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<div class="title">ElementwiseBinaryLayer.cpp</div> </div>
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<a href="_elementwise_binary_layer_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span>  </div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_elementwise_binary_layer_8hpp.html">ElementwiseBinaryLayer.hpp</a>"</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span>  </div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_layer_clone_base_8hpp.html">LayerCloneBase.hpp</a>"</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span>  </div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> {</div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span>  </div>
<div class="line"><a name="l00013"></a><span class="lineno"><a class="line" href="classarmnn_1_1_elementwise_binary_layer.html#aa345377aa7ae6160626f84002cef78ff"> 13</a></span> <a class="code" href="classarmnn_1_1_elementwise_binary_layer.html#aa345377aa7ae6160626f84002cef78ff">ElementwiseBinaryLayer::ElementwiseBinaryLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_elementwise_binary_descriptor.html">ElementwiseBinaryDescriptor</a>& param, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span>  : <a class="code" href="classarmnn_1_1_layer_with_parameters.html">LayerWithParameters</a>(2, 1, <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>::<a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a699bcffd93aff3022014b9efc9eaefd1">ElementwiseBinary</a>, param, name)</div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> {</div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> }</div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  </div>
<div class="line"><a name="l00018"></a><span class="lineno"><a class="line" href="classarmnn_1_1_elementwise_binary_layer.html#adfa912d0c4c6c00f1af2cbfa799572b7"> 18</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_elementwise_binary_layer.html#adfa912d0c4c6c00f1af2cbfa799572b7">ElementwiseBinaryLayer::CreateWorkload</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_workload_factory.html">IWorkloadFactory</a>& factory)<span class="keyword"> const</span></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <a class="code" href="structarmnn_1_1_elementwise_binary_queue_descriptor.html">ElementwiseBinaryQueueDescriptor</a> descriptor;</div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="classarmnn_1_1_layer.html#af7f0460d32511de0da525f1817d13e8c">SetAdditionalInfo</a>(descriptor);</div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  </div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keywordflow">return</span> factory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a694a8411c8c799da95306034d274930b">CreateWorkload</a>(<a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a699bcffd93aff3022014b9efc9eaefd1">LayerType::ElementwiseBinary</a>, descriptor, <a class="code" href="classarmnn_1_1_layer_with_parameters.html#a30a858b2b26d651a066537e499fbf40d">PrepInfoAndDesc</a>(descriptor));</div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span> }</div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  </div>
<div class="line"><a name="l00026"></a><span class="lineno"><a class="line" href="classarmnn_1_1_elementwise_binary_layer.html#ad85d0f53bc6a30fba7ddc37614e2e7ab"> 26</a></span> <a class="code" href="classarmnn_1_1_elementwise_binary_layer.html">ElementwiseBinaryLayer</a>* <a class="code" href="classarmnn_1_1_elementwise_binary_layer.html#ad85d0f53bc6a30fba7ddc37614e2e7ab">ElementwiseBinaryLayer::Clone</a>(<a class="code" href="classarmnn_1_1_graph.html">Graph</a>& graph)<span class="keyword"> const</span></div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keywordflow">return</span> CloneBase<ElementwiseBinaryLayer>(graph, <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>, <a class="code" href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> }</div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  </div>
<div class="line"><a name="l00031"></a><span class="lineno"><a class="line" href="classarmnn_1_1_elementwise_binary_layer.html#a65ca562c882ad619684445a1402f415a"> 31</a></span> std::vector<TensorShape> <a class="code" href="classarmnn_1_1_elementwise_binary_layer.html#a65ca562c882ad619684445a1402f415a">ElementwiseBinaryLayer::InferOutputShapes</a>(<span class="keyword">const</span> std::vector<TensorShape>& inputShapes)<span class="keyword"> const</span></div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <a class="code" href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(inputShapes.size() == 2);</div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> input0 = inputShapes[0];</div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> input1 = inputShapes[1];</div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  </div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordflow">if</span> (inputShapes[0].GetNumDimensions() < inputShapes[1].GetNumDimensions())</div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  {</div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  input1 = inputShapes[0];</div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  input0 = inputShapes[1];</div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  }</div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  </div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDims = input0.