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| author | Nikhil Raj <nikhil.raj@arm.com> | 2022-06-17 13:24:58 +0100 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-06-17 13:24:58 +0100 |
| commit | d5d43d82c0137e08553e44345c609cdd1a7931c7 (patch) | |
| tree | f1509f7fa94db0373a2c127682dd3d0ccc1915bd /22.05.01/_depthwise_convolution2d_end_to_end_tests_8hpp_source.xhtml | |
| parent | 549b9600a6eaf0727fa084465a75f173edf8f381 (diff) | |
| download | armnn-d5d43d82c0137e08553e44345c609cdd1a7931c7.tar.gz | |
Update Doxygen for 22.05 patch release
* Pooling3D added to tfLite delegate
* Available in tag 22.05.01
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: I8d605bba4e87d30baa2c6d7b338c78a4400dc021
Diffstat (limited to '22.05.01/_depthwise_convolution2d_end_to_end_tests_8hpp_source.xhtml')
| -rw-r--r-- | 22.05.01/_depthwise_convolution2d_end_to_end_tests_8hpp_source.xhtml | 139 |
1 files changed, 139 insertions, 0 deletions
diff --git a/22.05.01/_depthwise_convolution2d_end_to_end_tests_8hpp_source.xhtml b/22.05.01/_depthwise_convolution2d_end_to_end_tests_8hpp_source.xhtml new file mode 100644 index 0000000000..146f7e42cb --- /dev/null +++ b/22.05.01/_depthwise_convolution2d_end_to_end_tests_8hpp_source.xhtml @@ -0,0 +1,139 @@ +<!-- 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/DepthwiseConvolution2dEndToEndTests.hpp Source File</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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">22.05.01</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(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('_depthwise_convolution2d_end_to_end_tests_8hpp_source.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="headertitle"> +<div class="title">DepthwiseConvolution2dEndToEndTests.hpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_depthwise_convolution2d_end_to_end_tests_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_end_to_end_test_impl_8hpp.xhtml">EndToEndTestImpl.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_quantize_helper_8hpp.xhtml">armnnUtils/QuantizeHelper.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="backends_2backends_common_2test_2_common_test_utils_8hpp.xhtml">CommonTestUtils.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="include_2armnn_test_utils_2_data_layout_utils_8hpp.xhtml">armnnTestUtils/DataLayoutUtils.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <map></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <vector></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> {</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> CreateDepthwiseConvolution2dNetwork(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a>& descriptor,</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& inputInfo,</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& weightsInfo,</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& biasInfo,</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& outputInfo,</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>& weights,</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>& biases)</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> {</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>());</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input = network->AddInputLayer(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* weightsLayer = network->AddConstantLayer(weights, <span class="stringliteral">"Weights"</span>);</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* biasLayer = network->AddConstantLayer(biases, <span class="stringliteral">"Bias"</span>);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* convolution2d = network->AddDepthwiseConvolution2dLayer(descriptor, <span class="stringliteral">"depthwiseConvolution2d"</span>);</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = network->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> </div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, convolution2d, inputInfo, 0, 0);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(weightsLayer, convolution2d, weightsInfo, 0, 1);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(biasLayer, convolution2d, biasInfo, 0, 2);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(convolution2d, output, outputInfo, 0, 0);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordflow">return</span> network;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> }</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> } <span class="comment">// anonymous namespace</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> </div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="keyword">template</span><armnn::DataType ArmnnType, armnn::DataType ArmnnBType></div><div class="line"><a name="l00049"></a><span class="lineno"><a class="line" href="_depthwise_convolution2d_end_to_end_tests_8hpp.xhtml#a0e45acb473ac9b518987058b0f6bfc86"> 49</a></span> <span class="keywordtype">void</span> <a class="code" href="_depthwise_convolution2d_end_to_end_tests_8hpp.xhtml#a0e45acb473ac9b518987058b0f6bfc86">DepthwiseConvolution2dEndToEnd</a>(<span class="keyword">const</span> std::vector<armnn::BackendId>& backends,</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout)</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> {</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">using</span> T = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">ResolveType<ArmnnType></a>;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keyword">using</span> BT = <a class="code" href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">ResolveType<ArmnnBType></a>;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> qScale = IsQuantizedType<T>() ? 0.25f : 1.0f;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">const</span> int32_t qOffset = IsQuantizedType<T>() ? 