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| author | Nikhil Raj <nikhil.raj@arm.com> | 2022-08-19 15:23:36 +0100 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-08-19 15:23:36 +0100 |
| commit | 7bfd38a721360183f3392f9ab35db18a0dd7fef8 (patch) | |
| tree | 5b4da2f2e88636c939afbafa2571170297114e40 /22.08/_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp_source.xhtml | |
| parent | d5d43d82c0137e08553e44345c609cdd1a7931c7 (diff) | |
| download | armnn-7bfd38a721360183f3392f9ab35db18a0dd7fef8.tar.gz | |
Update Doxygen for 22.08 Release
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: I4789fe868e0492839be1482e5cee3642ed90d756
Diffstat (limited to '22.08/_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp_source.xhtml')
| -rw-r--r-- | 22.08/_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp_source.xhtml | 149 |
1 files changed, 149 insertions, 0 deletions
diff --git a/22.08/_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp_source.xhtml b/22.08/_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp_source.xhtml new file mode 100644 index 0000000000..1ce61a3b8e --- /dev/null +++ b/22.08/_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp_source.xhtml @@ -0,0 +1,149 @@ +<!-- 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/FuseConvertF32BF16IntoConstLayerTests.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"> + $(document).ready(initResizable); +</script> +<link href="search/search.css" rel="stylesheet" type="text/css"/> +<script type="text/javascript" src="search/searchdata.js"></script> +<script type="text/javascript" src="search/search.js"></script> +<script type="text/x-mathjax-config"> + MathJax.Hub.Config({ + extensions: ["tex2jax.js"], + jax: ["input/TeX","output/HTML-CSS"], +}); +</script><script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js"></script> +<link href="doxygen.css" rel="stylesheet" type="text/css" /> +<link href="stylesheet.css" rel="stylesheet" type="text/css"/> +</head> +<body> +<div id="top"><!-- do not remove this div, it is closed by doxygen! --> +<div id="titlearea"> +<table cellspacing="0" cellpadding="0"> + <tbody> + <tr style="height: 56px;"> + <img alt="ArmNN" src="Arm_NN_horizontal_blue.png" style="max-width: 10rem; margin-top: .5rem; margin-left 10px"/> + <td style="padding-left: 0.5em;"> + <div id="projectname"> +  <span id="projectnumber">22.08</span> + </div> + </td> + </tr> + </tbody> +</table> +</div> +<!-- end header part --> +<!-- Generated by Doxygen 1.8.13 --> +<script type="text/javascript"> +var searchBox = new SearchBox("searchBox", "search",false,'Search'); +</script> +<script type="text/javascript" src="menudata.js"></script> +<script type="text/javascript" src="menu.js"></script> +<script type="text/javascript"> +$(function() { + initMenu('',true,false,'search.php','Search'); + $(document).ready(function() { init_search(); }); +}); +</script> +<div id="main-nav"></div> +</div><!-- top --> +<div id="side-nav" class="ui-resizable side-nav-resizable"> + <div id="nav-tree"> + <div id="nav-tree-contents"> + <div id="nav-sync" class="sync"></div> + </div> + </div> + <div id="splitbar" style="-moz-user-select:none;" + class="ui-resizable-handle"> + </div> +</div> +<script type="text/javascript"> +$(document).ready(function(){initNavTree('_fuse_convert_f32_b_f16_into_const_layer_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">FuseConvertF32BF16IntoConstLayerTests.cpp</div> </div> +</div><!--header--> +<div class="contents"> +<a href="_fuse_convert_f32_b_f16_into_const_layer_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 © 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> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include <<a class="code" href="_layers_fwd_8hpp.xhtml">LayersFwd.hpp</a>></span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include <<a class="code" href="_network_8hpp.xhtml">Network.hpp</a>></span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_network_utils_8hpp.xhtml">NetworkUtils.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> <span class="preprocessor">#include <TestUtils.hpp></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="include_2armnn_2backends_2_tensor_handle_8hpp.xhtml">armnn/backends/TensorHandle.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <doctest/doctest.h></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div><div class="line"><a name="l00016"></a><span class="lineno"><a class="line" href="_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp.xhtml#a77a062dba8ec73047ae4e734519f5ef8"> 16</a></span> <a class="code" href="_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp.xhtml#a77a062dba8ec73047ae4e734519f5ef8">TEST_SUITE</a>(<span class="stringliteral">"Optimizer"</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">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn_1_1optimizations.xhtml">armnn::optimizations</a>;</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> TEST_CASE(<span class="stringliteral">"FuseConvertFp32Fp16intoConst"</span>)</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> {</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = {1, 2, 2, 3};</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </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_tensor_info.xhtml">TensorInfo</a> constTensorInfo(4, shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>, 1.0, 0, <span class="keyword">true</span>);</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_tensor_info.xhtml">TensorInfo</a> outputConvertInfo(4, shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>, 1.0, 0, <span class="keyword">true</span>);</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>  <a class="code" href="classarmnn_1_1_constant_layer.xhtml">ConstantLayer</a>* constantLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_constant_layer.xhtml">ConstantLayer</a>>(<span class="stringliteral">"constant"</span>);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  std::vector<float> constantValues(constTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(), 