755</span>  0.0f , 0.0f,</div><div class="line"><a name="l02756"></a><span class="lineno"> 2756</span>  0.0f , 0.1f,</div><div class="line"><a name="l02757"></a><span class="lineno"> 2757</span> </div><div class="line"><a name="l02758"></a><span class="lineno"> 2758</span>  0.0f , 0.0f,</div><div class="line"><a name="l02759"></a><span class="lineno"> 2759</span>  0.0f , 0.1f,</div><div class="line"><a name="l02760"></a><span class="lineno"> 2760</span> </div><div class="line"><a name="l02761"></a><span class="lineno"> 2761</span>  0.2f , 0.0f,</div><div class="line"><a name="l02762"></a><span class="lineno"> 2762</span>  0.0f , 0.0f,</div><div class="line"><a name="l02763"></a><span class="lineno"> 2763</span> </div><div class="line"><a name="l02764"></a><span class="lineno"> 2764</span>  0.2f , 0.0f,</div><div class="line"><a name="l02765"></a><span class="lineno"> 2765</span>  0.0f , 0.0f,</div><div class="line"><a name="l02766"></a><span class="lineno"> 2766</span> </div><div class="line"><a name="l02767"></a><span class="lineno"> 2767</span>  0.0f , 0.3f,</div><div class="line"><a name="l02768"></a><span class="lineno"> 2768</span>  0.0f , 0.0f,</div><div class="line"><a name="l02769"></a><span class="lineno"> 2769</span> </div><div class="line"><a name="l02770"></a><span class="lineno"> 2770</span>  0.0f , 0.3f,</div><div class="line"><a name="l02771"></a><span class="lineno"> 2771</span>  0.0f , 0.0f</div><div class="line"><a name="l02772"></a><span class="lineno"> 2772</span>  };</div><div class="line"><a name="l02773"></a><span class="lineno"> 2773</span> </div><div class="line"><a name="l02774"></a><span class="lineno"> 2774</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, 8, 2, 2}, ArmnnType);</div><div class="line"><a name="l02775"></a><span class="lineno"> 2775</span>  std::vector<float> outputExpectedNoQuantizedValues =</div><div class="line"><a name="l02776"></a><span class="lineno"> 2776</span>  {</div><div class="line"><a name="l02777"></a><span class="lineno"> 2777</span>  10.f, 10.f,</div><div class="line"><a name="l02778"></a><span class="lineno"> 2778</span>  10.f, 10.f,</div><div class="line"><a name="l02779"></a><span class="lineno"> 2779</span> </div><div class="line"><a name="l02780"></a><span class="lineno"> 2780</span>  1.f, 1.f,</div><div class="line"><a name="l02781"></a><span class="lineno"> 2781</span>  1.f, 1.f,</div><div class="line"><a name="l02782"></a><span class="lineno"> 2782</span> </div><div class="line"><a name="l02783"></a><span class="lineno"> 2783</span>  2.f, 2.f,</div><div class="line"><a name="l02784"></a><span class="lineno"> 2784</span>  2.f, 2.f,</div><div class="line"><a name="l02785"></a><span class="lineno"> 2785</span> </div><div class="line"><a name="l02786"></a><span class="lineno"> 2786</span>  3.f, 3.f,</div><div class="line"><a name="l02787"></a><span class="lineno"> 2787</span>  3.f, 3.f,</div><div class="line"><a name="l02788"></a><span class="lineno"> 2788</span> </div><div class="line"><a name="l02789"></a><span class="lineno"> 2789</span>  23.f, 24.f,</div><div class="line"><a name="l02790"></a><span class="lineno"> 2790</span>  26.f, 27.f,</div><div class="line"><a name="l02791"></a><span class="lineno"> 2791</span> </div><div class="line"><a name="l02792"></a><span class="lineno"> 2792</span>  2.5f, 2.6000001f,</div><div class="line"><a name="l02793"></a><span class="lineno"> 2793</span>  2.8f, 2.9f,</div><div class="line"><a name="l02794"></a><span class="lineno"> 2794</span> </div><div class="line"><a name="l02795"></a><span class="lineno"> 2795</span>  4.2000003f, 4.4f,</div><div class="line"><a name="l02796"></a><span class="lineno"> 2796</span>  4.8f, 5.f,</div><div class="line"><a name="l02797"></a><span class="lineno"> 2797</span> </div><div class="line"><a name="l02798"></a><span class="lineno"> 2798</span>  6.6000004f, 6.9f,</div><div class="line"><a name="l02799"></a><span class="lineno"> 2799</span>  7.5000005f, 7.8f</div><div class="line"><a name="l02800"></a><span class="lineno"> 2800</span>  };</div><div class="line"><a name="l02801"></a><span class="lineno"> 2801</span> </div><div class="line"><a name="l02802"></a><span class="lineno"> 2802</span> </div><div class="line"><a name="l02803"></a><span class="lineno"> 2803</span>  <span class="keywordflow">return</span> DepthwiseConvolution2d3x3DilationTestCommon<ArmnnType, ArmnnBType>(</div><div class="line"><a name="l02804"></a><span class="lineno"> 2804</span>  workloadFactory,</div><div class="line"><a