50 : 0;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> depthMultiplier = 2;</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 8;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 16;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 2;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize = 1;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> </div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernelHeight = 5;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> kernelWidth = 3;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> </div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = inputHeight - kernelHeight + 1 + 2;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = (inputWidth - kernelWidth + 1)/2;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = inputChannels * depthMultiplier;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputBatchSize = inputBatchSize;</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, ArmnnType, qScale, qOffset, <span class="keyword">true</span>);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, ArmnnType, qScale, qOffset);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> weightsInfo({1, kernelHeight, kernelWidth, outputChannels}, ArmnnType, qScale, qOffset, <span class="keyword">true</span>);</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> biasesInfo({outputChannels}, ArmnnBType, qScale * qScale, 0, <span class="keyword">true</span>);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  std::vector<float> inputData =</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  {</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f,</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f,</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f,</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f,</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f,</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f,</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  };</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  std::vector<float> weightsData =</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  {</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  1.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  1.0f, -1.0f, 1.0f,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  1.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  1.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  1.0f, 1.0f, 1.0f,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  2.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  2.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  2.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  2.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  2.0f, 2.0f, 2.0f,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  0.0f, -1.0f, 0.0f,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  0.0f, 1.0f, 0.0f,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  0.0f, 0.0f, 0.0f</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  };</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  std::vector<float> biasesData = { 0.0f, 2.0f, 1.0f, -1.0f };</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  std::vector<float> expectedOutputData =</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  {</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  3.0f, 3.0f, 3.0f, 3.0f, 3.0f, 3.0f, 3.0f, 3.0f, 3.0f, 3.0f, 3.0f, 3.0f, 3.0f, 3.0f,</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.5f, 5.5f, 5.5f, 5.5f, 5.5f, 5.5f, 5.5f,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  5.5f, 5.5f, 5.5f, 5.5f, 5.5f, 5.5f, 5.5f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f, 5.0f,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  2.5f, 2.5f, 2.5f, 2.5f, 2.5f, 2.5f, 2.5f, 3.5f, 3.5f, 3.5f, 3.5f, 3.5f, 3.5f, 3.5f,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  4.5f, 4.5f, 4.5f, 4.5f, 4.5f, 4.5f, 4.5f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f, 6.0f,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  1.0f, 3.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 2.0f, 4.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  2.0f, 4.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 2.0f, 4.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  2.0f, 4.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 2.0f, 4.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  2.0f, 4.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 3.0f, 5.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  3.0f, 5.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 3.0f, 5.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  3.0f, 5.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 3.0f, 5.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  };</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> </div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 0;</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 0;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 1;</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 0;</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 1;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</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="l00152"></a><span class="lineno"> 152</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = dataLayout;</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="comment">// Permute input and output if NCDHW.