3.1416f);</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> constTensor(constTensorInfo, constantValues.data());</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  constantLayer-><a class="code" href="classarmnn_1_1_constant_layer.xhtml#ad0c4b8ee0efd8f9336571cbeab8a53fe">m_LayerOutput</a> = std::make_shared<ScopedTensorHandle>(constTensor);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  constantLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(constTensorInfo);</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <a class="code" href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">ConvertFp32ToBf16Layer</a>* convertLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">ConvertFp32ToBf16Layer</a>>(<span class="stringliteral">"convert"</span>);</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  convertLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputConvertInfo);</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="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>* output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="comment">// Connect up constant -> convert -> output</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  constantLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(convertLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  convertLayer-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(output-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keyword">auto</span> checkConstantFloat32 = [](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a> *<span class="keyword">const</span> layer) -> <span class="keywordtype">bool</span> {</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">return</span> IsLayerOfType<ConstantLayer>(layer) &&</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  (layer->GetDataType() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</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">auto</span> checkConstantBFloat16 = [](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a> *<span class="keyword">const</span> layer) -> <span class="keywordtype">bool</span> {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keywordflow">return</span> IsLayerOfType<ConstantLayer>(layer) &&</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  (layer->GetDataType() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>);</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> </div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  CHECK(<a class="code" href="est_utils_2_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>(),</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  checkConstantFloat32,</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  &IsLayerOfType<ConvertFp32ToBf16Layer>,</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  &IsLayerOfType<OutputLayer>));</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>  <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#a8fc3cdb7b4956182c23e8d217f961550">FuseConversionLayersIntoConstLayers</a>()));</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  CHECK(<a class="code" href="est_utils_2_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>(),</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  checkConstantBFloat16,</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> TEST_CASE(<span class="stringliteral">"RevertConstantWeightsToFP32"</span>)</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> {</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = {1, 2, 2, 3};</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> constTensorInfo(4, shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>, 1.0, 0, <span class="keyword">true</span>);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputConvertInfo(4, shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>, 1.0, 0, <span class="keyword">true</span>);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo(4, shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">auto</span>* input = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">InputLayer</a>>(0, <span class="stringliteral">"input0"</span>);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(inputInfo);</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>* constantLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_constant_layer.xhtml">ConstantLayer</a>>(<span class="stringliteral">"constant"</span>);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  std::vector<float> constantValues(constTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(), 3.1416f);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="classarmnn_1_1_const_tensor.xhtml">ConstTensor</a> constTensor(constTensorInfo, constantValues.data());</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  constantLayer->m_LayerOutput = std::make_shared<ScopedTensorHandle>(constTensor);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  constantLayer->GetOutputSlot().SetTensorInfo(constTensorInfo);</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>  <a class="code" href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">ConvertFp32ToBf16Layer</a>* convertLayerInputs = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">ConvertFp32ToBf16Layer</a>>(<span class="stringliteral">"convert"</span>);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  convertLayerInputs-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputConvertInfo);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <a class="code" href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">ConvertFp32ToBf16Layer</a>* convertLayerWeights = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">ConvertFp32ToBf16Layer</a>>(<span class="stringliteral">"convert2"</span>);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  convertLayerWeights-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputConvertInfo);</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <a class="code" href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">ConvertFp32ToBf16Layer</a>* convertLayerBiases = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">ConvertFp32ToBf16Layer</a>>(<span