name="l02805"></a><span class="lineno"> 2805</span>  memoryManager,</div><div class="line"><a name="l02806"></a><span class="lineno"> 2806</span>  inputNoQuantizedValues,</div><div class="line"><a name="l02807"></a><span class="lineno"> 2807</span>  inputTensorInfo,</div><div class="line"><a name="l02808"></a><span class="lineno"> 2808</span>  kernelNoQuantizedValues,</div><div class="line"><a name="l02809"></a><span class="lineno"> 2809</span>  kernelTensorInfo,</div><div class="line"><a name="l02810"></a><span class="lineno"> 2810</span>  outputExpectedNoQuantizedValues,</div><div class="line"><a name="l02811"></a><span class="lineno"> 2811</span>  outputTensorInfo,</div><div class="line"><a name="l02812"></a><span class="lineno"> 2812</span>  1,</div><div class="line"><a name="l02813"></a><span class="lineno"> 2813</span>  1,</div><div class="line"><a name="l02814"></a><span class="lineno"> 2814</span>  layout,</div><div class="line"><a name="l02815"></a><span class="lineno"> 2815</span>  biasEnabled);</div><div class="line"><a name="l02816"></a><span class="lineno"> 2816</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><!-- fragment --> +</div> +</div> +<a id="a8a51827c480f827c1e29f9347d7433c3"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a8a51827c480f827c1e29f9347d7433c3">◆ </a></span>DepthwiseConvolution2dPerAxisQuantTest()</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><uint8_t, 4> DepthwiseConvolution2dPerAxisQuantTest </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="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03572">3572</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_deprecated_8hpp_source.xhtml#l00033">ARMNN_NO_DEPRECATE_WARN_BEGIN</a>, <a class="el" href="_deprecated_8hpp_source.xhtml#l00034">ARMNN_NO_DEPRECATE_WARN_END</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#l01320">IWorkloadFactory::CreateDepthwiseConvolution2d()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00498">DepthwiseConvolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00500">DepthwiseConvolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00494">DepthwiseConvolution2dDescriptor::m_DilationX</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00496">DepthwiseConvolution2dDescriptor::m_DilationY</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00488">DepthwiseConvolution2dDescriptor::m_PadBottom</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00482">DepthwiseConvolution2dDescriptor::m_PadLeft</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00484">DepthwiseConvolution2dDescriptor::m_PadRight</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00486">DepthwiseConvolution2dDescriptor::m_PadTop</a>, <a class="el" href="_workload_data_8hpp_source.xhtml#l00049">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00490">DepthwiseConvolution2dDescriptor::m_StrideX</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00492">DepthwiseConvolution2dDescriptor::m_StrideY</a>, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::NCHW</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00041">LayerTestResult< T, n >::output</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00042">LayerTestResult< T, n >::outputExpected</a>, and <a class="el" href="_data_layout_utils_8hpp_source.xhtml#l00026">PermuteTensorNhwcToNchw()</a>.</p> +<div class="fragment"><div class="line"><a name="l03576"></a><span class="lineno"> 3576</span> {</div><div class="line"><a name="l03577"></a><span class="lineno"> 3577</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l03578"></a><span class="lineno"> 3578</span> </div><div class="line"><a name="l03579"></a><span class="lineno"> 3579</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> inputType = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>;</div><div class="line"><a name="l03580"></a><span class="lineno"> 3580</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> kernelType = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>;</div><div class="line"><a name="l03581"></a><span class="lineno"> 3581</span>  <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> biasType = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>;</div><div class="line"><a name="l03582"></a><span class="lineno"> 3582</span> </div><div class="line"><a name="l03583"></a><span class="lineno"> 3583</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo ({ 1, 3, 3, 2 }, inputType, 0.5f, 128); <span class="comment">// N H W C</span></div><div