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<div class="title">AddBroadcastReshapeLayer.hpp</div> </div>
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<a href="_add_broadcast_reshape_layer_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 © 2020-2021,2023-2024 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;<span class="preprocessor">#pragma once</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160; </div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</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="l00008"></a><span class="lineno"> 8</span>&#160; </div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_tensor_handle_8hpp.html">armnn/backends/TensorHandle.hpp</a>&gt;</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_polymorphic_downcast_8hpp.html">armnn/utility/PolymorphicDowncast.hpp</a>&gt;</span></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;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;{</div>
<div class="line"><a name="l00014"></a><span class="lineno"><a class="line" href="namespacearmnn_1_1optimizations.html"> 14</a></span>&#160;<span class="keyword">namespace </span>optimizations</div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;{</div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160; </div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="keyword">static</span> <span class="keyword">const</span> std::set&lt;armnn::LayerType&gt; broadcastOps{ <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">LayerType::Addition</a>, <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a3025cdaab2deb0bb2cd642449e570833">LayerType::Division</a>,</div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a8321e79c278ec510f63675c040594892">LayerType::Maximum</a>, <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa1d0ec6d56f8833a078b5a7ac4caf2d4">LayerType::Minimum</a>,</div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a27d1a1f7b7c2180e5b20ce9e3d00e2dd">LayerType::Multiplication</a>, <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32">LayerType::Prelu</a>,</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a6eb8b8b560161603402c0238b3a7d8b0">LayerType::Subtraction</a>, <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a699bcffd93aff3022014b9efc9eaefd1">LayerType::ElementwiseBinary</a>,</div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af6c0e3a1c3cfabd32ae8d3ae741fcf0a">LayerType::Comparison</a>, <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af4f53c8297dc1cb53d4e6f8151070a30">LayerType::LogicalBinary</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"><a class="line" href="classarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl.html"> 23</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl.html">AddBroadcastReshapeLayerImpl</a></div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;{</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;<span class="keyword">public</span>:<span class="comment"></span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="comment"> /// Run for every ElementwiseBaseLayer. Add Broadcast reshape layer if the inputs shape are different.</span></div>
<div class="line"><a name="l00027"></a><span class="lineno"><a class="line" href="classarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl.html#aaa2a4663cec52a8aa89a93c7c8317183"> 27</a></span>&#160;<span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl.html#aaa2a4663cec52a8aa89a93c7c8317183">Run</a>(<a class="code" href="classarmnn_1_1_graph.html">Graph</a>&amp; graph, <a class="code" href="classarmnn_1_1_layer.html">Layer</a>&amp; layer)<span class="keyword"> const</span></div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="keyword"> </span>{</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <span class="keywordflow">if</span> (std::find(broadcastOps.begin(), broadcastOps.end(), layer.<a class="code" href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>()) != broadcastOps.end())</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; layer.<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">GetConnectedOutputSlot</a>()-&gt;<a class="code" href="classarmnn_1_1_output_slot.html#ac51cbac15935434659c8504d6db54e28">IsTensorInfoSet</a>();</div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; layer.<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">GetConnectedOutputSlot</a>()-&gt;<a class="code" href="classarmnn_1_1_output_slot.html#ac51cbac15935434659c8504d6db54e28">IsTensorInfoSet</a>();</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; inputInfo0 = layer.<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">GetConnectedOutputSlot</a>()-&gt;<a class="code" href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>&amp; inputInfo1 = layer.<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.html#a9effd325a6d512a3f8ff4bd207d53255">GetConnectedOutputSlot</a>()-&gt;<a class="code" href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>();</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; </div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="keywordflow">if</span> (inputInfo0.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() == inputInfo1.