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diff --git a/20.02/_permute_and_batch_to_space_as_depth_to_space_tests_8cpp_source.xhtml b/20.02/_permute_and_batch_to_space_as_depth_to_space_tests_8cpp_source.xhtml new file mode 100644 index 0000000000..6b7d19f8e2 --- /dev/null +++ b/20.02/_permute_and_batch_to_space_as_depth_to_space_tests_8cpp_source.xhtml @@ -0,0 +1,155 @@ +<!-- 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/armnn/test/optimizations/PermuteAndBatchToSpaceAsDepthToSpaceTests.cpp 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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">20.02</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(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('_permute_and_batch_to_space_as_depth_to_space_tests_8cpp_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">PermuteAndBatchToSpaceAsDepthToSpaceTests.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_permute_and_batch_to_space_as_depth_to_space_tests_8cpp.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 © 2019 Arm Ltd. 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> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "../TestUtils.hpp"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_network_8hpp.xhtml">Network.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_optimizer_8hpp.xhtml">Optimizer.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</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> <a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(<a class="code" href="classarmnn_1_1_optimizer.xhtml">Optimizer</a>)</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn_1_1optimizations.xhtml">armnn::optimizations</a>;</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> <span class="comment"></span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment">/// Shared function for the below tests, so that we test the same network in both cases.</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"></span><a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> CreateTestNetwork()</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> {</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="comment">// Create a network</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a706f7345af3f18f4b16e226a672214c6">INetwork::Create</a>();</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keyword">auto</span> input = network->AddInputLayer(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo({ 1, 2, 3, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  input->GetOutputSlot(0).SetTensorInfo(inputInfo);</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>  <span class="comment">// Insert Permute which swaps batches and channels dimensions</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keyword">auto</span> permute = network->AddPermuteLayer(<a class="code" href="structarmnn_1_1_permute_descriptor.xhtml">PermuteDescriptor</a>(<a class="code" href="classarmnn_1_1_permutation_vector.xhtml">PermutationVector</a>{ 3, 1, 2, 0 }), <span class="stringliteral">"permute"</span>);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> permuteInfo({ 4, 2, 3, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  permute->GetOutputSlot(0).SetTensorInfo(permuteInfo);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  input->GetOutputSlot(0).Connect(permute->GetInputSlot(0));</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> </div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="comment">// Insert BatchToSpace</span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">BatchToSpaceNdDescriptor</a> batchToSpaceDesc;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  batchToSpaceDesc.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> = { 2, 2 };</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  batchToSpaceDesc.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keyword">auto</span> batchToSpace = network->AddBatchToSpaceNdLayer(batchToSpaceDesc, <span class="stringliteral">"batchToSpace"</span>);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> batchToSpaceInfo({ 1, 4, 6, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  batchToSpace->GetOutputSlot(0).SetTensorInfo(batchToSpaceInfo);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  permute->GetOutputSlot(0).Connect(batchToSpace->GetInputSlot(0));</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="keyword">auto</span> output = network->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  batchToSpace->GetOutputSlot(0).Connect(output->GetInputSlot(0));</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keywordflow">return</span> network;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> }</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"></span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment">/// Shared function for the below tests, so that we test the same network in both cases.</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"></span><a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> CreateTransposeTestNetwork()</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> {</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="comment">// Create a network</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a706f7345af3f18f4b16e226a672214c6">INetwork::Create</a>();</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">auto</span> input = network->AddInputLayer(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo({ 1, 2, 3, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  input->GetOutputSlot(0).SetTensorInfo(inputInfo);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// Insert Permute which swaps batches and channels dimensions</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">auto</span> permute = network->AddTransposeLayer(<a class="code" href="structarmnn_1_1_transpose_descriptor.xhtml">TransposeDescriptor</a>(<a class="code" href="classarmnn_1_1_permutation_vector.xhtml">PermutationVector</a>{ 3, 1, 2, 0 }), <span class="stringliteral">"permute"</span>);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> permuteInfo({ 4, 2, 3, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  permute->GetOutputSlot(0).SetTensorInfo(permuteInfo);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  input->GetOutputSlot(0).Connect(permute->GetInputSlot(0));</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="comment">// Insert BatchToSpace</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">BatchToSpaceNdDescriptor</a> batchToSpaceDesc;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  batchToSpaceDesc.