class="line"><a name="l03584"></a><span class="lineno"> 3584</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 2, 2, 4 }, inputType, 1.0f, 128); <span class="comment">// N H W C</span></div><div class="line"><a name="l03585"></a><span class="lineno"> 3585</span> </div><div class="line"><a name="l03586"></a><span class="lineno"> 3586</span>  <span class="keyword">const</span> std::vector<float> quantScales{ 1.0f, 0.5f, 1.0f, 0.5f };</div><div class="line"><a name="l03587"></a><span class="lineno"> 3587</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantDimension = 0;</div><div class="line"><a name="l03588"></a><span class="lineno"> 3588</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> kernelInfo({ 2, 2, 2, 2 }, kernelType, quantScales, quantDimension); <span class="comment">// M I H W</span></div><div class="line"><a name="l03589"></a><span class="lineno"> 3589</span> </div><div class="line"><a name="l03590"></a><span class="lineno"> 3590</span>  <span class="keyword">const</span> std::vector<float> biasQuantScales{ 0.5f, 0.25f, 0.5f, 0.25f };</div><div class="line"><a name="l03591"></a><span class="lineno"> 3591</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> biasQuantDimension = 0;</div><div class="line"><a name="l03592"></a><span class="lineno"> 3592</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> biasInfo({ 4 }, biasType, biasQuantScales, biasQuantDimension);</div><div class="line"><a name="l03593"></a><span class="lineno"> 3593</span> </div><div class="line"><a name="l03594"></a><span class="lineno"> 3594</span>  std::vector<uint8_t> inputData =</div><div class="line"><a name="l03595"></a><span class="lineno"> 3595</span>  {</div><div class="line"><a name="l03596"></a><span class="lineno"> 3596</span>  129, 130,</div><div class="line"><a name="l03597"></a><span class="lineno"> 3597</span>  129, 130,</div><div class="line"><a name="l03598"></a><span class="lineno"> 3598</span>  129, 130,</div><div class="line"><a name="l03599"></a><span class="lineno"> 3599</span>  129, 130,</div><div class="line"><a name="l03600"></a><span class="lineno"> 3600</span>  129, 130,</div><div class="line"><a name="l03601"></a><span class="lineno"> 3601</span>  129, 130,</div><div class="line"><a name="l03602"></a><span class="lineno"> 3602</span>  129, 130,</div><div class="line"><a name="l03603"></a><span class="lineno"> 3603</span>  129, 130,</div><div class="line"><a name="l03604"></a><span class="lineno"> 3604</span>  129, 130</div><div class="line"><a name="l03605"></a><span class="lineno"> 3605</span>  };</div><div class="line"><a name="l03606"></a><span class="lineno"> 3606</span> </div><div class="line"><a name="l03607"></a><span class="lineno"> 3607</span>  std::vector<int8_t> kernelData =</div><div class="line"><a name="l03608"></a><span class="lineno"> 3608</span>  {</div><div class="line"><a name="l03609"></a><span class="lineno"> 3609</span>  1, 1, 1, 1,</div><div class="line"><a name="l03610"></a><span class="lineno"> 3610</span>  1, 1, 1, 1,</div><div class="line"><a name="l03611"></a><span class="lineno"> 3611</span>  1, 1, 1, 1,</div><div class="line"><a name="l03612"></a><span class="lineno"> 3612</span>  1, 1, 1, 1</div><div class="line"><a name="l03613"></a><span class="lineno"> 3613</span>  };</div><div class="line"><a name="l03614"></a><span class="lineno"> 3614</span> </div><div class="line"><a name="l03615"></a><span class="lineno"> 3615</span>  std::vector<int32_t> biasData =</div><div class="line"><a name="l03616"></a><span class="lineno"> 3616</span>  {</div><div class="line"><a name="l03617"></a><span class="lineno"> 3617</span>  4, 4, 4, 4</div><div class="line"><a name="l03618"></a><span class="lineno"> 3618</span>  };</div><div class="line"><a name="l03619"></a><span class="lineno"> 3619</span> </div><div class="line"><a name="l03620"></a><span class="lineno"> 3620</span>  std::vector<uint8_t> expectedOutputData =</div><div class="line"><a name="l03621"></a><span class="lineno"> 3621</span>  {</div><div class="line"><a name="l03622"></a><span class="lineno"> 3622</span>  132, 130, 134, 131,</div><div class="line"><a name="l03623"></a><span class="lineno"> 3623</span>  132, 130, 134, 131,</div><div class="line"><a name="l03624"></a><span class="lineno"> 3624</span>  132, 130, 134, 131,</div><div class="line"><a name="l03625"></a><span class="lineno"> 3625</span>  132, 130, 134, 131</div><div class="line"><a name="l03626"></a><span class="lineno"> 3626</span>  };</div><div class="line"><a