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review.mlplatform.org / ml / armnn / 3184c907b2420e6c66485529f336251b2b62aecf / . / Documentation / classarmnn_1_1optimizations_1_1_fold_pad_into_convolution2d_impl.xhtml
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102<div class="title">FoldPadIntoConvolution2dImpl Class Reference</div> </div>
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105
106<p><code>#include &lt;<a class="el" href="_fold_pad_into_convolution2d_8hpp_source.xhtml">FoldPadIntoConvolution2d.hpp</a>&gt;</code></p>
107<table class="memberdecls">
108<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
109Public Member Functions</h2></td></tr>
110<tr class="memitem:a5a8476ffc04ce7460bb09ad50d1d23de"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1optimizations_1_1_fold_pad_into_convolution2d_impl.xhtml#a5a8476ffc04ce7460bb09ad50d1d23de">Run</a> (<a class="el" href="classarmnn_1_1_graph.xhtml">Graph</a> &amp;graph, <a class="el" href="classarmnn_1_1_input_slot.xhtml">InputSlot</a> &amp;connection) const</td></tr>
111<tr class="separator:a5a8476ffc04ce7460bb09ad50d1d23de"><td class="memSeparator" colspan="2">&#160;</td></tr>
112</table><table class="memberdecls">
113<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
114Protected Member Functions</h2></td></tr>
115<tr class="memitem:a008dac8de51c0f701621e64c91c6b9f8"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1optimizations_1_1_fold_pad_into_convolution2d_impl.xhtml#a008dac8de51c0f701621e64c91c6b9f8">FoldPadIntoConvolution2dImpl</a> ()=default</td></tr>
116<tr class="separator:a008dac8de51c0f701621e64c91c6b9f8"><td class="memSeparator" colspan="2">&#160;</td></tr>
117<tr class="memitem:ab52c3ac73b3b657ccc44ac92d2ce88f1"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1optimizations_1_1_fold_pad_into_convolution2d_impl.xhtml#ab52c3ac73b3b657ccc44ac92d2ce88f1">~FoldPadIntoConvolution2dImpl</a> ()=default</td></tr>
118<tr class="separator:ab52c3ac73b3b657ccc44ac92d2ce88f1"><td class="memSeparator" colspan="2">&#160;</td></tr>
119</table>
120<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
121<div class="textblock">
122<p class="definition">Definition at line <a class="el" href="_fold_pad_into_convolution2d_8hpp_source.xhtml#l00015">15</a> of file <a class="el" href="_fold_pad_into_convolution2d_8hpp_source.xhtml">FoldPadIntoConvolution2d.hpp</a>.</p>
123</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
124<a id="a008dac8de51c0f701621e64c91c6b9f8"></a>
125<h2 class="memtitle"><span class="permalink"><a href="#a008dac8de51c0f701621e64c91c6b9f8">&#9670;&nbsp;</a></span>FoldPadIntoConvolution2dImpl()</h2>
126
127<div class="memitem">
128<div class="memproto">
129<table class="mlabels">
130 <tr>
131 <td class="mlabels-left">
132 <table class="memname">
133 <tr>
134 <td class="memname"><a class="el" href="classarmnn_1_1optimizations_1_1_fold_pad_into_convolution2d_impl.xhtml">FoldPadIntoConvolution2dImpl</a> </td>
135 <td>(</td>
136 <td class="paramname"></td><td>)</td>
137 <td></td>
138 </tr>
139 </table>
140 </td>
141 <td class="mlabels-right">
142<span class="mlabels"><span class="mlabel">protected</span><span class="mlabel">default</span></span> </td>
143 </tr>
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146
147<p class="reference">Referenced by <a class="el" href="_fold_pad_into_convolution2d_8hpp_source.xhtml#l00019">FoldPadIntoConvolution2dImpl::Run()</a>.</p>
148
149</div>
150</div>
151<a id="ab52c3ac73b3b657ccc44ac92d2ce88f1"></a>
152<h2 class="memtitle"><span class="permalink"><a href="#ab52c3ac73b3b657ccc44ac92d2ce88f1">&#9670;&nbsp;</a></span>~FoldPadIntoConvolution2dImpl()</h2>
153
154<div class="memitem">
155<div class="memproto">
156<table class="mlabels">
157 <tr>
158 <td class="mlabels-left">
159 <table class="memname">
160 <tr>
161 <td class="memname">~<a class="el" href="classarmnn_1_1optimizations_1_1_fold_pad_into_convolution2d_impl.xhtml">FoldPadIntoConvolution2dImpl</a> </td>
162 <td>(</td>
163 <td class="paramname"></td><td>)</td>
164 <td></td>
165 </tr>
166 </table>
167 </td>
168 <td class="mlabels-right">
169<span class="mlabels"><span class="mlabel">protected</span><span class="mlabel">default</span></span> </td>
170 </tr>
171</table>
172</div><div class="memdoc">
173
174<p class="reference">Referenced by <a class="el" href="_fold_pad_into_convolution2d_8hpp_source.xhtml#l00019">FoldPadIntoConvolution2dImpl::Run()</a>.</p>
175
176</div>
177</div>
178<h2 class="groupheader">Member Function Documentation</h2>
179<a id="a5a8476ffc04ce7460bb09ad50d1d23de"></a>
180<h2 class="memtitle"><span class="permalink"><a href="#a5a8476ffc04ce7460bb09ad50d1d23de">&#9670;&nbsp;</a></span>Run()</h2>
181
182<div class="memitem">
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185 <tr>
186 <td class="mlabels-left">
187 <table class="memname">
188 <tr>
189 <td class="memname">void Run </td>
190 <td>(</td>