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> = { 2, 2 };</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  batchToSpaceDesc.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">auto</span> batchToSpace = network->AddBatchToSpaceNdLayer(batchToSpaceDesc, <span class="stringliteral">"batchToSpace"</span>);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> batchToSpaceInfo({ 1, 4, 6, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  batchToSpace->GetOutputSlot(0).SetTensorInfo(batchToSpaceInfo);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  permute->GetOutputSlot(0).Connect(batchToSpace->GetInputSlot(0));</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">auto</span> output = network->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  batchToSpace->GetOutputSlot(0).Connect(output->GetInputSlot(0));</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordflow">return</span> network;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> }</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> } <span class="comment">// namespace</span></div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="comment"></span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="comment">/// Tests that the optimization performed by PermuteAndBatchToSpaceAsDepthToSpace is as expected.</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="comment">/// Note this does not ensure the correctness of the optimization - that is done in the below test.</span></div><div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="_permute_and_batch_to_space_as_depth_to_space_tests_8cpp.xhtml#ac9ae3545393ad3f2dac5c8f789bbbfbf"> 87</a></span> <span class="comment"></span><a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(PermuteAndBatchToSpaceAsDepthToSpaceOptimizerTest)</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> {</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = CreateTestNetwork();</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph = <span class="keyword">static_cast<</span><a class="code" href="classarmnn_1_1_network.xhtml">Network</a>*<span class="keyword">></span>(network.get())->GetGraph();</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="comment">// Confirm initial graph is as we expect</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(), &IsLayerOfType<InputLayer>, &IsLayerOfType<PermuteLayer>,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  &IsLayerOfType<BatchToSpaceNdLayer>, &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="comment">// Perform the optimization which should merge the two layers into a DepthToSpace</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a17d1279f5f8e3b92c328b1ed3b6fd549">PermuteAndBatchToSpaceAsDepthToSpace</a>()));</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>  <span class="comment">// Check that the replacement has been made as expected</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">auto</span> checkDepthToSpace = [](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> layer) -> <span class="keywordtype">bool</span> {</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">return</span> IsLayerOfType<DepthToSpaceLayer>(layer) &&</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  static_cast<const DepthToSpaceLayer*>(layer)->GetParameters().m_BlockSize == 2 &&</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keyword">static_cast<</span><span class="keyword">const </span><a class="code" href="classarmnn_1_1_depth_to_space_layer.xhtml">DepthToSpaceLayer</a>*<span class="keyword">></span>(layer)->GetParameters().m_DataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a> &&</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  layer->GetOutputHandler().GetTensorInfo() == <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 4, 6, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  };</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>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(), &IsLayerOfType<InputLayer>, checkDepthToSpace,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// Check the new layer has the two merged layers listed as related layers</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  std::list<std::string> testRelatedLayers = { <span class="stringliteral">"batchToSpace"</span>, <span class="stringliteral">"permute"</span> };</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  BOOST_TEST(CheckRelatedLayers<DepthToSpaceLayer>(graph, testRelatedLayers));</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> }</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="comment"></span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment">/// Tests that the optimization performed by PermuteAndBatchToSpaceAsDepthToSpace is as expected.</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="comment">/// Note this does not ensure the correctness of the optimization - that is done in the below test.