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>())</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="keywordflow">return</span>;</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; }</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; </div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> reshapeSlot = 1;</div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> reshapeInfo = inputInfo1;</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputInfo = inputInfo0;</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; </div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="keywordflow">if</span> (inputInfo0.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() &lt; inputInfo1.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>())</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; reshapeSlot = 0;</div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; reshapeInfo = inputInfo0;</div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; inputInfo = inputInfo1;</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; }</div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; </div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; uint32_t numDimensions = inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; </div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; std::vector&lt;unsigned&gt; reshapedDim;</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; reshapeInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; {</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; reshapedDim.push_back(reshapeInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[i]);</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; }</div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; </div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160; std::vector&lt;unsigned int&gt; reshapedDimensions(numDimensions, 1);</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; std::copy_backward(reshapedDim.begin(), reshapedDim.end(), reshapedDimensions.end());</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; </div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; reshapeInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">SetShape</a>(<a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a>{ numDimensions, reshapedDimensions.data() });</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; </div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="comment">// If the parent layer is a Constant layer and it is only used once we can short circuit by just</span></div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="comment">// changing the tensor info rather than adding a reshape layer.</span></div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <a class="code" href="classarmnn_1_1_layer.html">Layer</a>&amp; parentLayer = layer.<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(reshapeSlot).<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="l00069"></a><span class="lineno"> 69</span>&#160; <span class="keywordflow">if</span> ((parentLayer.<a class="code" href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</a>) &amp;&amp;</div>
<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; (parentLayer.<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.html#a25b0119c02aece1d341b99953d169c0f">GetNumConnections</a>() == 1))</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; <a class="code" href="classarmnn_1_1_constant_layer.html">ConstantLayer</a>&amp; constantLayer = <span class="keyword">static_cast&lt;</span><a class="code" href="classarmnn_1_1_constant_layer.html">ConstantLayer</a>&amp;<span class="keyword">&gt;</span>(parentLayer);</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; </div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; constantLayer.<a class="code" href="classarmnn_1_1_constant_layer.html#ad0c4b8ee0efd8f9336571cbeab8a53fe">m_LayerOutput</a> = std::make_unique&lt;ScopedTensorHandle&gt;(</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a>(reshapeInfo, constantLayer.<a class="code" href="classarmnn_1_1_constant_layer.html#ad0c4b8ee0efd8f9336571cbeab8a53fe">m_LayerOutput</a>.get()-&gt;GetConstTensor&lt;<span class="keywordtype">void</span>&gt;()));</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; constantLayer.<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(reshapeInfo);</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="keywordflow">else</span></div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; {</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="keyword">const</span> std::string layerName = <span class="stringliteral">&quot;Reshape_for:&quot;</span> + layer.<a class="code" href="classarmnn_1_1_layer.html#a9a97cb6d32661a57fc33bd29b8e41ff4">GetNameStr</a>() + <span class="stringliteral">&quot;-&quot;</span> + std::to_string(reshapeSlot);</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_reshape_descriptor.html">ReshapeDescriptor</a> descriptor{ reshapeInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>() };</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <a class="code" href="classarmnn_1_1_reshape_layer.html">ReshapeLayer</a>* reshapeLayer =</div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; graph.<a class="code" href="classarmnn_1_1_graph.html#a3ff30c6669fdc69de1f5be1f89bacc3f">InsertNewLayer</a>&lt;<a class="code" href="classarmnn_1_1_reshape_layer.html">ReshapeLayer</a>&gt;(layer.