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<div class="title">MaxMinIntoBoundedRelu.hpp</div> </div>
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<a href="_max_min_into_bounded_relu_8hpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2024 Arm Ltd and Contributors. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160; </div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#pragma once</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160; </div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_optimization_8hpp.html">Optimization.hpp</a>&quot;</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160; </div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn_1_1optimizations.html">armnn::optimizations</a></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;{</div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160; </div>
<div class="line"><a name="l00013"></a><span class="lineno"><a class="line" href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html"> 13</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html">MaxMinIntoBoundedReluImpl</a></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;{</div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="keyword">public</span>:<span class="comment"></span></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> /// Run for every exclusive connection between any Max &amp; Min layers</span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> /// The Max, Min and its associated constant inputs will be removed, and replaced with a BoundedRelu Activation</span></div>
<div class="line"><a name="l00018"></a><span class="lineno"><a class="line" href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html#ab8beb4d0cfc5c103045f261ff726b08e"> 18</a></span>&#160;<span class="comment"></span> <span class="keyword">static</span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html#ab8beb4d0cfc5c103045f261ff726b08e">Run</a>(<a class="code" href="classarmnn_1_1_graph.html">Graph</a>&amp; graph, <a class="code" href="classarmnn_1_1_input_slot.html">InputSlot</a>&amp; connection)</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; {</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; <a class="code" href="classarmnn_1_1_layer.html">Layer</a>&amp; base = connection.<a class="code" href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">GetConnectedOutputSlot</a>()-&gt;<a class="code" href="classarmnn_1_1_output_slot.html#a7ddaf04177053a536f0e7be83a642bc6">GetOwningLayer</a>();</div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; <a class="code" href="classarmnn_1_1_layer.html">Layer</a>&amp; child = connection.<a class="code" href="classarmnn_1_1_input_slot.html#a7ddaf04177053a536f0e7be83a642bc6">GetOwningLayer</a>();</div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; </div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; <span class="keyword">auto</span>&amp; maxLayer = *PolymorphicDowncast&lt;ElementwiseBinaryLayer*&gt;(&amp;base);</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; <span class="keywordflow">if</span> (maxLayer.GetParameters().m_Operation != <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a8321e79c278ec510f63675c040594892">BinaryOperation::Maximum</a>)</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; {</div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; }</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; <span class="keyword">auto</span>&amp; minLayer = *PolymorphicDowncast&lt;ElementwiseBinaryLayer*&gt;(&amp;child);</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <span class="keywordflow">if</span> (minLayer.GetParameters().m_Operation != <a class="code" href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aa1d0ec6d56f8833a078b5a7ac4caf2d4">BinaryOperation::Minimum</a>)</div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; {</div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keywordflow">return</span>;</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; </div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; <span class="keywordflow">if</span> (maxLayer.GetDataType() != minLayer.GetDataType())</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="keywordflow">return</span>;</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; </div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="comment">// get max and min values</span></div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; float_t maxValue;</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="keywordflow">if</span> (!GetValue(maxLayer, maxValue))</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; {</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; }</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; float_t minValue;</div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="keywordflow">if</span> (!GetValue(minLayer, minValue))</div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; {</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; }</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; <span class="comment">// Save original parent output slot of the max layer</span></div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <a class="code" href="classarmnn_1_1_output_slot.html">OutputSlot</a>&amp; parentOut = *maxLayer.GetInputSlot(0).GetConnectedOutputSlot();</div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; </div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="comment">// Insert activation layer between max layer and its parent layer</span></div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; <a class="code" href="structarmnn_1_1_activation_descriptor.html">ActivationDescriptor</a> boundedReluDescriptor(<a class="code" href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">ActivationFunction::BoundedReLu</a>, minValue, maxValue);</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="keyword">const</span> std::string name = std::string(<span class="stringliteral">&quot;replaced-&quot;</span>) + maxLayer.GetName() + std::string(<span class="stringliteral">&quot;-&quot;</span>) + minLayer.GetName()</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; + std::string(<span class="stringliteral">&quot;-with-BoundedRelu&quot;</span>);</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="keyword">auto</span>&amp; boundedReluLayer = *graph.