</span></div><div class="line"><a name="l00117"></a><span class="lineno"><a class="line" href="_permute_and_batch_to_space_as_depth_to_space_tests_8cpp.xhtml#ad5937fc491fa54298cbd8fa7d599993f"> 117</a></span> <span class="comment"></span><a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(TransposeAndBatchToSpaceAsDepthToSpaceOptimizerTest)</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>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = CreateTransposeTestNetwork();</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph = <span class="keyword">static_cast<</span><a class="code" href="classarmnn_1_1_network.xhtml">Network</a>*<span class="keyword">></span>(network.get())->GetGraph();</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="comment">// Confirm initial graph is as we expect</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(), &IsLayerOfType<InputLayer>, &IsLayerOfType<TransposeLayer>,</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  &IsLayerOfType<BatchToSpaceNdLayer>, &IsLayerOfType<OutputLayer>));</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>  <span class="comment">// Perform the optimization which should merge the two layers into a DepthToSpace</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#a98f54d4391347d517c7a7869e7707203">TransposeAndBatchToSpaceAsDepthToSpace</a>()));</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> </div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="comment">// Check that the replacement has been made as expected</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="keyword">auto</span> checkDepthToSpace = [](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>* <span class="keyword">const</span> layer) -> <span class="keywordtype">bool</span> {</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordflow">return</span> IsLayerOfType<DepthToSpaceLayer>(layer) &&</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  static_cast<const DepthToSpaceLayer*>(layer)->GetParameters().m_BlockSize == 2 &&</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keyword">static_cast<</span><span class="keyword">const </span><a class="code" href="classarmnn_1_1_depth_to_space_layer.xhtml">DepthToSpaceLayer</a>*<span class="keyword">></span>(layer)->GetParameters().m_DataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a> &&</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  layer->GetOutputHandler().GetTensorInfo() == <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 4, 6, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  };</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">cbegin</a>(), graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">cend</a>(), &IsLayerOfType<InputLayer>, checkDepthToSpace,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="comment">// Check the new layer has the two merged layers listed as related layers</span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  std::list<std::string> testRelatedLayers = { <span class="stringliteral">"batchToSpace"</span>, <span class="stringliteral">"permute"</span> };</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  BOOST_TEST(CheckRelatedLayers<DepthToSpaceLayer>(graph, testRelatedLayers));</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> </div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="comment">// This unit test needs the reference backend, it's not available if the reference backend is not built</span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="preprocessor">#if defined(ARMNNREF_ENABLED)</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="comment"></span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="comment">/// Tests that a optimization performed by PermuteAndBatchToSpaceAsDepthToSpace does not change the behaviour</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="comment">/// of the network (i.e. it still produces the correct output).</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> <span class="comment"></span><a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(PermuteAndBatchToSpaceAsDepthToSpaceCorrectnessTest)</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> {</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = CreateTestNetwork();</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>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">IRuntimePtr</a> runtime = <a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(<a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a>());</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optimizedNetwork = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*network, { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">Compute::CpuRef</a> }, runtime->GetDeviceSpec());</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>  <span class="comment">// Confirm that the optimization has actually taken place</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& optGraph = <span class="keyword">static_cast<</span><a class="code" href="classarmnn_1_1_optimized_network.xhtml">OptimizedNetwork</a>*<span class="keyword">></span>(optimizedNetwork.get())->GetGraph();</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(optGraph.cbegin(), optGraph.cend(), &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  &IsLayerOfType<DepthToSpaceLayer>, &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> </div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="comment">// Load the graph into a runtime so we can check it produces the correct output</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  runtime->LoadNetwork(netId, std::move(optimizedNetwork));</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<float> inputData{</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="comment">// Each row here is a row of pixels where each pixel has 4 channels</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="comment">// clang-format off</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  1.0f, 2.0f, 3.0f, 4.0f, 10.0f, 20.0f, 30.0f, 40.0f, 100.0f, 200.0f, 300.0f, 400.0f,</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  -1.0f, -2.0f, -3.0f, -4.0f, -10.0f, -20.0f, -30.0f, -40.0f, -100.0f, -200.0f, -300.0f, -400.0f,</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="comment">// clang-format on</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  };</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> input(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 3, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), inputData);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputs = { { 0, input } };</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  std::vector<float> outputData(4 * 6);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <a class="code" href="classarmnn_1_1_tensor.xhtml">Tensor</a> output(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 4, 6, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), outputData.data());</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputs = { { 0, output } };</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  runtime->EnqueueWorkload(netId, inputs, outputs);</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="comment">// Check the output is as expected.