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| <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1optimizations_1_1pad__fold_1_1_fold_pad_into_convolution2d_impl.html">FoldPadIntoConvolution2dImpl</a></td></tr> |
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| <tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="classarmnn_1_1optimizations_1_1pad__fold_1_1_fold_pad_into_depthwise_convolution2d_impl.html">FoldPadIntoDepthwiseConvolution2dImpl</a></td></tr> |
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| Functions</h2></td></tr> |
| <tr class="memitem:a41605a45fe3f148071b04c7d861f391f"><td class="memItemLeft" align="right" valign="top">float </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a41605a45fe3f148071b04c7d861f391f">GetZeroElement</a> (const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> &tensorInfo)</td></tr> |
| <tr class="separator:a41605a45fe3f148071b04c7d861f391f"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a1112c7c010be092e8d2478e5268666de"><td class="memItemLeft" align="right" valign="top">float </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a1112c7c010be092e8d2478e5268666de">GetLowestElement</a> (const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> &tensorInfo)</td></tr> |
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| <tr class="memitem:aef8fbdfbe08862db57b8ea6e09d84bce"><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#aef8fbdfbe08862db57b8ea6e09d84bce">IsNeutralElement</a> (const <a class="el" href="structarmnn_1_1_convolution2d_descriptor.html">Convolution2dDescriptor</a> &, const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> &tensorInfo, const float tensorValue)</td></tr> |
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| <tr class="memitem:a9c5795e478ba9afc068c645f3ac72ca5"><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a9c5795e478ba9afc068c645f3ac72ca5">IsNeutralElement</a> (const <a class="el" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">DepthwiseConvolution2dDescriptor</a> &, const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> &tensorInfo, const float tensorValue)</td></tr> |
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| <tr class="memitem:a860dc7bc83a72db266ef5d6759686d24"><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a860dc7bc83a72db266ef5d6759686d24">IsNeutralElement</a> (const <a class="el" href="structarmnn_1_1_pooling2d_descriptor.html">Pooling2dDescriptor</a> &descriptor, const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> &tensorInfo, const float tensorValue)</td></tr> |
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| <tr class="memitem:a9f3ad988ab5cf0c11de5380e77bbb50e"><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a9f3ad988ab5cf0c11de5380e77bbb50e">IsPooling2dPadded</a> (const <a class="el" href="structarmnn_1_1_pooling2d_descriptor.html">Pooling2dDescriptor</a> &poolDescriptor)</td></tr> |
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| <tr class="memitem:a33ffc65d1f6581b0789d3d3a033f698e"><td class="memTemplParams" colspan="2">template<typename Descriptor > </td></tr> |
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| <tr class="memitem:adeaaacf15ed6830d77298930545187e6"><td class="memItemLeft" align="right" valign="top">bool </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#adeaaacf15ed6830d77298930545187e6">TryFoldPadIntoLayer2d</a> (const <a class="el" href="structarmnn_1_1_pad_descriptor.html">PadDescriptor</a> &padDescriptor, <a class="el" href="structarmnn_1_1_pooling2d_descriptor.html">Pooling2dDescriptor</a> &poolDescriptor, const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> &tensorInfo, bool isBackendOptimization=false)</td></tr> |
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| <tr class="memitem:a0dfb192db7209941d02bba0bd904822e"><td class="memTemplParams" colspan="2">template<typename Layer2dT > </td></tr> |
| <tr class="memitem:a0dfb192db7209941d02bba0bd904822e"><td class="memTemplItemLeft" align="right" valign="top">Layer2dT * </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a0dfb192db7209941d02bba0bd904822e">FoldPadIntoLayer2dImpl</a> (<a class="el" href="classarmnn_1_1_graph.html">Graph</a> &graph, <a class="el" href="classarmnn_1_1_input_slot.html">InputSlot</a> &connection)</td></tr> |
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| <h2 class="groupheader">Function Documentation</h2> |
| <a id="a0dfb192db7209941d02bba0bd904822e"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a0dfb192db7209941d02bba0bd904822e">◆ </a></span>FoldPadIntoLayer2dImpl()</h2> |
| |
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| <td class="memname">Layer2dT* armnn::optimizations::pad_fold::FoldPadIntoLayer2dImpl </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarmnn_1_1_graph.html">Graph</a> & </td> |
| <td class="paramname"><em>graph</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarmnn_1_1_input_slot.html">InputSlot</a> & </td> |
| <td class="paramname"><em>connection</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
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| </div><div class="memdoc"> |
| |
| <p class="definition">Definition at line <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00144">144</a> of file <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html">FoldPadIntoLayer2d.hpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> {</div> |