<a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(reshapeSlot), descriptor, layerName.c_str());</div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; reshapeLayer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(reshapeInfo);</div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; }</div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; }</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; }</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; </div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160;<span class="keyword">protected</span>:</div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <a class="code" href="classarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl.html#affc14705fa8863941b09b4df2169165d">AddBroadcastReshapeLayerImpl</a>() = <span class="keywordflow">default</span>;</div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <a class="code" href="classarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl.html#a926b9b2f21335752bc1cad1a2a413b5f">~AddBroadcastReshapeLayerImpl</a>() = <span class="keywordflow">default</span>;</div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160;};</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; </div>
<div class="line"><a name="l00094"></a><span class="lineno"><a class="line" href="namespacearmnn_1_1optimizations.html#a4fc55afb4885278ad1510b2c4307af76"> 94</a></span>&#160;<span class="keyword">using</span> <a class="code" href="classarmnn_1_1_optimize_for_type.html">AddBroadcastReshapeLayer</a> = <a class="code" href="classarmnn_1_1_optimize_for_type.html">OptimizeForType&lt;Layer, AddBroadcastReshapeLayerImpl&gt;</a>;</div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; </div>
<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160;} <span class="comment">// namespace optimizations</span></div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160;} <span class="comment">// namespace armnn</span></div>
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<div class="ttc" id="aclassarmnn_1_1_output_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00100">Layer.cpp:100</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_output_slot_html_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &amp;tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00095">Layer.cpp:95</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4af6c0e3a1c3cfabd32ae8d3ae741fcf0a"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af6c0e3a1c3cfabd32ae8d3ae741fcf0a">armnn::LayerType::Comparison</a></div><div class="ttdeci">@ Comparison</div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00197">Tensor.hpp:197</a></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="a_optimization_8hpp_html"><div class="ttname"><a href="_optimization_8hpp.html">Optimization.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">armnn::Layer::GetInputSlot</a></div><div class="ttdeci">const InputSlot &amp; GetInputSlot(unsigned int index) const override</div><div class="ttdoc">Get a const input slot handle by slot index.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00337">Layer.hpp:337</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_output_slot_html_ac51cbac15935434659c8504d6db54e28"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#ac51cbac15935434659c8504d6db54e28">armnn::OutputSlot::IsTensorInfoSet</a></div><div class="ttdeci">bool IsTensorInfoSet() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00105">Layer.cpp:105</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a699bcffd93aff3022014b9efc9eaefd1"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a699bcffd93aff3022014b9efc9eaefd1">armnn::LayerType::ElementwiseBinary</a></div><div class="ttdeci">@ ElementwiseBinary</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="aclassarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></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="aclassarmnn_1_1_reshape_layer_html"><div class="ttname"><a href="classarmnn_1_1_reshape_layer.html">armnn::ReshapeLayer</a></div><div class="ttdoc">This layer represents a reshape operation.</div><div class="ttdef"><b>Definition:</b> <a href="_reshape_layer_8hpp_source.html#l00015">ReshapeLayer.hpp:15</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a6eb8b8b560161603402c0238b3a7d8b0"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a6eb8b8b560161603402c0238b3a7d8b0">armnn::LayerType::Subtraction</a></div><div class="ttdeci">@ Subtraction</div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32">armnn::LayerType::Prelu</a></div><div class="ttdeci">@ Prelu</div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4af4f53c8297dc1cb53d4e6f8151070a30"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4af4f53c8297dc1cb53d4e6f8151070a30">armnn::LayerType::LogicalBinary</a></div><div class="ttdeci">@ LogicalBinary</div></div>
<div class="ttc" id="aclassarmnn_1_1_output_slot_html_a25b0119c02aece1d341b99953d169c0f"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#a25b0119c02aece1d341b99953d169c0f">armnn::OutputSlot::GetNumConnections</a></div><div class="ttdeci">unsigned int GetNumConnections() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00158">Layer.hpp:158</a></div></div>
<div class="ttc" id="a_polymorphic_downcast_8hpp_html"><div class="ttname"><a href="_polymorphic_downcast_8hpp.html">PolymorphicDowncast.hpp</a></div></div>
<div class="ttc" id="astructarmnn_1_1_reshape_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_reshape_descriptor.html">armnn::ReshapeDescriptor</a></div><div class="ttdoc">A ReshapeDescriptor for the ReshapeLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l01023">Descriptors.hpp:1023</a></div></div>