</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="comment">// Note this output has been generated by running the network *without* the optimization.</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  std::vector<float> expectedOutput = {</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="comment">// Rows and columns here match exactly with the tensor, as there is only 1 channel.</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="comment">// clang-format off</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  1.0f, 2.0f, 10.0f, 20.0f, 100.0f, 200.0f,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  3.0f, 4.0f, 30.0f, 40.0f, 300.0f, 400.0f,</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  -1.0f, -2.0f, -10.0f, -20.0f, -100.0f, -200.0f,</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  -3.0f, -4.0f, -30.0f, -40.0f, -300.0f, -400.0f,</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="comment">// clang-format on</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  };</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  BOOST_TEST(outputData == expectedOutput);</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> }</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> <span class="comment"></span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> <span class="comment">/// Tests that a optimization performed by PermuteAndBatchToSpaceAsDepthToSpace does not change the behaviour</span></div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> <span class="comment">/// of the network (i.e. it still produces the correct output).</span></div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> <span class="comment"></span><a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(TransposeAndBatchToSpaceAsDepthToSpaceCorrectnessTest)</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> {</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> network = CreateTransposeTestNetwork();</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <a class="code" href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">IRuntimePtr</a> runtime = <a class="code" href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(<a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">IRuntime::CreationOptions</a>());</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <a class="code" href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optimizedNetwork = <a class="code" href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*network, { <a class="code" href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">Compute::CpuRef</a> }, runtime->GetDeviceSpec());</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span> </div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="comment">// Confirm that the optimization has actually taken place</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>& optGraph = <span class="keyword">static_cast<</span><a class="code" href="classarmnn_1_1_optimized_network.xhtml">OptimizedNetwork</a>*<span class="keyword">></span>(optimizedNetwork.get())->GetGraph();</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  BOOST_TEST(<a class="code" href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a>(optGraph.cbegin(), optGraph.cend(), &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  &IsLayerOfType<DepthToSpaceLayer>, &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> </div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="comment">// Load the graph into a runtime so we can check it produces the correct output</span></div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <a class="code" href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  runtime->LoadNetwork(netId, std::move(optimizedNetwork));</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  std::vector<float> inputData{</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="comment">// Each row here is a row of pixels where each pixel has 4 channels</span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <span class="comment">// clang-format off</span></div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  1.0f, 2.0f, 3.0f, 4.0f, 10.0f, 20.0f, 30.0f, 40.0f, 100.0f, 200.0f, 300.0f, 400.0f,</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  -1.0f, -2.0f, -3.0f, -4.0f, -10.0f, -20.0f, -30.0f, -40.0f, -100.0f, -200.0f, -300.0f, -400.0f,</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="comment">// clang-format on</span></div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  };</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> input(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 3, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), inputData);</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <a class="code" href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">InputTensors</a> inputs = { { 0, input } };</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  std::vector<float> outputData(4 * 6);</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="classarmnn_1_1_tensor.xhtml">Tensor</a> output(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 4, 6, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>), outputData.data());</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <a class="code" href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputs = { { 0, output } };</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  runtime->EnqueueWorkload(netId, inputs, outputs);</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="comment">// Check the output is as expected.