| <div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  PadLayer& padLayer = *PolymorphicDowncast<PadLayer*>(&connection.GetConnectedOutputSlot()->GetOwningLayer());</div> |
| <div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  Layer2dT& layer2d = *PolymorphicDowncast<Layer2dT*>(&connection.GetOwningLayer());</div> |
| <div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  </div> |
| <div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keyword">const</span> PadDescriptor& padDescriptor = padLayer.GetParameters();</div> |
| <div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keyword">auto</span> newLayer2dDescriptor = layer2d.GetParameters();</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>  <span class="keywordflow">if</span> (!<a class="code" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#adeaaacf15ed6830d77298930545187e6">TryFoldPadIntoLayer2d</a>(padDescriptor, newLayer2dDescriptor, padLayer.GetOutputSlot().GetTensorInfo()))</div> |
| <div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  {</div> |
| <div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div> |
| <div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  }</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">// Workaround an issue in the compute library. The conv2d algorithm that the</span></div> |
| <div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="comment">// compute library is choosing is not handling the 1x1 filter case when</span></div> |
| <div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">// the padding size >= filter size</span></div> |
| <div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordflow">if</span> (layer2d.GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">armnn::LayerType::Convolution2d</a>)</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">// Get filter width and height</span></div> |
| <div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a> dataLayoutIndex(newLayer2dDescriptor.m_DataLayout);</div> |
| <div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keyword">const</span> TensorShape& filterShape = layer2d.GetInputSlot(1).GetTensorInfo().GetShape();</div> |
| <div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterWidth = filterShape[dataLayoutIndex.GetWidthIndex()];</div> |
| <div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterHeight = filterShape[dataLayoutIndex.GetHeightIndex()];</div> |
| <div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="comment">// Calculate total padding and check conditions</span></div> |
| <div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="keyword">auto</span> horizontalPadding = newLayer2dDescriptor.m_PadLeft + newLayer2dDescriptor.m_PadRight;</div> |
| <div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keyword">auto</span> verticalPadding = newLayer2dDescriptor.m_PadTop + newLayer2dDescriptor.m_PadBottom;</div> |
| <div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="keywordflow">if</span> ((filterWidth == 1) && (horizontalPadding >= filterWidth))</div> |
| <div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  {</div> |
| <div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div> |
| <div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  }</div> |
| <div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> ((filterHeight == 1) && (verticalPadding >= filterHeight))</div> |
| <div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  {</div> |
| <div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div> |
| <div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  }</div> |
| <div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  }</div> |
| <div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  </div> |
| <div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="comment">// Save original parent output slot of the pad layer</span></div> |
| <div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  OutputSlot& parentSlot = *padLayer.GetInputSlot(0).GetConnectedOutputSlot();</div> |
| <div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  </div> |
| <div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="comment">// Insert new layer2d layer between the pad layer and its parent layer.</span></div> |
| <div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keyword">const</span> std::string name = std::string(<span class="stringliteral">"folded-"</span>) + padLayer.GetName() + <span class="stringliteral">"-into-"</span> + layer2d.GetName();</div> |
| <div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keyword">auto</span>& newLayer2d = *graph.InsertNewLayer<Layer2dT>(padLayer.GetInputSlot(0), newLayer2dDescriptor, name.c_str());</div> |
| <div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  </div> |
| <div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  newLayer2d.GetOutputSlot().MoveAllConnections(parentSlot);</div> |
| <div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="comment">// Start at 1 to connect only weights and bias</span></div> |
| <div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 1; i < layer2d.GetNumInputSlots(); ++i)</div> |
| <div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  {</div> |
| <div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keywordflow">if</span> (layer2d.GetInputSlot(i).GetConnectedOutputSlot() != <span class="keyword">nullptr</span>)</div> |