<a class="code" href="classarmnn_1_1_graph.html#a3ff30c6669fdc69de1f5be1f89bacc3f">InsertNewLayer</a>&lt;<a class="code" href="classarmnn_1_1_activation_layer.html">ActivationLayer</a>&gt;(maxLayer.GetInputSlot(0),</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; boundedReluDescriptor,</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; name.c_str());</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">// Reconnects with original parent.</span></div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; boundedReluLayer.<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a19d30f83e90f2612e6aec510715f790d">MoveAllConnections</a>(parentOut);</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; </div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="comment">// Moves connections in min layer output to parent layer.</span></div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="comment">// Min layer will be removed as it&#39;s left unconnected.</span></div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="comment">// Max layer will be removed if left unconnected.</span></div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; minLayer.GetOutputSlot().MoveAllConnections(boundedReluLayer.GetOutputSlot());</div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; }</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; </div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160;<span class="keyword">protected</span>:</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <a class="code" href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html#a65db2d72b0776e98bacbd6037b374d09">MaxMinIntoBoundedReluImpl</a>() = <span class="keywordflow">default</span>;</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <a class="code" href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html#a43b1f24af6a51c0e749e200d1bbcf765">~MaxMinIntoBoundedReluImpl</a>() = <span class="keywordflow">default</span>;</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; </div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160;<span class="keyword">private</span>:</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keyword">static</span> float_t GetConstTensorValue(<a class="code" href="classarmnn_1_1_layer.html">Layer</a>&amp; layer)</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="keyword">auto</span>&amp; constLayer = *PolymorphicDowncast&lt;ConstantLayer*&gt;(&amp;layer);</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="keywordflow">switch</span> (constLayer.GetDataType())</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; {</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>:</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="keywordflow">return</span> *constLayer.m_LayerOutput-&gt;GetConstTensor&lt;<span class="keywordtype">float</span>&gt;();</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">DataType::BFloat16</a>:</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="keywordflow">return</span> <span class="keyword">static_cast&lt;</span>float_t<span class="keyword">&gt;</span>(*constLayer.m_LayerOutput-&gt;GetConstTensor&lt;<a class="code" href="classarmnn_1_1_b_float16.html">BFloat16</a>&gt;());</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>:</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="keywordflow">return</span> <span class="keyword">static_cast&lt;</span>float_t<span class="keyword">&gt;</span>(*constLayer.m_LayerOutput-&gt;GetConstTensor&lt;half_float::half&gt;());</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>:</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">DataType::Boolean</a>:</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <span class="keywordflow">return</span> <span class="keyword">static_cast&lt;</span>float_t<span class="keyword">&gt;</span>(*constLayer.m_LayerOutput-&gt;GetConstTensor&lt;uint8_t&gt;());</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">DataType::QAsymmS8</a>:</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>:</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; <span class="keywordflow">return</span> <span class="keyword">static_cast&lt;</span>float_t<span class="keyword">&gt;</span>(*constLayer.m_LayerOutput-&gt;GetConstTensor&lt;int8_t&gt;());</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">DataType::QSymmS16</a>:</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <span class="keywordflow">return</span> <span class="keyword">static_cast&lt;</span>float_t<span class="keyword">&gt;</span>(*constLayer.m_LayerOutput-&gt;GetConstTensor&lt;int16_t&gt;());</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>:</div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="keywordflow">return</span> <span class="keyword">static_cast&lt;</span>float_t<span class="keyword">&gt;</span>(*constLayer.m_LayerOutput-&gt;GetConstTensor&lt;int32_t&gt;());</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6ae1b3c9c6087a93b07c83e0b04f377a8d">DataType::Signed64</a>:</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <span class="keywordflow">return</span> <span class="keyword">static_cast&lt;</span>float_t<span class="keyword">&gt;</span>(*constLayer.m_LayerOutput-&gt;GetConstTensor&lt;int64_t&gt;());</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="keywordflow">default</span>:</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_invalid_argument_exception.html">InvalidArgumentException</a>(<span class="stringliteral">&quot;No supported Data Type&quot;</span>);</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; }</div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; }</div>