name="l03627"></a><span class="lineno"> 3627</span> </div><div class="line"><a name="l03628"></a><span class="lineno"> 3628</span>  <span class="keywordflow">if</span> (layout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div><div class="line"><a name="l03629"></a><span class="lineno"> 3629</span>  {</div><div class="line"><a name="l03630"></a><span class="lineno"> 3630</span>  <a class="code" href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(inputInfo, inputData);</div><div class="line"><a name="l03631"></a><span class="lineno"> 3631</span>  <a class="code" href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(outputInfo, expectedOutputData);</div><div class="line"><a name="l03632"></a><span class="lineno"> 3632</span>  }</div><div class="line"><a name="l03633"></a><span class="lineno"> 3633</span> </div><div class="line"><a name="l03634"></a><span class="lineno"> 3634</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l03635"></a><span class="lineno"> 3635</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 1;</div><div class="line"><a name="l03636"></a><span class="lineno"> 3636</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l03637"></a><span class="lineno"> 3637</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 0;</div><div class="line"><a name="l03638"></a><span class="lineno"> 3638</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 0;</div><div class="line"><a name="l03639"></a><span class="lineno"> 3639</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 0;</div><div class="line"><a name="l03640"></a><span class="lineno"> 3640</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l03641"></a><span class="lineno"> 3641</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = 1;</div><div class="line"><a name="l03642"></a><span class="lineno"> 3642</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = 1;</div><div class="line"><a name="l03643"></a><span class="lineno"> 3643</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l03644"></a><span class="lineno"> 3644</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = layout;</div><div class="line"><a name="l03645"></a><span class="lineno"> 3645</span> </div><div class="line"><a name="l03646"></a><span class="lineno"> 3646</span>  <a class="code" href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l03647"></a><span class="lineno"> 3647</span>  std::unique_ptr<ITensorHandle> inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputInfo);</div><div class="line"><a name="l03648"></a><span class="lineno"> 3648</span>  std::unique_ptr<ITensorHandle> outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputInfo);</div><div class="line"><a name="l03649"></a><span class="lineno"> 3649</span>  <a class="code" href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="line"><a name="l03650"></a><span class="lineno"> 3650</span> </div><div class="line"><a name="l03651"></a><span class="lineno"> 3651</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l03652"></a><span class="lineno"> 3652</span>  <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">ScopedCpuTensorHandle</a> weightTensor(kernelInfo);</div><div class="line"><a name="l03653"></a><span class="lineno"> 3653</span>  <a class="code" href="classarmnn_1_1_scoped_cpu_tensor_handle.xhtml">ScopedCpuTensorHandle</a> biasTensor(biasInfo);</div><div class="line"><a name="l03654"></a><span class="lineno"> 3654</span> </div><div class="line"><a name="l03655"></a><span class="lineno"> 3655</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&weightTensor, kernelData.data());</div><div class="line"><a name="l03656"></a><span class="lineno"> 3656</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&biasTensor, biasData.data());</div><div class="line"><a name="l03657"></a><span class="lineno"> 3657</span> </div><div class="line"><a name="l03658"></a><span class="lineno"> 3658</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">DepthwiseConvolution2dQueueDescriptor</a> queueDescriptor;</div><div class="line"><a name="l03659"></a><span class="lineno"> 3659</span>  queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a> = descriptor;</div><div class="line"><a name="l03660"></a><span class="lineno"> 3660</span>  queueDescriptor.m_Weight = &weightTensor;</div><div class="line"><a name="l03661"></a><span class="lineno"> 3661</span>  queueDescriptor.m_Bias = &biasTensor;</div><div class="line"><a name="l03662"></a><span class="lineno"> 3662</span> </div><div class="line"><a