| <div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  {</div> |
| <div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  Layer& tgtLayer = layer2d.GetInputSlot(i).GetConnectedOutputSlot()->GetOwningLayer();</div> |
| <div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="comment">// Remove old connection and connect to new layer2d</span></div> |
| <div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  tgtLayer.GetOutputSlot(0).Disconnect(layer2d.GetInputSlot(i));</div> |
| <div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  tgtLayer.GetOutputSlot(0).Connect(newLayer2d.GetInputSlot(i));</div> |
| <div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  }</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>  </div> |
| <div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="comment">// Moves connections in old layer2d layer output to new layer.</span></div> |
| <div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="comment">// Old layer2d layer will be removed as it's left unconnected.</span></div> |
| <div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="comment">// Pad layer will be removed if left unconnected.</span></div> |
| <div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  layer2d.GetOutputSlot().MoveAllConnections(newLayer2d.GetOutputSlot());</div> |
| <div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  </div> |
| <div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordflow">return</span> &newLayer2d;</div> |
| <div class="line"><a name="l00206"></a><span class="lineno"> 206</span> }</div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_layer_8cpp_source.html#l00123">OutputSlot::Connect()</a>, <a class="el" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">armnn::Convolution2d</a>, <a class="el" href="_layer_8cpp_source.html#l00131">OutputSlot::Disconnect()</a>, <a class="el" href="_layer_8hpp_source.html#l00056">InputSlot::GetConnectedOutputSlot()</a>, <a class="el" href="_data_layout_indexed_8hpp_source.html#l00024">DataLayoutIndexed::GetHeightIndex()</a>, <a class="el" href="_layer_8hpp_source.html#l00337">Layer::GetInputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00332">Layer::GetName()</a>, <a class="el" href="_layer_8hpp_source.html#l00339">Layer::GetOutputSlot()</a>, <a class="el" href="_layer_8hpp_source.html#l00053">InputSlot::GetOwningLayer()</a>, <a class="el" href="_layer_8hpp_source.html#l00132">OutputSlot::GetOwningLayer()</a>, <a class="el" href="_layer_with_parameters_8hpp_source.html#l00019">LayerWithParameters< Parameters >::GetParameters()</a>, <a class="el" href="_layer_8cpp_source.html#l00100">OutputSlot::GetTensorInfo()</a>, <a class="el" href="_data_layout_indexed_8hpp_source.html#l00025">DataLayoutIndexed::GetWidthIndex()</a>, <a class="el" href="_graph_8hpp_source.html#l00481">Graph::InsertNewLayer()</a>, and <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00088">TryFoldPadIntoLayer2d()</a>.</p> |
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| </div> |
| </div> |
| <a id="a1112c7c010be092e8d2478e5268666de"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a1112c7c010be092e8d2478e5268666de">◆ </a></span>GetLowestElement()</h2> |
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| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
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| <td class="mlabels-left"> |
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| <td class="memname">float armnn::optimizations::pad_fold::GetLowestElement </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> & </td> |
| <td class="paramname"><em>tensorInfo</em></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">inline</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p class="definition">Definition at line <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00026">26</a> of file <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html">FoldPadIntoLayer2d.hpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> {</div> |
| <div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  constexpr <span class="keywordtype">float</span> negativeInfinity = -std::numeric_limits<float>::infinity();</div> |
| <div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> scale = tensorInfo.GetQuantizationScale();</div> |
| <div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keyword">const</span> int32_t offset = tensorInfo.GetQuantizationOffset();</div> |
| <div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  </div> |
| <div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keywordflow">switch</span> (tensorInfo.GetDataType())</div> |
| <div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  {</div> |
| <div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keywordflow">case</span> DataType::Float16:</div> |
| <div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keywordflow">return</span> armnnUtils::SelectiveQuantize<armnn::Half>(negativeInfinity, scale, offset);</div> |
| <div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keywordflow">case</span> DataType::Float32:</div> |
| <div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordflow">return</span> armnnUtils::SelectiveQuantize<float>(negativeInfinity, scale, offset);</div> |