</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="comment">// Note this output has been generated by running the network *without* the optimization.</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  std::vector<float> expectedOutput = {</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="comment">// Rows and columns here match exactly with the tensor, as there is only 1 channel.</span></div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="comment">// clang-format off</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  1.0f, 2.0f, 10.0f, 20.0f, 100.0f, 200.0f,</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  3.0f, 4.0f, 30.0f, 40.0f, 300.0f, 400.0f,</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> </div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  -1.0f, -2.0f, -10.0f, -20.0f, -100.0f, -200.0f,</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  -3.0f, -4.0f, -30.0f, -40.0f, -300.0f, -400.0f,</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="comment">// clang-format on</span></div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  };</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  BOOST_TEST(outputData == expectedOutput);</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> }</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> </div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> <a class="code" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="ttc" id="_output_shape_of_squeeze_8cpp_xhtml_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div> +<div class="ttc" id="classarmnn_1_1_i_runtime_xhtml_ad44ecd3700748dc30dc4bbe34ba5bde7"><div class="ttname"><a href="classarmnn_1_1_i_runtime.xhtml#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a></div><div class="ttdeci">static IRuntimePtr Create(const CreationOptions &options)</div><div class="ttdef"><b>Definition:</b> <a href="_runtime_8cpp_source.xhtml#l00032">Runtime.cpp:32</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64"><div class="ttname"><a href="namespacearmnn.xhtml#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a></div><div class="ttdoc">CPU Execution: Reference C++ kernels. </div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa7427025a851113a492de0b68b23d22a"><div class="ttname"><a href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a></div><div class="ttdeci">Optimizer::Optimizations MakeOptimizations(Args &&... args)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8hpp_source.xhtml#l00043">Optimizer.hpp:43</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a98f54d4391347d517c7a7869e7707203"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a98f54d4391347d517c7a7869e7707203">armnn::optimizations::TransposeAndBatchToSpaceAsDepthToSpace</a></div><div class="ttdeci">OptimizeForConnection< TransposeLayer, BatchToSpaceNdLayer, PermuteAndBatchToSpaceAsDepthToSpaceImpl< TransposeLayer > > TransposeAndBatchToSpaceAsDepthToSpace</div><div class="ttdef"><b>Definition:</b> <a href="_permute_and_batch_to_space_as_depth_to_space_8hpp_source.xhtml#l00105">PermuteAndBatchToSpaceAsDepthToSpace.hpp:105</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#l00053">Tensor.hpp:53</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml">armnn::optimizations</a></div><div class="ttdef"><b>Definition:</b> <a href="_add_debug_8hpp_source.xhtml#l00012">AddDebug.hpp:12</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a98b1109a9006f8cc7d4566146a3bd737"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a98b1109a9006f8cc7d4566146a3bd737">armnn::Graph::cbegin</a></div><div class="ttdeci">ConstIterator cbegin() const</div><div class="ttdoc">Returns const iterator pointing to the beginning of the list. Lowercase for range-based for loops...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00168">Graph.hpp:168</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimizer_xhtml_a1f48ba622b76ea04d15c9b62f642bf08"><div class="ttname"><a href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a></div><div class="ttdeci">static void Pass(Graph &graph, const Optimizations &optimizations)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8cpp_source.xhtml#l00016">Optimizer.cpp:16</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.xhtml#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr< IRuntime, void(*)(IRuntime *runtime)> IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00024">IRuntime.hpp:24</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::BatchToSpaceNdDescriptor::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#l00684">Descriptors.hpp:684</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_aa01bce88f89975a5a031db4cc8861527"><div class="ttname"><a href="namespacearmnn.xhtml#aa01bce88f89975a5a031db4cc8861527">armnn::InputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class ConstTensor > > InputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00225">Tensor.hpp:225</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a83015160d8c67d5d77735eb0d4033d9a"><div class="ttname"><a href="namespacearmnn.xhtml#a83015160d8c67d5d77735eb0d4033d9a">armnn::NetworkId</a></div><div class="ttdeci">int NetworkId</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00019">IRuntime.hpp:19</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_batch_to_space_nd_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">armnn::BatchToSpaceNdDescriptor</a></div><div class="ttdoc">A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00657">Descriptors.hpp:657</a></div></div> +<div class="ttc" id="_optimizer_8hpp_xhtml"><div class="ttname"><a href="_optimizer_8hpp.xhtml">Optimizer.