name="l03663"></a><span class="lineno"> 3663</span>  AddInputToWorkload(queueDescriptor, workloadInfo, inputInfo, inputHandle.get());</div><div class="line"><a name="l03664"></a><span class="lineno"> 3664</span>  AddOutputToWorkload(queueDescriptor, workloadInfo, outputInfo, outputHandle.get());</div><div class="line"><a name="l03665"></a><span class="lineno"> 3665</span> </div><div class="line"><a name="l03666"></a><span class="lineno"> 3666</span>  std::unique_ptr<IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#accb9759dfd2880efe0f8d2705ddee448">CreateDepthwiseConvolution2d</a>(queueDescriptor, workloadInfo);</div><div class="line"><a name="l03667"></a><span class="lineno"> 3667</span>  inputHandle->Allocate();</div><div class="line"><a name="l03668"></a><span class="lineno"> 3668</span>  outputHandle->Allocate();</div><div class="line"><a name="l03669"></a><span class="lineno"> 3669</span> </div><div class="line"><a name="l03670"></a><span class="lineno"> 3670</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputData.data());</div><div class="line"><a name="l03671"></a><span class="lineno"> 3671</span> </div><div class="line"><a name="l03672"></a><span class="lineno"> 3672</span>  ExecuteWorkload(*workload, memoryManager);</div><div class="line"><a name="l03673"></a><span class="lineno"> 3673</span> </div><div class="line"><a name="l03674"></a><span class="lineno"> 3674</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> ret(outputInfo);</div><div class="line"><a name="l03675"></a><span class="lineno"> 3675</span> </div><div class="line"><a name="l03676"></a><span class="lineno"> 3676</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(ret.output.origin(), outputHandle.get());</div><div class="line"><a name="l03677"></a><span class="lineno"> 3677</span>  ret.outputExpected = MakeTensor<uint8_t, 4>(outputInfo, expectedOutputData);</div><div class="line"><a name="l03678"></a><span class="lineno"> 3678</span> </div><div class="line"><a name="l03679"></a><span class="lineno"> 3679</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l03680"></a><span class="lineno"> 3680</span> }</div><div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::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#l00498">Descriptors.hpp:498</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::DepthwiseConvolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00488">Descriptors.hpp:488</a></div></div> +<div class="ttc" id="_deprecated_8hpp_xhtml_ab66a241a0ed3ee89c866e777b035d0ed"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_BEGIN</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00033">Deprecated.hpp:33</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00500">Descriptors.hpp:500</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_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::DepthwiseConvolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00482">Descriptors.hpp:482</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div> +<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> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::DepthwiseConvolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation factor value for height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00496">Descriptors.hpp:496</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::DepthwiseConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00490">Descriptors.hpp:490</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00032">Types.hpp:32</a></div></div> +<div class="ttc" id="_deprecated_8hpp_xhtml_ad762b11b48e5c1d1c1743f529485728a"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_END</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00034">Deprecated.hpp:34</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::DepthwiseConvolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation factor value for width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00494">Descriptors.hpp:494</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::DepthwiseConvolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00486">Descriptors.hpp:486</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div> +<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> +<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="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< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0</div></div> +<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> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::DepthwiseConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00492">Descriptors.hpp:492</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00030">LayerTestResult.hpp:30</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_accb9759dfd2880efe0f8d2705ddee448"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#accb9759dfd2880efe0f8d2705ddee448">armnn::IWorkloadFactory::CreateDepthwiseConvolution2d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateDepthwiseConvolution2d(const DepthwiseConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01320">WorkloadFactory.cpp:1320</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00452">Descriptors.hpp:452</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">armnn::DepthwiseConvolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00189">WorkloadData.hpp:189</a></div></div> +<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::DepthwiseConvolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00484">Descriptors.hpp:484</a></div></div> +<div class="ttc" id="_data_layout_utils_8hpp_xhtml_a1452f049aef30409b3b649af2be7ff82"><div class="ttname"><a href="_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a></div><div class="ttdeci">void PermuteTensorNhwcToNchw(armnn::TensorInfo &tensorInfo, std::vector< T > &tensorData)</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_utils_8hpp_source.xhtml#l00026">DataLayoutUtils.hpp:26</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a11fbd94028ab646528b42d0c8c55eee1"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a11fbd94028ab646528b42d0c8c55eee1">◆ </a></span>DepthwiseConvolution2dTest()</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, 4> DepthwiseConvolution2dTest </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03449">3449</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03454"></a><span class="lineno"> 3454</span> {</div><div class="line"><a name="l03455"></a><span class="lineno"> 3455</span>  <span class="keywordflow">return</span> DepthwiseConvolution2dTestImpl<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l03456"></a><span class="lineno"> 3456</span>  workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout);</div><div class="line"><a name="l03457"></a><span class="lineno"> 3457</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a8076c31bd6e9eae629994a89a5fa18c3"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a8076c31bd6e9eae629994a89a5fa18c3">◆ </a></span>DepthwiseConvolution2dUint8Test()</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><uint8_t, 4> DepthwiseConvolution2dUint8Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03520">3520</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03525"></a><span class="lineno"> 3525</span> {</div><div class="line"><a name="l03526"></a><span class="lineno"> 3526</span>  <span class="keywordflow">return</span> DepthwiseConvolution2dTestImpl<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>(</div><div class="line"><a name="l03527"></a><span class="lineno"> 3527</span>  workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);</div><div class="line"><a name="l03528"></a><span class="lineno"> 3528</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="ac7bae01fdca8edac70cc9bc722426b17"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ac7bae01fdca8edac70cc9bc722426b17">◆ </a></span>SimpleConvolution2d3x3NhwcTest()</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, 4> SimpleConvolution2d3x3NhwcTest </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">bool </td> + <td class="paramname"><em>biasEnabled</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="_conv2d_test_impl_8cpp_source.xhtml#l03250">3250</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> +<div class="fragment"><div class="line"><a name="l03254"></a><span class="lineno"> 3254</span> {</div><div class="line"><a name="l03255"></a><span class="lineno"> 3255</span>  <span class="keywordflow">return</span> SimpleConvolution2d3x3NhwcTestCommon<armnn::DataType::Float32>(</div><div class="line"><a name="l03256"></a><span class="lineno"> 3256</span>  workloadFactory,</div><div class="line"><a name="l03257"></a><span class="lineno"> 3257</span>  memoryManager,</div><div class="line"><a name="l03258"></a><span class="lineno"> 3258</span>  0.f,</div><div class="line"><a name="l03259"></a><span class="lineno"> 3259</span>  0,</div><div class="line"><a name="l03260"></a><span class="lineno"> 3260</span>  biasEnabled,</div><div class="line"><a