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shiftedDims = input0.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() - input1.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  </div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="comment">// Get the max of the inputs.</span></div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  std::vector<unsigned int> dims(numDims);</div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = shiftedDims; i < numDims; i++)</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dim0 = input0[i];</div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dim1 = input1[i - shiftedDims];</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>  <span class="comment">// Validate inputs are broadcast compatible.</span></div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="_assert_8hpp.html#a91c4dfde57907d7698c7531785690a7f">ARMNN_ASSERT_MSG</a>(dim0 == dim1 || dim0 == 1 || dim1 == 1,</div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="stringliteral">"Dimensions should either match or one should be of size 1."</span>);</div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  </div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  dims[i] = std::max(dim0, dim1);</div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  }</div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  </div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="comment">// Fill in the rest of the shifted dimensions.</span></div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < shiftedDims; i++)</div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  {</div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  dims[i] = input0[i];</div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  }</div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  </div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordflow">return</span> std::vector<TensorShape>({ <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>(numDims, dims.data()) });</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span> }</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  </div>
<div class="line"><a name="l00069"></a><span class="lineno"><a class="line" href="classarmnn_1_1_elementwise_binary_layer.html#a8c8f543d7e9729362c266d12ec169966"> 69</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_elementwise_binary_layer.html#a8c8f543d7e9729362c266d12ec169966">ElementwiseBinaryLayer::ValidateTensorShapesFromInputs</a>()</div>
<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>  <a class="code" href="classarmnn_1_1_layer.html#a0607e36e88f38c34c71c663164b76776">VerifyLayerConnections</a>(2, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  </div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& outputShape = <a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  </div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="classarmnn_1_1_layer.html#a448afc716fda85394df1e8e5b7d530e8">VerifyShapeInferenceType</a>(outputShape, <a class="code" href="classarmnn_1_1_layer.html#afe508761cc8318b15329ba4acf7fbfec">m_ShapeInferenceMethod</a>);</div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  </div>
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">auto</span> inferredShapes = <a class="code" href="classarmnn_1_1_elementwise_binary_layer.html#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>({ <a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>() });</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  </div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(inferredShapes.size() == 1);</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>  <a class="code" href="classarmnn_1_1_layer.html#aeb2d638cc0e02c10075e015100996f2d">ValidateAndCopyShape</a>(outputShape, inferredShapes[0], <a class="code" href="classarmnn_1_1_layer.html#afe508761cc8318b15329ba4acf7fbfec">m_ShapeInferenceMethod</a>, <a class="code" href="namespacearmnn.html#addb6b14dd1b632263ffe77430259a7c4">GetLayerTypeAsCString</a>(<a class="code" href="classarmnn_1_1_layer.html#ad8e15c530c929ab823d89ae9fd2d3f11">GetType</a>()));</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>  </div>
<div class="line"><a name="l00085"></a><span class="lineno"><a class="line" href="classarmnn_1_1_elementwise_binary_layer.html#a46fc3fdd4b2a5dd6d184e57983cf20bc"> 85</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_elementwise_binary_layer.html#a46fc3fdd4b2a5dd6d184e57983cf20bc">ElementwiseBinaryLayer::ExecuteStrategy</a>(<a class="code" href="classarmnn_1_1_i_strategy.html">IStrategy</a>& strategy)<span class="keyword"> const</span></div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="keyword"></span>{</div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  strategy.<a class="code" href="classarmnn_1_1_i_strategy.html#ad4f8c9ff973cf6a603d26b56c5b34967">ExecuteStrategy</a>(<span class="keyword">this</span>, <a class="code" href="classarmnn_1_1_layer_with_parameters.html#afa3e8a8f23589b1eaddbe203825bbdcf">GetParameters</a>(), {}, <a class="code" href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span> }</div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span> } <span class="comment">// namespace armnn</span></div>