class="stringliteral">"convert3"</span>);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  convertLayerBiases-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(outputConvertInfo);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keyword">auto</span>* biases = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_constant_layer.xhtml">armnn::ConstantLayer</a>>(<span class="stringliteral">"Biases"</span>);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  biases-><a class="code" href="classarmnn_1_1_constant_layer.xhtml#ad0c4b8ee0efd8f9336571cbeab8a53fe">m_LayerOutput</a> = std::make_unique<armnn::ScopedTensorHandle>(constTensor);</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  biases->GetOutputSlot().SetTensorInfo(constTensorInfo);</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keyword">auto</span>* conv = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">armnn::Convolution2dLayer</a>>(descriptor, <span class="stringliteral">"conv2d"</span>);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> infoFP32({ 2, 3, 8, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  conv->GetOutputSlot().SetTensorInfo(infoFP32);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">auto</span>* output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> </div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="comment">// Connect up Input -> Convert -></span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="comment">// Constant -> Convert -> Conv2d -> Output</span></div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="comment">// Constant -> Convert -></span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  input-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(convertLayerInputs-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  constantLayer->GetOutputSlot().Connect(convertLayerWeights-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  biases->GetOutputSlot().Connect(convertLayerBiases-><a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0));</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  convertLayerInputs-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(conv->GetInputSlot(0));</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  convertLayerWeights-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(conv->GetInputSlot(1));</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  convertLayerBiases-><a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(conv->GetInputSlot(2));</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>  conv->GetOutputSlot().Connect(output->GetInputSlot(0));</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keyword">auto</span> checkConstantFloat32 = [](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a> *<span class="keyword">const</span> layer) -> <span class="keywordtype">bool</span> {</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  <span class="keywordflow">return</span> IsLayerOfType<ConstantLayer>(layer) &&</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  (layer->GetDataType() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</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>  <span class="keyword">auto</span> checkConstantBFloat16 = [](<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a> *<span class="keyword">const</span> layer) -> <span class="keywordtype">bool</span> {</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keywordflow">return</span> IsLayerOfType<ConstantLayer>(layer) &&</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  (layer->GetDataType() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  };</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  CHECK(<a class="code" href="est_utils_2_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>(),</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  checkConstantFloat32,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  checkConstantFloat32,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  &IsLayerOfType<ConvertFp32ToBf16Layer>,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  &IsLayerOfType<ConvertFp32ToBf16Layer>,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  &IsLayerOfType<ConvertFp32ToBf16Layer>,</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  &IsLayerOfType<Convolution2dLayer>,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</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#a8fc3cdb7b4956182c23e8d217f961550">FuseConversionLayersIntoConstLayers</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>  <span class="keywordtype">bool</span> revert = <a class="code" href="namespacearmnn.xhtml#a787197d592bc37e921d87b59d5b8afe9">RevertConstantWeightsToFP32</a>(conv);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> </div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="comment">// Erase unconnected layer as occurs during Topological Sort.</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a96d76fd10af39fbfabfd0caf0d1439fa">EraseLayer</a>(convertLayerInputs);</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  CHECK(revert);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  CHECK(constantLayer->GetDataType() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</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>  CHECK(<a class="code" href="est_utils_2_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>(),</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  &IsLayerOfType<InputLayer>,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  checkConstantBFloat16,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  checkConstantFloat32,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  &IsLayerOfType<Convolution2dLayer>,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  &IsLayerOfType<OutputLayer>));</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> }</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> }</div><div class="ttc" id="classarmnn_1_1_constant_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_constant_layer.xhtml">armnn::ConstantLayer</a></div><div class="ttdoc">A layer that the constant data can be bound to. </div><div class="ttdef"><b>Definition:</b> <a href="_constant_layer_8hpp_source.xhtml#l00015">ConstantLayer.