name="l03261"></a><span class="lineno"> 3261</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>);</div><div class="line"><a name="l03262"></a><span class="lineno"> 3262</span> }</div><div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="abac8f73ae590a93fe91115371ae4ced3"></a> +<h2 class="memtitle"><span class="permalink"><a href="#abac8f73ae590a93fe91115371ae4ced3">◆ </a></span>SimpleConvolution2d3x3QSymm16Test()</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><int16_t, 4> SimpleConvolution2d3x3QSymm16Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03299">3299</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03304"></a><span class="lineno"> 3304</span> {</div><div class="line"><a name="l03305"></a><span class="lineno"> 3305</span>  <span class="keywordflow">return</span> SimpleConvolution2d3x3TestCommon<armnn::DataType::QSymmS16, armnn::DataType::Signed32>(</div><div class="line"><a name="l03306"></a><span class="lineno"> 3306</span>  workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);</div><div class="line"><a name="l03307"></a><span class="lineno"> 3307</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="af4ac6874d18e1cb59873a17073512873"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af4ac6874d18e1cb59873a17073512873">◆ </a></span>SimpleConvolution2d3x3Stride2x2Test()</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, 4> SimpleConvolution2d3x3Stride2x2Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03264">3264</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03269"></a><span class="lineno"> 3269</span> {</div><div class="line"><a name="l03270"></a><span class="lineno"> 3270</span>  <span class="keywordflow">return</span> SimpleConvolution2d3x3Stride2x2TestCommon<armnn::DataType::Float32>(</div><div class="line"><a name="l03271"></a><span class="lineno"> 3271</span>  workloadFactory,</div><div class="line"><a name="l03272"></a><span class="lineno"> 3272</span>  memoryManager,</div><div class="line"><a name="l03273"></a><span class="lineno"> 3273</span>  0.f,</div><div class="line"><a name="l03274"></a><span class="lineno"> 3274</span>  0,</div><div class="line"><a name="l03275"></a><span class="lineno"> 3275</span>  biasEnabled,</div><div class="line"><a name="l03276"></a><span class="lineno"> 3276</span>  layout);</div><div class="line"><a name="l03277"></a><span class="lineno"> 3277</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="acbe1a2adccd9e0aad14fc0ccb9266b0d"></a> +<h2 class="memtitle"><span class="permalink"><a href="#acbe1a2adccd9e0aad14fc0ccb9266b0d">◆ </a></span>SimpleConvolution2d3x3Test()</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, 4> SimpleConvolution2d3x3Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03240">3240</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03245"></a><span class="lineno"> 3245</span> {</div><div class="line"><a name="l03246"></a><span class="lineno"> 3246</span>  <span class="keywordflow">return</span> SimpleConvolution2d3x3TestCommon<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l03247"></a><span class="lineno"> 3247</span>  workloadFactory, memoryManager, 0.f, 0, biasEnabled, layout);</div><div class="line"><a name="l03248"></a><span class="lineno"> 3248</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="ad45f359d9d4bee360bee857faa79d292"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ad45f359d9d4bee360bee857faa79d292">◆ </a></span>SimpleConvolution2d3x3Uint8Test()</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><uint8_t, 4> SimpleConvolution2d3x3Uint8Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03279">3279</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03284"></a><span class="lineno"> 3284</span> {</div><div class="line"><a name="l03285"></a><span class="lineno"> 3285</span>  <span class="keywordflow">return</span> SimpleConvolution2d3x3TestCommon<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>(</div><div class="line"><a name="l03286"></a><span class="lineno"> 3286</span>  workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);</div><div class="line"><a name="l03287"></a><span class="lineno"> 3287</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a9dcd2fb98f5c3284c74f65a7c7a69da1"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a9dcd2fb98f5c3284c74f65a7c7a69da1">◆ </a></span>SimpleConvolution2d3x5QSymm16Test()</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><int16_t, 