| <div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordflow">case</span> DataType::QAsymmU8:</div> |
| <div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordflow">return</span> armnnUtils::SelectiveQuantize<uint8_t>(negativeInfinity, scale, offset);</div> |
| <div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordflow">case</span> DataType::QSymmS16:</div> |
| <div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordflow">return</span> armnnUtils::SelectiveQuantize<int16_t>(negativeInfinity, scale, offset);</div> |
| <div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordflow">case</span> DataType::QSymmS8:</div> |
| <div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="comment">// Fall-through</span></div> |
| <div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordflow">case</span> DataType::QAsymmS8:</div> |
| <div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">return</span> armnnUtils::SelectiveQuantize<int8_t>(negativeInfinity, scale, offset);</div> |
| <div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordflow">case</span> DataType::BFloat16:</div> |
| <div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">return</span> armnnUtils::SelectiveQuantize<armnn::BFloat16>(negativeInfinity, scale, offset);</div> |
| <div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordflow">default</span>:</div> |
| <div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  {</div> |
| <div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="_assert_8hpp.html#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(<span class="keyword">false</span>, <span class="stringliteral">"Unsupported DataType"</span>);</div> |
| <div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordflow">return</span> NAN;</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>  }</div> |
| <div class="line"><a name="l00054"></a><span class="lineno"> 54</span> }</div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_assert_8hpp_source.html#l00015">ARMNN_ASSERT_MSG</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::BFloat16</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::Float16</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_tensor_8hpp_source.html#l00200">TensorInfo::GetDataType()</a>, <a class="el" href="_tensor_8cpp_source.html#l00482">TensorInfo::GetQuantizationOffset()</a>, <a class="el" href="_tensor_8cpp_source.html#l00461">TensorInfo::GetQuantizationScale()</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::QAsymmS8</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::QAsymmU8</a>, <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::QSymmS16</a>, and <a class="el" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::QSymmS8</a>.</p> |
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| <p class="reference">Referenced by <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00068">IsNeutralElement()</a>.</p> |
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| </div> |
| </div> |
| <a id="a41605a45fe3f148071b04c7d861f391f"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a41605a45fe3f148071b04c7d861f391f">◆ </a></span>GetZeroElement()</h2> |
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| <div class="memitem"> |
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| <td class="memname">float armnn::optimizations::pad_fold::GetZeroElement </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> & </td> |
| <td class="paramname"><em>tensorInfo</em></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
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| <span class="mlabels"><span class="mlabel">inline</span></span> </td> |
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| </div><div class="memdoc"> |
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| <p class="definition">Definition at line <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00021">21</a> of file <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html">FoldPadIntoLayer2d.hpp</a>.</p> |
| <div class="fragment"><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>  <span class="keywordflow">return</span> <span class="keyword">static_cast<</span><span class="keywordtype">float</span><span class="keyword">></span>(tensorInfo.IsQuantized() ? tensorInfo.GetQuantizationOffset() : 0);</div> |
| <div class="line"><a name="l00024"></a><span class="lineno"> 24</span> }</div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_tensor_8cpp_source.html#l00482">TensorInfo::GetQuantizationOffset()</a>, and <a class="el" href="_tensor_8cpp_source.html#l00508">TensorInfo::IsQuantized()</a>.</p> |
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| <p class="reference">Referenced by <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00056">IsNeutralElement()</a>.</p> |
| |
| </div> |
| </div> |
| <a id="aef8fbdfbe08862db57b8ea6e09d84bce"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#aef8fbdfbe08862db57b8ea6e09d84bce">◆ </a></span>IsNeutralElement() <span class="overload">[1/3]</span></h2> |
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| <div class="memitem"> |
| <div class="memproto"> |
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| <td class="mlabels-left"> |
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| <td class="memname">bool armnn::optimizations::pad_fold::IsNeutralElement </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="structarmnn_1_1_convolution2d_descriptor.html">Convolution2dDescriptor</a> & </td> |