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00543">Descriptors.hpp:543</a></div></div> +<div class="ttc" id="_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp_xhtml_a77a062dba8ec73047ae4e734519f5ef8"><div class="ttname"><a href="_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp.xhtml#a77a062dba8ec73047ae4e734519f5ef8">TEST_SUITE</a></div><div class="ttdeci">TEST_SUITE("Optimizer")</div><div class="ttdef"><b>Definition:</b> <a href="_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp_source.xhtml#l00016">FuseConvertF32BF16IntoConstLayerTests.cpp:16</a></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="est_utils_2_test_utils_8hpp_xhtml_a0eedb278f57355b47fa983450d4e378c"><div class="ttname"><a href="est_utils_2_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="est_utils_2_test_utils_8hpp_source.xhtml#l00021">TestUtils.hpp:21</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_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_broadcast_reshape_layer_8hpp_source.xhtml#l00015">AddBroadcastReshapeLayer.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_constant_layer_xhtml_ad0c4b8ee0efd8f9336571cbeab8a53fe"><div class="ttname"><a href="classarmnn_1_1_constant_layer.xhtml#ad0c4b8ee0efd8f9336571cbeab8a53fe">armnn::ConstantLayer::m_LayerOutput</a></div><div class="ttdeci">std::shared_ptr< ConstTensorHandle > m_LayerOutput</div><div class="ttdef"><b>Definition:</b> <a href="_constant_layer_8hpp_source.xhtml#l00044">ConstantLayer.hpp:44</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00456">Graph.hpp:456</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#l00179">Graph.hpp:179</a></div></div> +<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00495">Descriptors.hpp:495</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00112">Layer.cpp:112</a></div></div> +<div class="ttc" id="classarmnn_1_1_graph_xhtml_a96d76fd10af39fbfabfd0caf0d1439fa"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a96d76fd10af39fbfabfd0caf0d1439fa">armnn::Graph::EraseLayer</a></div><div class="ttdeci">void EraseLayer(Iterator pos)</div><div class="ttdoc">Deletes the layer at the specified position. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00504">Graph.hpp:504</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"><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="_optimizer_8hpp_xhtml"><div class="ttname"><a href="_optimizer_8hpp.xhtml">Optimizer.hpp</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot & GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00324">Layer.hpp:324</a></div></div> +<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.xhtml#l00013">OutputLayer.hpp:13</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="namespacearmnn_xhtml_a787197d592bc37e921d87b59d5b8afe9"><div class="ttname"><a href="namespacearmnn.xhtml#a787197d592bc37e921d87b59d5b8afe9">armnn::RevertConstantWeightsToFP32</a></div><div class="ttdeci">bool RevertConstantWeightsToFP32(Layer *layer)</div><div class="ttdef"><b>Definition:</b> <a href="_network_utils_8cpp_source.xhtml#l00277">NetworkUtils.cpp:277</a></div></div> +<div class="ttc" id="_network_utils_8hpp_xhtml"><div class="ttname"><a href="_network_utils_8hpp.xhtml">NetworkUtils.hpp</a></div></div> +<div class="ttc" id="include_2armnn_2backends_2_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="include_2armnn_2backends_2_tensor_handle_8hpp.xhtml">TensorHandle.hpp</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a></div></div> +<div class="ttc" id="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#l00030">Graph.hpp:30</a></div></div> +<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.xhtml#l00013">InputLayer.hpp:13</a></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="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00087">Layer.cpp:87</a></div></div> +<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot & GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00326">Layer.hpp:326</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="_layers_fwd_8hpp_xhtml"><div class="ttname"><a href="_layers_fwd_8hpp.xhtml">LayersFwd.hpp</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#l00181">Graph.hpp:181</a></div></div> +<div class="ttc" id="classarmnn_1_1_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml">armnn::Convolution2dLayer</a></div><div class="ttdoc">This layer represents a convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.xhtml#l00015">Convolution2dLayer.hpp:15</a></div></div> +<div class="ttc" id="classarmnn_1_1_convert_fp32_to_bf16_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_convert_fp32_to_bf16_layer.xhtml">armnn::ConvertFp32ToBf16Layer</a></div><div class="ttdoc">This layer converts data type Float32 to BFloat16. </div><div class="ttdef"><b>Definition:</b> <a href="_convert_fp32_to_bf16_layer_8hpp_source.xhtml#l00014">ConvertFp32ToBf16Layer.hpp:14</a></div></div> +<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_a8fc3cdb7b4956182c23e8d217f961550"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#a8fc3cdb7b4956182c23e8d217f961550">armnn::optimizations::FuseConversionLayersIntoConstLayers</a></div><div class="ttdeci">OptimizeForConnection< ConstantLayer, ConvertFp32ToBf16Layer, FuseConvertFp32ToBf16IntoConstLayers > FuseConversionLayersIntoConstLayers</div><div class="ttdef"><b>Definition:</b> <a href="_fuse_convert_fp32_to_bf16_into_const_layers_8hpp_source.xhtml#l00086">FuseConvertFp32ToBf16IntoConstLayers.hpp:86</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#l00217">Layer.hpp:217</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00196">Tensor.hpp:196</a></div></div> +</div><!-- fragment --></div><!-- 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="_fuse_convert_f32_b_f16_into_const_layer_tests_8cpp.xhtml">FuseConvertF32BF16IntoConstLayerTests.cpp</a></li> + <li class="footer">Generated on Fri Aug 19 2022 14:38:27 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> |