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; </div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <span class="keyword">static</span> <span class="keywordtype">bool</span> GetValue(Layer&amp; layer, float_t&amp; value)</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; {</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; Layer&amp; input0 = layer.GetInputSlot(0).GetConnectedOutputSlot()-&gt;GetOwningLayer();</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; Layer&amp; input1 = layer.GetInputSlot(1).GetConnectedOutputSlot()-&gt;GetOwningLayer();</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; <span class="keywordflow">if</span> (input0.GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; {</div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <span class="keywordflow">if</span> (input0.GetOutputSlot(0).GetTensorInfo().GetNumElements() != 1)</div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; {</div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; }</div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; value = GetConstTensorValue(input0);</div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; }</div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (input1.GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">LayerType::Constant</a>)</div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; {</div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="keywordflow">if</span> (input1.GetOutputSlot(0).GetTensorInfo().GetNumElements() != 1)</div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; {</div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; }</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; value = GetConstTensorValue(input1);</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; }</div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <span class="keywordflow">else</span></div>
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; {</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; }</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; };</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160;};</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; </div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160;<span class="keyword">using</span> <a class="code" href="namespacearmnn_1_1optimizations.html#abc1cdfdd0c890de85bfd7eaac1292ffe">MaxMinIntoBoundedRelu</a> = OptimizeForExclusiveConnection&lt;ElementwiseBinaryLayer,</div>
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; ElementwiseBinaryLayer,</div>
<div class="line"><a name="l00134"></a><span class="lineno"><a class="line" href="namespacearmnn_1_1optimizations.html#abc1cdfdd0c890de85bfd7eaac1292ffe"> 134</a></span>&#160; <a class="code" href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html">MaxMinIntoBoundedReluImpl</a>&gt;;</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; </div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160;} <span class="comment">// namespace armnn::optimizations</span></div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a></div><div class="ttdeci">@ Boolean</div></div>
<div class="ttc" id="aclassarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl_html_a65db2d72b0776e98bacbd6037b374d09"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html#a65db2d72b0776e98bacbd6037b374d09">armnn::optimizations::MaxMinIntoBoundedReluImpl::MaxMinIntoBoundedReluImpl</a></div><div class="ttdeci">MaxMinIntoBoundedReluImpl()=default</div></div>
<div class="ttc" id="astructarmnn_1_1_activation_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.html">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00036">Descriptors.hpp:36</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_input_slot_html_a7ddaf04177053a536f0e7be83a642bc6"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#a7ddaf04177053a536f0e7be83a642bc6">armnn::InputSlot::GetOwningLayer</a></div><div class="ttdeci">Layer &amp; GetOwningLayer() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00053">Layer.hpp:53</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_output_slot_html"><div class="ttname"><a href="classarmnn_1_1_output_slot.html">armnn::OutputSlot</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00100">Layer.hpp:100</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div><div class="ttdeci">@ Float32</div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; 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.html#l00339">Layer.hpp:339</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div><div class="ttdeci">@ QAsymmU8</div></div>
<div class="ttc" id="anamespacearmnn_html_a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d"><div class="ttname"><a href="namespacearmnn.html#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a></div><div class="ttdeci">@ BoundedReLu</div><div class="ttdoc">min(a, max(b, input)) ReLu1 &amp; ReLu6.</div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">armnn::DataType::QSymmS8</a></div><div class="ttdeci">@ QSymmS8</div></div>
<div class="ttc" id="a_optimization_8hpp_html"><div class="ttname"><a href="_optimization_8hpp.html">Optimization.hpp</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a></div><div class="ttdeci">@ QSymmS16</div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a></div><div class="ttdeci">@ BFloat16</div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00230">Layer.hpp:230</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ac4f8557279754ed7b3f749d55b0e3047a8321e79c278ec510f63675c040594892"><div class="ttname"><a href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047a8321e79c278ec510f63675c040594892">armnn::BinaryOperation::Maximum</a></div><div class="ttdeci">@ Maximum</div></div>