| <td class="paramname">, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> & </td> |
| <td class="paramname"><em>tensorInfo</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const float </td> |
| <td class="paramname"><em>tensorValue</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">inline</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p class="definition">Definition at line <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00056">56</a> of file <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html">FoldPadIntoLayer2d.hpp</a>.</p> |
| <div class="fragment"><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="keywordflow">return</span> tensorValue == <a class="code" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a41605a45fe3f148071b04c7d861f391f">GetZeroElement</a>(tensorInfo);</div> |
| <div class="line"><a name="l00059"></a><span class="lineno"> 59</span> }</div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00021">GetZeroElement()</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00088">TryFoldPadIntoLayer2d()</a>.</p> |
| |
| </div> |
| </div> |
| <a id="a9c5795e478ba9afc068c645f3ac72ca5"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a9c5795e478ba9afc068c645f3ac72ca5">◆ </a></span>IsNeutralElement() <span class="overload">[2/3]</span></h2> |
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| <td class="memname">bool armnn::optimizations::pad_fold::IsNeutralElement </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">DepthwiseConvolution2dDescriptor</a> & </td> |
| <td class="paramname">, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> & </td> |
| <td class="paramname"><em>tensorInfo</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const float </td> |
| <td class="paramname"><em>tensorValue</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">inline</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p class="definition">Definition at line <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00061">61</a> of file <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html">FoldPadIntoLayer2d.hpp</a>.</p> |
| <div class="fragment"><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>  <span class="keywordflow">return</span> tensorValue == <a class="code" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a41605a45fe3f148071b04c7d861f391f">GetZeroElement</a>(tensorInfo);</div> |
| <div class="line"><a name="l00066"></a><span class="lineno"> 66</span> }</div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00021">GetZeroElement()</a>.</p> |
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| </div> |
| </div> |
| <a id="a860dc7bc83a72db266ef5d6759686d24"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a860dc7bc83a72db266ef5d6759686d24">◆ </a></span>IsNeutralElement() <span class="overload">[3/3]</span></h2> |
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| <td class="memname">bool armnn::optimizations::pad_fold::IsNeutralElement </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="structarmnn_1_1_pooling2d_descriptor.html">Pooling2dDescriptor</a> & </td> |
| <td class="paramname"><em>descriptor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> & </td> |
| <td class="paramname"><em>tensorInfo</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const float </td> |
| <td class="paramname"><em>tensorValue</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </td> |
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| <span class="mlabels"><span class="mlabel">inline</span></span> </td> |
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| <p class="definition">Definition at line <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00068">68</a> of file <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html">FoldPadIntoLayer2d.hpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> {</div> |
| <div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordflow">return</span> (descriptor.m_PoolType == PoolingAlgorithm::Max)</div> |
| <div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  ? tensorValue <= <a class="code" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a1112c7c010be092e8d2478e5268666de">GetLowestElement</a>(tensorInfo)</div> |
| <div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  : tensorValue == <a class="code" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a41605a45fe3f148071b04c7d861f391f">GetZeroElement</a>(tensorInfo);</div> |
| <div class="line"><a name="l00074"></a><span class="lineno"> 74</span> }</div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00026">GetLowestElement()</a>, <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00021">GetZeroElement()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00405">Pooling2dDescriptor::m_PoolType</a>, and <a class="el" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::Max</a>.</p> |
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| <a id="a9f3ad988ab5cf0c11de5380e77bbb50e"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a9f3ad988ab5cf0c11de5380e77bbb50e">◆ </a></span>IsPooling2dPadded()</h2> |
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| <td class="memname">bool armnn::optimizations::pad_fold::IsPooling2dPadded </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="structarmnn_1_1_pooling2d_descriptor.html">Pooling2dDescriptor</a> & </td> |