<div class="ttc" id="aclassarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl_html_affc14705fa8863941b09b4df2169165d"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl.html#affc14705fa8863941b09b4df2169165d">armnn::optimizations::AddBroadcastReshapeLayerImpl::AddBroadcastReshapeLayerImpl</a></div><div class="ttdeci">AddBroadcastReshapeLayerImpl()=default</div></div>
<div class="ttc" id="aclassarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl_html_a926b9b2f21335752bc1cad1a2a413b5f"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl.html#a926b9b2f21335752bc1cad1a2a413b5f">armnn::optimizations::AddBroadcastReshapeLayerImpl::~AddBroadcastReshapeLayerImpl</a></div><div class="ttdeci">~AddBroadcastReshapeLayerImpl()=default</div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a27d1a1f7b7c2180e5b20ce9e3d00e2dd"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a27d1a1f7b7c2180e5b20ce9e3d00e2dd">armnn::LayerType::Multiplication</a></div><div class="ttdeci">@ Multiplication</div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">armnn::LayerType::Addition</a></div><div class="ttdeci">@ Addition</div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html_a9a97cb6d32661a57fc33bd29b8e41ff4"><div class="ttname"><a href="classarmnn_1_1_layer.html#a9a97cb6d32661a57fc33bd29b8e41ff4">armnn::Layer::GetNameStr</a></div><div class="ttdeci">const std::string &amp; GetNameStr() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00240">Layer.hpp:240</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a3025cdaab2deb0bb2cd642449e570833"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a3025cdaab2deb0bb2cd642449e570833">armnn::LayerType::Division</a></div><div class="ttdeci">@ Division</div></div>
<div class="ttc" id="aclassarmnn_1_1_optimize_for_type_html"><div class="ttname"><a href="classarmnn_1_1_optimize_for_type.html">armnn::OptimizeForType</a></div><div class="ttdef"><b>Definition:</b> <a href="_optimization_8hpp_source.html#l00067">Optimization.hpp:67</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html_ad8e15c530c929ab823d89ae9fd2d3f11"><div class="ttname"><a href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const override</div><div class="ttdoc">Returns the armnn::LayerType of this layer.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00286">Layer.hpp:286</a></div></div>
<div class="ttc" id="a_tensor_handle_8hpp_html"><div class="ttname"><a href="_tensor_handle_8hpp.html">TensorHandle.hpp</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape &amp; GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00193">Tensor.hpp:193</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_constant_layer_html_ad0c4b8ee0efd8f9336571cbeab8a53fe"><div class="ttname"><a href="classarmnn_1_1_constant_layer.html#ad0c4b8ee0efd8f9336571cbeab8a53fe">armnn::ConstantLayer::m_LayerOutput</a></div><div class="ttdeci">std::shared_ptr&lt; ConstTensorHandle &gt; m_LayerOutput</div><div class="ttdef"><b>Definition:</b> <a href="_constant_layer_8hpp_source.html#l00046">ConstantLayer.hpp:46</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aa1d0ec6d56f8833a078b5a7ac4caf2d4"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aa1d0ec6d56f8833a078b5a7ac4caf2d4">armnn::LayerType::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_1_constant_layer_html"><div class="ttname"><a href="classarmnn_1_1_constant_layer.html">armnn::ConstantLayer</a></div><div class="ttdoc">A layer that the constant data can be bound to.</div><div class="ttdef"><b>Definition:</b> <a href="_constant_layer_8hpp_source.html#l00015">ConstantLayer.hpp:15</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_info_html_abe8889e8150beef5fd204b2d87b49298"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#abe8889e8150beef5fd204b2d87b49298">armnn::TensorInfo::SetShape</a></div><div class="ttdeci">void SetShape(const TensorShape &amp;newShape)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00195">Tensor.hpp:195</a></div></div>
<div class="ttc" id="anamespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors.</div><div class="ttdef"><b>Definition:</b> <a href="01__00__quick__start_8dox_source.html#l00006">01_00_quick_start.dox:6</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00329">Tensor.hpp:329</a></div></div>
<div class="ttc" id="aclassarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl_html_aaa2a4663cec52a8aa89a93c7c8317183"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl.html#aaa2a4663cec52a8aa89a93c7c8317183">armnn::optimizations::AddBroadcastReshapeLayerImpl::Run</a></div><div class="ttdeci">void Run(Graph &amp;graph, Layer &amp;layer) const</div><div class="ttdoc">Run for every ElementwiseBaseLayer. Add Broadcast reshape layer if the inputs shape are different.</div><div class="ttdef"><b>Definition:</b> <a href="_add_broadcast_reshape_layer_8hpp_source.html#l00027">AddBroadcastReshapeLayer.hpp:27</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a8321e79c278ec510f63675c040594892"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a8321e79c278ec510f63675c040594892">armnn::LayerType::Maximum</a></div><div class="ttdeci">@ Maximum</div></div>
<div class="ttc" id="aclassarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl_html"><div class="ttname"><a href="classarmnn_1_1optimizations_1_1_add_broadcast_reshape_layer_impl.html">armnn::optimizations::AddBroadcastReshapeLayerImpl</a></div><div class="ttdef"><b>Definition:</b> <a href="_add_broadcast_reshape_layer_8hpp_source.html#l00023">AddBroadcastReshapeLayer.hpp:23</a></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>
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