4> SimpleConvolution2d3x5QSymm16Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03289">3289</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03294"></a><span class="lineno"> 3294</span> {</div><div class="line"><a name="l03295"></a><span class="lineno"> 3295</span>  <span class="keywordflow">return</span> SimpleConvolution2d3x5TestCommon<armnn::DataType::QSymmS16, armnn::DataType::Signed32>(</div><div class="line"><a name="l03296"></a><span class="lineno"> 3296</span>  workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);</div><div class="line"><a name="l03297"></a><span class="lineno"> 3297</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="afb5e7d86e241292d9cb899b960da54af"></a> +<h2 class="memtitle"><span class="permalink"><a href="#afb5e7d86e241292d9cb899b960da54af">◆ </a></span>SimpleConvolution2d3x5Test()</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, 4> SimpleConvolution2d3x5Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03220">3220</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03225"></a><span class="lineno"> 3225</span> {</div><div class="line"><a name="l03226"></a><span class="lineno"> 3226</span>  <span class="keywordflow">return</span> SimpleConvolution2d3x5TestCommon<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l03227"></a><span class="lineno"> 3227</span>  workloadFactory, memoryManager, 0.f, 0, biasEnabled, layout);</div><div class="line"><a name="l03228"></a><span class="lineno"> 3228</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a8ffca1c4b38a68b10ba06f4f1416660f"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a8ffca1c4b38a68b10ba06f4f1416660f">◆ </a></span>SimpleConvolution2d3x5Uint8Test()</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><uint8_t, 4> SimpleConvolution2d3x5Uint8Test </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">bool </td> + <td class="paramname"><em>biasEnabled</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> </td> + <td class="paramname"><em>layout</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="_conv2d_test_impl_8cpp_source.xhtml#l03230">3230</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03235"></a><span class="lineno"> 3235</span> {</div><div class="line"><a name="l03236"></a><span class="lineno"> 3236</span>  <span class="keywordflow">return</span> SimpleConvolution2d3x5TestCommon<armnn::DataType::QAsymmU8, armnn::DataType::Signed32>(</div><div class="line"><a name="l03237"></a><span class="lineno"> 3237</span>  workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);</div><div class="line"><a name="l03238"></a><span class="lineno"> 3238</span> }</div></div><!-- fragment --> +</div> +</div> +<a id="a77a29527216d36bce78e88354462ede8"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a77a29527216d36bce78e88354462ede8">◆ </a></span>SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTest()</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, 4> SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml#l03540">3540</a> of file <a class="el" href="_conv2d_test_impl_8cpp_source.xhtml">Conv2dTestImpl.cpp</a>.</p> +<div class="fragment"><div class="line"><a name="l03543"></a><span class="lineno"> 3543</span> {</div><div class="line"><a name="l03544"></a><span class="lineno"> 3544</span>  <span class="keywordflow">return</span> SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTestCommon<armnn::DataType::Float32, armnn::DataType::Float32>(</div><div class="line"><a name="l03545"></a><span class="lineno"> 3545</span>  workloadFactory,</div><div class="line"><a name="l03546"></a><span class="lineno"> 3546</span>  memoryManager,</div><div class="line"><a name="l03547"></a><span class="lineno"> 3547</span>  0.f,</div><div class="line"><a name="l03548"></a><span class="lineno"> 3548</span>  0,</div><div class="line"><a name="l03549"></a><span class="lineno"> 3549</span>  <span class="keyword">false</span>);</div><div class="line"><a name="l03550"></a><span class="lineno"> 3550</span> }</div></div><!-- fragment --> +</div> +</div> +</div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.xhtml">backendsCommon</a></li><li class="navelem"><a class="el" href="dir_28bfe507f7e135bdae07c2a6b7f66696.xhtml">test</a></li><li class="navelem"><a class="el" href="dir_99a30439342d160875b21dac3498ad7f.xhtml">layerTests</a></li><li class="navelem"><a class="el" href="_conv2d_test_impl_8hpp.xhtml">Conv2dTestImpl.hpp</a></li> + <li class="footer">Generated on Tue Aug 25 2020 12:29:46 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li> + </ul> +</div> +</body> +</html> |