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor.xhtml">armnn::Tensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and a mutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00191">Tensor.hpp:191</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a17d1279f5f8e3b92c328b1ed3b6fd549"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a17d1279f5f8e3b92c328b1ed3b6fd549">armnn::optimizations::PermuteAndBatchToSpaceAsDepthToSpace</a></div><div class="ttdeci">OptimizeForConnection< PermuteLayer, BatchToSpaceNdLayer, PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteLayer > > PermuteAndBatchToSpaceAsDepthToSpace</div><div class="ttdef"><b>Definition:</b> <a href="_permute_and_batch_to_space_as_depth_to_space_8hpp_source.xhtml#l00103">PermuteAndBatchToSpaceAsDepthToSpace.hpp:103</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.xhtml#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> messages=EmptyOptional())</div><div class="ttdoc">Create an optimized version of the network. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00890">Network.cpp:890</a></div></div> +<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a02e143524aefddd40b485fcf7dea6696"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">armnn::BatchToSpaceNdDescriptor::m_BlockShape</a></div><div class="ttdeci">std::vector< unsigned int > m_BlockShape</div><div class="ttdoc">Block shape values. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00680">Descriptors.hpp:680</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#l00199">Tensor.hpp:199</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a8f091a512915d1cb29a4ebf13dfc53ea"><div class="ttname"><a href="namespacearmnn.xhtml#a8f091a512915d1cb29a4ebf13dfc53ea">armnn::OutputTensors</a></div><div class="ttdeci">std::vector< std::pair< LayerBindingId, class Tensor > > OutputTensors</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00226">Tensor.hpp:226</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.xhtml#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00566">INetwork.hpp:566</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a10d15f3df1ab52b3b915a4be1dbf386b"><div class="ttname"><a href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">armnn::BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00170">ConstTensorLayerVisitor.cpp:170</a></div></div> +<div class="ttc" id="classarmnn_1_1_permutation_vector_xhtml"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00173">Types.hpp:173</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div> +<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.xhtml">armnn::IRuntime::CreationOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.xhtml#l00041">IRuntime.hpp:41</a></div></div> +<div class="ttc" id="classarmnn_1_1_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_network.xhtml">armnn::Network</a></div><div class="ttdoc">Private implementation of INetwork. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00028">Network.hpp:28</a></div></div> +<div class="ttc" id="_profiler_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div> +<div class="ttc" id="_network_8hpp_xhtml"><div class="ttname"><a href="_network_8hpp.xhtml">Network.hpp</a></div></div> +<div class="ttc" id="_test_utils_8hpp_xhtml_a0eedb278f57355b47fa983450d4e378c"><div class="ttname"><a href="_test_utils_8hpp.xhtml#a0eedb278f57355b47fa983450d4e378c">CheckSequence</a></div><div class="ttdeci">bool CheckSequence(const armnn::Graph::ConstIterator first, const armnn::Graph::ConstIterator last)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8hpp_source.xhtml#l00020">TestUtils.hpp:20</a></div></div> +<div class="ttc" id="structarmnn_1_1_transpose_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_descriptor.xhtml">armnn::TransposeDescriptor</a></div><div class="ttdoc">A TransposeDescriptor for the TransposeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01123">Descriptors.hpp:1123</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="classarmnn_1_1_graph_xhtml_a02fd29b6dc3e21fbe4484362d85893bc"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a02fd29b6dc3e21fbe4484362d85893bc">armnn::Graph::cend</a></div><div class="ttdeci">ConstIterator cend() const</div><div class="ttdoc">Returns const iterator pointing to the end of the list. Lowercase for range-based for loops...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00170">Graph.hpp:170</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#l00101">INetwork.hpp:101</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a706f7345af3f18f4b16e226a672214c6"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a706f7345af3f18f4b16e226a672214c6">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00049">Network.cpp:49</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimizer_xhtml"><div class="ttname"><a href="classarmnn_1_1_optimizer.xhtml">armnn::Optimizer</a></div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8hpp_source.xhtml#l00014">Optimizer.hpp:14</a></div></div> +<div class="ttc" id="classarmnn_1_1_depth_to_space_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_depth_to_space_layer.xhtml">armnn::DepthToSpaceLayer</a></div><div class="ttdoc">This layer represents a DepthToSpace operation. </div><div class="ttdef"><b>Definition:</b> <a href="_depth_to_space_layer_8hpp_source.xhtml#l00014">DepthToSpaceLayer.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> +<div class="ttc" id="structarmnn_1_1_permute_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_permute_descriptor.xhtml">armnn::PermuteDescriptor</a></div><div class="ttdoc">A PermuteDescriptor for the PermuteLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00102">Descriptors.hpp:102</a></div></div> +<div class="ttc" id="classarmnn_1_1_optimized_network_xhtml"><div class="ttname"><a href="classarmnn_1_1_optimized_network.xhtml">armnn::OptimizedNetwork</a></div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.xhtml#l00265">Network.hpp:265</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_e0a84d05c80a2ef4231141dcbbeac5c8.xhtml">armnn</a></li><li class="navelem"><a class="el" href="dir_9d86fd1fbecbedf5bdb69c7e7235fe5f.xhtml">test</a></li><li class="navelem"><a class="el" href="dir_f1cd0e6da811a659c139424442adfb5f.xhtml">optimizations</a></li><li class="navelem"><a class="el" href="_permute_and_batch_to_space_as_depth_to_space_tests_8cpp.xhtml">PermuteAndBatchToSpaceAsDepthToSpaceTests.cpp</a></li> + <li class="footer">Generated on Fri Mar 13 2020 16:09:08 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> |