| <td class="paramname"><em>poolDescriptor</em></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </td> |
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| <span class="mlabels"><span class="mlabel">inline</span></span> </td> |
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| <p class="definition">Definition at line <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00076">76</a> of file <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html">FoldPadIntoLayer2d.hpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> {</div> |
| <div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">const</span> <span class="keyword">auto</span> poolingPadValues = std::make_tuple(poolDescriptor.m_PadLeft, poolDescriptor.m_PadRight,</div> |
| <div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  poolDescriptor.m_PadTop, poolDescriptor.m_PadBottom);</div> |
| <div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordflow">if</span> (poolingPadValues != std::make_tuple(0U, 0U, 0U, 0U))</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>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  }</div> |
| <div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l00085"></a><span class="lineno"> 85</span> }</div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_descriptors_8hpp_source.html#l00413">Pooling2dDescriptor::m_PadBottom</a>, <a class="el" href="_descriptors_8hpp_source.html#l00407">Pooling2dDescriptor::m_PadLeft</a>, <a class="el" href="_descriptors_8hpp_source.html#l00409">Pooling2dDescriptor::m_PadRight</a>, and <a class="el" href="_descriptors_8hpp_source.html#l00411">Pooling2dDescriptor::m_PadTop</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00115">TryFoldPadIntoLayer2d()</a>.</p> |
| |
| </div> |
| </div> |
| <a id="a33ffc65d1f6581b0789d3d3a033f698e"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#a33ffc65d1f6581b0789d3d3a033f698e">◆ </a></span>TryFoldPadIntoLayer2d() <span class="overload">[1/2]</span></h2> |
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| <td class="memname">bool armnn::optimizations::pad_fold::TryFoldPadIntoLayer2d </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="structarmnn_1_1_pad_descriptor.html">PadDescriptor</a> & </td> |
| <td class="paramname"><em>padDescriptor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">Descriptor & </td> |
| <td class="paramname"><em>layerDescriptor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> & </td> |
| <td class="paramname"><em>tensorInfo</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p class="definition">Definition at line <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00088">88</a> of file <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html">FoldPadIntoLayer2d.hpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> {</div> |
| <div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a> layout = <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a>(layerDescriptor.m_DataLayout);</div> |
| <div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchIndex = 0;</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>  constexpr <span class="keyword">auto</span> noPad = std::make_pair(0U, 0U);</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="keywordflow">if</span> ((!<a class="code" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a860dc7bc83a72db266ef5d6759686d24">IsNeutralElement</a>(layerDescriptor, tensorInfo, padDescriptor.m_PadValue)) ||</div> |
| <div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  (padDescriptor.m_PadList[batchIndex] != noPad) || (padDescriptor.m_PadList[layout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">GetChannelsIndex</a>()] != noPad))</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="keywordflow">return</span> <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  }</div> |
| <div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  </div> |
| <div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keyword">const</span> <span class="keyword">auto</span>& padList = padDescriptor.m_PadList;</div> |
| <div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  </div> |
| <div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="comment">// In Convolution2dDescriptor/Pooling2dDescriptor, padLeft and padRight are defined as paddings</span></div> |
| <div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="comment">// on width dimension whereas padTop and padBottom - paddings on height dimension, so updating</span></div> |
| <div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="comment">// these according to data layout</span></div> |
| <div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  layerDescriptor.m_PadLeft += padList[layout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()].first;</div> |
| <div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  layerDescriptor.m_PadRight += padList[layout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()].second;</div> |
| <div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  layerDescriptor.m_PadTop += padList[layout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()].first;</div> |
| <div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  layerDescriptor.m_PadBottom += padList[layout.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()].second;</div> |