191 <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.xhtml">Graph</a> &amp;&#160;</td>
192 <td class="paramname"><em>graph</em>, </td>
193 </tr>
194 <tr>
195 <td class="paramkey"></td>
196 <td></td>
197 <td class="paramtype"><a class="el" href="classarmnn_1_1_input_slot.xhtml">InputSlot</a> &amp;&#160;</td>
198 <td class="paramname"><em>connection</em>&#160;</td>
199 </tr>
200 <tr>
201 <td></td>
202 <td>)</td>
203 <td></td><td> const</td>
204 </tr>
205 </table>
206 </td>
207 <td class="mlabels-right">
208<span class="mlabels"><span class="mlabel">inline</span></span> </td>
209 </tr>
210</table>
211</div><div class="memdoc">
212
213<p class="definition">Definition at line <a class="el" href="_fold_pad_into_convolution2d_8hpp_source.xhtml#l00019">19</a> of file <a class="el" href="_fold_pad_into_convolution2d_8hpp_source.xhtml">FoldPadIntoConvolution2d.hpp</a>.</p>
214
215<p class="reference">References <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">armnn::Convolution2d</a>, <a class="el" href="classarmnn_1_1optimizations_1_1_fold_pad_into_convolution2d_impl.xhtml#a008dac8de51c0f701621e64c91c6b9f8">FoldPadIntoConvolution2dImpl::FoldPadIntoConvolution2dImpl()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00055">InputSlot::GetConnectedOutputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00310">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00305">Layer::GetName()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00221">Layer::GetOutputHandler()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00312">Layer::GetOutputSlot()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00052">InputSlot::GetOwningLayer()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00115">OutputSlot::GetOwningLayer()</a>, <a class="el" href="_output_handler_8hpp_source.xhtml#l00044">OutputHandler::GetTensorInfo()</a>, <a class="el" href="_layer_8hpp_source.xhtml#l00259">Layer::GetType()</a>, <a class="el" href="_graph_8hpp_source.xhtml#l00409">Graph::InsertNewLayer()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00438">Convolution2dDescriptor::m_BiasEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00440">Convolution2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00428">Convolution2dDescriptor::m_PadBottom</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00422">Convolution2dDescriptor::m_PadLeft</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00424">Convolution2dDescriptor::m_PadRight</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l00426">Convolution2dDescriptor::m_PadTop</a>, <a class="el" href="_layer_8cpp_source.xhtml#l00112">OutputSlot::MoveAllConnections()</a>, <a class="el" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>, <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ade43468adaf6acb2c38ebc0c1176f82f">armnn::Pad</a>, <a class="el" href="_output_handler_8cpp_source.xhtml#l00017">OutputHandler::SetTensorInfo()</a>, and <a class="el" href="classarmnn_1_1optimizations_1_1_fold_pad_into_convolution2d_impl.xhtml#ab52c3ac73b3b657ccc44ac92d2ce88f1">FoldPadIntoConvolution2dImpl::~FoldPadIntoConvolution2dImpl()</a>.</p>
216<div class="fragment"><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; {</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; Layer&amp; base = connection.GetConnectedOutputSlot()-&gt;GetOwningLayer();</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; Layer&amp; child = connection.GetOwningLayer();</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; BOOST_ASSERT(base.GetType() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ade43468adaf6acb2c38ebc0c1176f82f">LayerType::Pad</a>);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; BOOST_ASSERT(child.GetType() == <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">LayerType::Convolution2d</a>);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; PadLayer* padLayer = boost::polymorphic_downcast&lt;PadLayer*&gt;(&amp;base);</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; Convolution2dLayer* convolution2dLayer = boost::polymorphic_downcast&lt;Convolution2dLayer*&gt;(&amp;child);</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; OutputSlot* parentOut = base.GetInputSlot(0).GetConnectedOutputSlot();</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keyword">const</span> TensorInfo&amp; outInfo = child.GetOutputHandler().GetTensorInfo();</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keyword">const</span> std::string name = std::string(<span class="stringliteral">&quot;folded-&quot;</span>) + base.GetName() + std::string(<span class="stringliteral">&quot;-into-&quot;</span>) + child.GetName();</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; Convolution2dDescriptor descriptor = convolution2dLayer-&gt;GetParameters();</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; <span class="keyword">auto</span> padList = padLayer-&gt;GetParameters().m_PadList;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a> dataLayout = descriptor.m_DataLayout;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="comment">// In Convolution2dDescriptor, padLeft and padRight are defined as paddings on width dimension</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="comment">// whereas padTop and padBottom - paddings on height dimension, so setting these according to data layout</span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="keywordflow">if</span>(dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>)</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; {</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; descriptor.m_PadLeft = padList[2].first;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; descriptor.m_PadRight = padList[2].second;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; descriptor.m_PadTop = padList[1].first;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; descriptor.m_PadBottom = padList[1].second;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; }</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; descriptor.m_PadLeft = padList[3].first;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; descriptor.m_PadRight = padList[3].second;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; descriptor.m_PadTop = padList[2].first;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; descriptor.m_PadBottom = padList[2].second;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; }</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="keyword">auto</span>&amp; newConv2dLayer = *graph.InsertNewLayer&lt;Convolution2dLayer&gt;(base.GetInputSlot(0),</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; descriptor,</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; name.c_str());</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; newConv2dLayer.GetOutputHandler().SetTensorInfo(outInfo);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="comment">// Copy weights and bias to the new convolution layer</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; BOOST_ASSERT_MSG(convolution2dLayer-&gt;m_Weight != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="stringliteral">&quot;FoldPadIntoConvolution2d: Weights data should not be null.&quot;</span>);</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; newConv2dLayer.m_Weight = std::move(convolution2dLayer-&gt;m_Weight);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="keywordflow">if</span> (descriptor.m_BiasEnabled)</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; {</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; BOOST_ASSERT_MSG(convolution2dLayer-&gt;m_Bias != <span class="keyword">nullptr</span>,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="stringliteral">&quot;FoldPadIntoConvolution2d: Bias data should not be null if bias is enabled.&quot;</span>);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; newConv2dLayer.m_Bias = std::move(convolution2dLayer-&gt;m_Bias);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; }</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160;</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <span class="comment">// Reconnects with original parent.</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; newConv2dLayer.GetOutputSlot().MoveAllConnections(*parentOut);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="comment">// Parent is now the new convolution2d layer.</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; parentOut = &amp;newConv2dLayer.GetOutputSlot();</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="comment">// Moves connections in child output to parent layer.</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="comment">// Child layer will be removed as it&#39;s left unconnected.</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="comment">// Base layer will be removed if left unconnected.</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; child.GetOutputSlot().MoveAllConnections(*parentOut);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; }</div><div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00049">Types.hpp:49</a></div></div>
217<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">armnn::LayerType::Convolution2d</a></div></div>
218<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4ade43468adaf6acb2c38ebc0c1176f82f"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ade43468adaf6acb2c38ebc0c1176f82f">armnn::LayerType::Pad</a></div></div>
219<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
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221</div>
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223<hr/>The documentation for this class was generated from the following file:<ul>
224<li>src/armnn/optimizations/<a class="el" href="_fold_pad_into_convolution2d_8hpp_source.xhtml">FoldPadIntoConvolution2d.hpp</a></li>
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