</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keywordflow">if</span> (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  {</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <a class="code" href="include_2armnn_test_utils_2_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(inputInfo, inputData);</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <a class="code" href="include_2armnn_test_utils_2_data_layout_utils_8hpp.xhtml#a1452f049aef30409b3b649af2be7ff82">PermuteTensorNhwcToNchw</a>(outputInfo, expectedOutputData);</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  }</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="comment">// Quantize data</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  std::vector<T> qInputData = armnnUtils::QuantizedVector<T>(inputData, qScale, qOffset);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  std::vector<T> qWeightsData = armnnUtils::QuantizedVector<T>(weightsData, qScale, qOffset);</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  std::vector<T> qExpectedOutputData = armnnUtils::QuantizedVector<T>(expectedOutputData, qScale, qOffset);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> </div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  std::vector<BT> qBiasesData = armnnUtils::QuantizedVector<BT>(biasesData, qScale * qScale, 0);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> weights(weightsInfo, qWeightsData);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> biases(biasesInfo, qBiasesData);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = CreateDepthwiseConvolution2dNetwork(descriptor,</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  inputInfo,</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  weightsInfo,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  biasesInfo,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  outputInfo,</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  weights,</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  biases);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network),</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  { { 0, qInputData } },</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  { { 0, qExpectedOutputData } },</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  backends);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> }</div><div class="ttc" id="include_2armnn_test_utils_2_data_layout_utils_8hpp_xhtml"><div class="ttname"><a href="include_2armnn_test_utils_2_data_layout_utils_8hpp.xhtml">DataLayoutUtils.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00066">INetwork.hpp:66</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_data_layout_utils_8hpp_xhtml_a1452f049aef30409b3b649af2be7ff82"><div class="ttname"><a href="include_2armnn_test_utils_2_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="include_2armnn_test_utils_2_data_layout_utils_8hpp_source.xhtml#l00026">DataLayoutUtils.hpp:26</a></div></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#l00673">Descriptors.hpp:673</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00062">Types.hpp:62</a></div></div> +<div class="ttc" id="_depthwise_convolution2d_end_to_end_tests_8hpp_xhtml_a0e45acb473ac9b518987058b0f6bfc86"><div class="ttname"><a href="_depthwise_convolution2d_end_to_end_tests_8hpp.xhtml#a0e45acb473ac9b518987058b0f6bfc86">DepthwiseConvolution2dEndToEnd</a></div><div class="ttdeci">void DepthwiseConvolution2dEndToEnd(const std::vector< armnn::BackendId > &backends, armnn::DataLayout dataLayout)</div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_end_to_end_tests_8hpp_source.xhtml#l00049">DepthwiseConvolution2dEndToEndTests.hpp:49</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#l00663">Descriptors.hpp:663</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#l00675">Descriptors.hpp:675</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="_quantize_helper_8hpp_xhtml"><div class="ttname"><a href="_quantize_helper_8hpp.xhtml">QuantizeHelper.hpp</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#l00657">Descriptors.hpp:657</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a0743ed5e860c316a20b68ca96301b411"><div class="ttname"><a href="namespacearmnn.xhtml#a0743ed5e860c316a20b68ca96301b411">armnn::ResolveType</a></div><div class="ttdeci">typename ResolveTypeImpl< DT >::Type ResolveType</div><div class="ttdef"><b>Definition:</b> <a href="_resolve_type_8hpp_source.xhtml#l00079">ResolveType.hpp:79</a></div></div> +<div class="ttc" id="_resolve_type_8hpp_xhtml"><div class="ttname"><a href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a></div></div> +<div class="ttc" id="_end_to_end_test_impl_8hpp_xhtml"><div class="ttname"><a href="_end_to_end_test_impl_8hpp.xhtml">EndToEndTestImpl.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.xhtml#l00006">01_00_quick_start.dox:6</a></div></div> +<div class="ttc" id="backends_2backends_common_2test_2_common_test_utils_8hpp_xhtml"><div class="ttname"><a href="backends_2backends_common_2test_2_common_test_utils_8hpp.xhtml">CommonTestUtils.hpp</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#l00665">Descriptors.hpp:665</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#l00661">Descriptors.hpp:661</a></div></div> +<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00327">Tensor.hpp:327</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#l00667">Descriptors.hpp:667</a></div></div> +<div class="ttc" id="_test_utils_8cpp_xhtml_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00014">TestUtils.cpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00241">INetwork.hpp:241</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_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00476">Network.cpp:476</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#l00624">Descriptors.hpp:624</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#l00659">Descriptors.hpp:659</a></div></div> +</div><!-- fragment --></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="_depthwise_convolution2d_end_to_end_tests_8hpp.xhtml">DepthwiseConvolution2dEndToEndTests.hpp</a></li> + <li class="footer">Generated on Fri Jun 17 2022 13:20:21 for ArmNN by + <a href="http://www.doxygen.org/index.html"> + <img class="footer" src="doxygen.png" alt="doxygen"/></a> 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