<div class="ttc" id="aclassarmnn_1_1_output_slot_html_a7ddaf04177053a536f0e7be83a642bc6"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7ddaf04177053a536f0e7be83a642bc6">armnn::OutputSlot::GetOwningLayer</a></div><div class="ttdeci">Layer &amp; GetOwningLayer() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00132">Layer.hpp:132</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div><div class="ttdeci">@ Float16</div></div>
<div class="ttc" id="anamespacearmnn_1_1optimizations_html"><div class="ttname"><a href="namespacearmnn_1_1optimizations.html">armnn::optimizations</a></div><div class="ttdef"><b>Definition:</b> <a href="_add_broadcast_reshape_layer_8hpp_source.html#l00014">AddBroadcastReshapeLayer.hpp:14</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_invalid_argument_exception_html"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.html">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00080">Exceptions.hpp:80</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_output_slot_html_a19d30f83e90f2612e6aec510715f790d"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a19d30f83e90f2612e6aec510715f790d">armnn::OutputSlot::MoveAllConnections</a></div><div class="ttdeci">void MoveAllConnections(OutputSlot &amp;destination)</div><div class="ttdoc">Moves all connections to another OutputSlot.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00156">Layer.cpp:156</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_input_slot_html"><div class="ttname"><a href="classarmnn_1_1_input_slot.html">armnn::InputSlot</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00042">Layer.hpp:42</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a></div><div class="ttdeci">@ Signed32</div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div><div class="ttdeci">@ QAsymmS8</div></div>
<div class="ttc" id="aclassarmnn_1_1_activation_layer_html"><div class="ttname"><a href="classarmnn_1_1_activation_layer.html">armnn::ActivationLayer</a></div><div class="ttdoc">This layer represents an activation operation with the specified activation function.</div><div class="ttdef"><b>Definition:</b> <a href="_activation_layer_8hpp_source.html#l00012">ActivationLayer.hpp:12</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_b_float16_html"><div class="ttname"><a href="classarmnn_1_1_b_float16.html">armnn::BFloat16</a></div><div class="ttdef"><b>Definition:</b> <a href="_b_float16_8hpp_source.html#l00015">BFloat16.hpp:15</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ac4f8557279754ed7b3f749d55b0e3047aa1d0ec6d56f8833a078b5a7ac4caf2d4"><div class="ttname"><a href="namespacearmnn.html#ac4f8557279754ed7b3f749d55b0e3047aa1d0ec6d56f8833a078b5a7ac4caf2d4">armnn::BinaryOperation::Minimum</a></div><div class="ttdeci">@ Minimum</div></div>
<div class="ttc" id="aclassarmnn_1_1_input_slot_html_a9effd325a6d512a3f8ff4bd207d53255"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">armnn::InputSlot::GetConnectedOutputSlot</a></div><div class="ttdeci">const OutputSlot * GetConnectedOutputSlot() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00056">Layer.hpp:56</a></div></div>
<div class="ttc" id="aclassarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl_html"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html">armnn::optimizations::MaxMinIntoBoundedReluImpl</a></div><div class="ttdef"><b>Definition:</b> <a href="_max_min_into_bounded_relu_8hpp_source.html#l00013">MaxMinIntoBoundedRelu.hpp:13</a></div></div>
<div class="ttc" id="anamespacearmnn_1_1optimizations_html_abc1cdfdd0c890de85bfd7eaac1292ffe"><div class="ttname"><a href="namespacearmnn_1_1optimizations.html#abc1cdfdd0c890de85bfd7eaac1292ffe">armnn::optimizations::MaxMinIntoBoundedRelu</a></div><div class="ttdeci">OptimizeForExclusiveConnection&lt; ElementwiseBinaryLayer, ElementwiseBinaryLayer, MaxMinIntoBoundedReluImpl &gt; MaxMinIntoBoundedRelu</div><div class="ttdef"><b>Definition:</b> <a href="_max_min_into_bounded_relu_8hpp_source.html#l00134">MaxMinIntoBoundedRelu.hpp:134</a></div></div>
<div class="ttc" id="anamespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6ae1b3c9c6087a93b07c83e0b04f377a8d"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6ae1b3c9c6087a93b07c83e0b04f377a8d">armnn::DataType::Signed64</a></div><div class="ttdeci">@ Signed64</div></div>
<div class="ttc" id="aclassarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl_html_a43b1f24af6a51c0e749e200d1bbcf765"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html#a43b1f24af6a51c0e749e200d1bbcf765">armnn::optimizations::MaxMinIntoBoundedReluImpl::~MaxMinIntoBoundedReluImpl</a></div><div class="ttdeci">~MaxMinIntoBoundedReluImpl()=default</div></div>
<div class="ttc" id="aclassarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00030">Graph.hpp:30</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_graph_html_a3ff30c6669fdc69de1f5be1f89bacc3f"><div class="ttname"><a href="classarmnn_1_1_graph.html#a3ff30c6669fdc69de1f5be1f89bacc3f">armnn::Graph::InsertNewLayer</a></div><div class="ttdeci">LayerT * InsertNewLayer(InputSlot &amp;insertBefore, Args &amp;&amp;... args)</div><div class="ttdoc">Inserts a new layer between the output slot currently connected to insertBefore and insertBefore itse...</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00481">Graph.hpp:481</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</a></div><div class="ttdeci">@ Constant</div></div>
<div class="ttc" id="aclassarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl_html_ab8beb4d0cfc5c103045f261ff726b08e"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_max_min_into_bounded_relu_impl.html#ab8beb4d0cfc5c103045f261ff726b08e">armnn::optimizations::MaxMinIntoBoundedReluImpl::Run</a></div><div class="ttdeci">static void Run(Graph &amp;graph, InputSlot &amp;connection)</div><div class="ttdoc">Run for every exclusive connection between any Max &amp; Min layers The Max, Min and its associated const...</div><div class="ttdef"><b>Definition:</b> <a href="_max_min_into_bounded_relu_8hpp_source.html#l00018">MaxMinIntoBoundedRelu.hpp:18</a></div></div>
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