| <div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  </div> |
| <div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div> |
| <div class="line"><a name="l00113"></a><span class="lineno"> 113</span> }</div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="_data_layout_indexed_8hpp_source.html#l00023">DataLayoutIndexed::GetChannelsIndex()</a>, <a class="el" href="_data_layout_indexed_8hpp_source.html#l00024">DataLayoutIndexed::GetHeightIndex()</a>, <a class="el" href="_data_layout_indexed_8hpp_source.html#l00025">DataLayoutIndexed::GetWidthIndex()</a>, <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00056">IsNeutralElement()</a>, <a class="el" href="_descriptors_8hpp_source.html#l01218">PadDescriptor::m_PadList</a>, and <a class="el" href="_descriptors_8hpp_source.html#l01221">PadDescriptor::m_PadValue</a>.</p> |
| |
| <p class="reference">Referenced by <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00144">FoldPadIntoLayer2dImpl()</a>, <a class="el" href="_ref_backend_8cpp_source.html#l00072">RefBackend::OptimizeSubgraphView()</a>, and <a class="el" href="_cl_backend_8cpp_source.html#l00292">ClBackend::OptimizeSubgraphView()</a>.</p> |
| |
| </div> |
| </div> |
| <a id="adeaaacf15ed6830d77298930545187e6"></a> |
| <h2 class="memtitle"><span class="permalink"><a href="#adeaaacf15ed6830d77298930545187e6">◆ </a></span>TryFoldPadIntoLayer2d() <span class="overload">[2/2]</span></h2> |
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| <td class="memname">bool armnn::optimizations::pad_fold::TryFoldPadIntoLayer2d </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="structarmnn_1_1_pad_descriptor.html">PadDescriptor</a> & </td> |
| <td class="paramname"><em>padDescriptor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="structarmnn_1_1_pooling2d_descriptor.html">Pooling2dDescriptor</a> & </td> |
| <td class="paramname"><em>poolDescriptor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> & </td> |
| <td class="paramname"><em>tensorInfo</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">bool </td> |
| <td class="paramname"><em>isBackendOptimization</em> = <code>false</code> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">inline</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
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| <p class="definition">Definition at line <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00115">115</a> of file <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html">FoldPadIntoLayer2d.hpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> {</div> |
| <div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="comment">// Cannot fold Average or L2 pooling if padding exists and the padding method is Exclude.</span></div> |
| <div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">if</span> (poolDescriptor.m_PoolType != PoolingAlgorithm::Max &&</div> |
| <div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <a class="code" href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a9f3ad988ab5cf0c11de5380e77bbb50e">IsPooling2dPadded</a>(poolDescriptor) &&</div> |
| <div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  poolDescriptor.m_PaddingMethod == PaddingMethod::Exclude)</div> |
| <div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  {</div> |
| <div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div> |
| <div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  }</div> |
| <div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  </div> |
| <div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="comment">// Cannot fold Average pooling if data type is quantized and layout is NHWC in Neon backend.</span></div> |
| <div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="comment">// Therefore, this specific case will become a backend specific optimization.</span></div> |
| <div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="keywordflow">if</span> (!isBackendOptimization &&</div> |
| <div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  tensorInfo.IsQuantized() &&</div> |
| <div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  poolDescriptor.m_PoolType == PoolingAlgorithm::Average &&</div> |
| <div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  poolDescriptor.m_DataLayout == DataLayout::NHWC)</div> |
| <div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  {</div> |
| <div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordflow">return</span> <span class="keyword">false</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>  </div> |
| <div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  poolDescriptor.m_PaddingMethod = PaddingMethod::IgnoreValue;</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="keywordflow">return</span> TryFoldPadIntoLayer2d<Pooling2dDescriptor>(padDescriptor, poolDescriptor, tensorInfo);</div> |
| <div class="line"><a name="l00141"></a><span class="lineno"> 141</span> }</div> |
| </div><!-- fragment --> |
| <p class="reference">References <a class="el" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::Average</a>, <a class="el" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::Exclude</a>, <a class="el" href="namespacearmnn.html#a3888429b6ebc79f9a7df549e5e4d9a2faad301514192636ad34210adce598a45a">armnn::IgnoreValue</a>, <a class="el" href="_fold_pad_into_layer2d_8hpp_source.html#l00076">IsPooling2dPadded()</a>, <a class="el" href="_tensor_8cpp_source.html#l00508">TensorInfo::IsQuantized()</a>, <a class="el" href="_descriptors_8hpp_source.html#l00427">Pooling2dDescriptor::m_DataLayout</a>, <a class="el" href="_descriptors_8hpp_source.html#l00425">Pooling2dDescriptor::m_PaddingMethod</a>, <a class="el" href="_descriptors_8hpp_source.html#l00405">Pooling2dDescriptor::m_PoolType</a>, <a class="el" href="namespacearmnn.html#a961bbfe1db71a848eff5a1f0ab775718a6a061313d22e51e0f25b7cd4dc065233">armnn::Max</a>, and <a class="el" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::NHWC</a>.</p> |
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| <div class="ttc" id="anamespacearmnn_1_1optimizations_1_1pad__fold_html_a9f3ad988ab5cf0c11de5380e77bbb50e"><div class="ttname"><a href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a9f3ad988ab5cf0c11de5380e77bbb50e">armnn::optimizations::pad_fold::IsPooling2dPadded</a></div><div class="ttdeci">bool IsPooling2dPadded(const Pooling2dDescriptor &poolDescriptor)</div><div class="ttdef"><b>Definition:</b> <a href="_fold_pad_into_layer2d_8hpp_source.html#l00076">FoldPadIntoLayer2d.hpp:76</a></div></div> |
| <div class="ttc" id="aclassarmnn_utils_1_1_data_layout_indexed_html"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a></div><div class="ttdoc">Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout.</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00017">DataLayoutIndexed.hpp:17</a></div></div> |
| <div class="ttc" id="a_assert_8hpp_html_a91c4dfde57907d7698c7531785690a7f"><div class="ttname"><a href="_assert_8hpp.html#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a></div><div class="ttdeci">#define ARMNN_ASSERT_MSG(COND, MSG)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.html#l00015">Assert.hpp:15</a></div></div> |
| <div class="ttc" id="aclassarmnn_utils_1_1_data_layout_indexed_html_a61c00316c443adc233c24e85c6c5b740"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">armnnUtils::DataLayoutIndexed::GetHeightIndex</a></div><div class="ttdeci">unsigned int GetHeightIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00024">DataLayoutIndexed.hpp:24</a></div></div> |
| <div class="ttc" id="anamespacearmnn_1_1optimizations_1_1pad__fold_html_a1112c7c010be092e8d2478e5268666de"><div class="ttname"><a href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a1112c7c010be092e8d2478e5268666de">armnn::optimizations::pad_fold::GetLowestElement</a></div><div class="ttdeci">float GetLowestElement(const TensorInfo &tensorInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_fold_pad_into_layer2d_8hpp_source.html#l00026">FoldPadIntoLayer2d.hpp:26</a></div></div> |
| <div class="ttc" id="aclassarmnn_utils_1_1_data_layout_indexed_html_a414e6f95548e6f7a01d5028b55ad3941"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">armnnUtils::DataLayoutIndexed::GetWidthIndex</a></div><div class="ttdeci">unsigned int GetWidthIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00025">DataLayoutIndexed.hpp:25</a></div></div> |
| <div class="ttc" id="aclassarmnn_utils_1_1_data_layout_indexed_html_a861b2621ee46e4b63379988b360b8cd9"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a861b2621ee46e4b63379988b360b8cd9">armnnUtils::DataLayoutIndexed::GetChannelsIndex</a></div><div class="ttdeci">unsigned int GetChannelsIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00023">DataLayoutIndexed.hpp:23</a></div></div> |
| <div class="ttc" id="anamespacearmnn_1_1optimizations_1_1pad__fold_html_adeaaacf15ed6830d77298930545187e6"><div class="ttname"><a href="namespacearmnn_1_1optimizations_1_1pad__fold.html#adeaaacf15ed6830d77298930545187e6">armnn::optimizations::pad_fold::TryFoldPadIntoLayer2d</a></div><div class="ttdeci">bool TryFoldPadIntoLayer2d(const PadDescriptor &padDescriptor, Pooling2dDescriptor &poolDescriptor, const TensorInfo &tensorInfo, bool isBackendOptimization=false)</div><div class="ttdef"><b>Definition:</b> <a href="_fold_pad_into_layer2d_8hpp_source.html#l00115">FoldPadIntoLayer2d.hpp:115</a></div></div> |
| <div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">armnn::LayerType::Convolution2d</a></div><div class="ttdeci">@ Convolution2d</div></div> |
| <div class="ttc" id="anamespacearmnn_1_1optimizations_1_1pad__fold_html_a41605a45fe3f148071b04c7d861f391f"><div class="ttname"><a href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a41605a45fe3f148071b04c7d861f391f">armnn::optimizations::pad_fold::GetZeroElement</a></div><div class="ttdeci">float GetZeroElement(const TensorInfo &tensorInfo)</div><div class="ttdef"><b>Definition:</b> <a href="_fold_pad_into_layer2d_8hpp_source.html#l00021">FoldPadIntoLayer2d.hpp:21</a></div></div> |
| <div class="ttc" id="anamespacearmnn_1_1optimizations_1_1pad__fold_html_a860dc7bc83a72db266ef5d6759686d24"><div class="ttname"><a href="namespacearmnn_1_1optimizations_1_1pad__fold.html#a860dc7bc83a72db266ef5d6759686d24">armnn::optimizations::pad_fold::IsNeutralElement</a></div><div class="ttdeci">bool IsNeutralElement(const Pooling2dDescriptor &descriptor, const TensorInfo &tensorInfo, const float tensorValue)</div><div class="ttdef"><b>Definition:</b> <a href="_fold_pad_into_layer2d_8hpp_source.html#l00068">FoldPadIntoLayer2d.hpp:68</a></div></div> |
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