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<div class="ttc" id="a_assert_8hpp_html_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.html#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.html#l00014">Assert.hpp:14</a></div></div>
<div class="ttc" id="a_elementwise_binary_layer_8hpp_html"><div class="ttname"><a href="_elementwise_binary_layer_8hpp.html">ElementwiseBinaryLayer.hpp</a></div></div>
<div class="ttc" id="anamespacearmnn_html_addb6b14dd1b632263ffe77430259a7c4"><div class="ttname"><a href="namespacearmnn.html#addb6b14dd1b632263ffe77430259a7c4">armnn::GetLayerTypeAsCString</a></div><div class="ttdeci">const char * GetLayerTypeAsCString(LayerType type)</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8cpp_source.html#l00013">InternalTypes.cpp:13</a></div></div>
<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 & GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00092">Layer.cpp:92</a></div></div>
<div class="ttc" id="a_exceptions_8hpp_html_aa3be76aec4ce713822a5ea1ecbb7bc61"><div class="ttname"><a href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a></div><div class="ttdeci">#define CHECK_LOCATION()</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.html#l00203">Exceptions.hpp:203</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html_aeb2d638cc0e02c10075e015100996f2d"><div class="ttname"><a href="classarmnn_1_1_layer.html#aeb2d638cc0e02c10075e015100996f2d">armnn::Layer::ValidateAndCopyShape</a></div><div class="ttdeci">void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00435">Layer.cpp:435</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 & 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="aclassarmnn_1_1_elementwise_binary_layer_html_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_elementwise_binary_layer.html#a65ca562c882ad619684445a1402f415a">armnn::ElementwiseBinaryLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">Returns inputShapes by default.</div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_binary_layer_8cpp_source.html#l00031">ElementwiseBinaryLayer.cpp:31</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_i_strategy_html"><div class="ttname"><a href="classarmnn_1_1_i_strategy.html">armnn::IStrategy</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_strategy_8hpp_source.html#l00016">IStrategy.hpp:16</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_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 & 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_layer_with_parameters_html_afa3e8a8f23589b1eaddbe203825bbdcf"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#afa3e8a8f23589b1eaddbe203825bbdcf">armnn::LayerWithParameters< ElementwiseBinaryDescriptor >::GetParameters</a></div><div class="ttdeci">const ElementwiseBinaryDescriptor & GetParameters() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00019">LayerWithParameters.hpp:19</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_with_parameters_html"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html">armnn::LayerWithParameters</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00014">LayerWithParameters.hpp:14</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html_a7ddf0cf6f620d59c10e63495ace795d0"><div class="ttname"><a href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">armnn::Layer::GetName</a></div><div class="ttdeci">const char * GetName() const override</div><div class="ttdoc">Returns the name of the layer.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00332">Layer.hpp:332</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_input_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::InputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo() const override</div><div class="ttdoc">Gets the TensorInfo for this InputSlot.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00592">Layer.cpp:592</a></div></div>
<div class="ttc" id="astructarmnn_1_1_elementwise_binary_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_elementwise_binary_descriptor.html">armnn::ElementwiseBinaryDescriptor</a></div><div class="ttdoc">A ElementwiseBinaryDescriptor for the ElementwiseBinaryLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00109">Descriptors.hpp:109</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="astructarmnn_1_1_elementwise_binary_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_elementwise_binary_queue_descriptor.html">armnn::ElementwiseBinaryQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00671">WorkloadData.hpp:671</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_with_parameters_html_ad32ac22bc72e28dfd6b466d143c8e262"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">armnn::LayerWithParameters< ElementwiseBinaryDescriptor >::m_Param</a></div><div class="ttdeci">ElementwiseBinaryDescriptor m_Param</div><div class="ttdoc">The parameters for the layer (not including tensor-valued weights etc.).</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00052">LayerWithParameters.hpp:52</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_elementwise_binary_layer_html_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_elementwise_binary_layer.html#a8c8f543d7e9729362c266d12ec169966">armnn::ElementwiseBinaryLayer::ValidateTensorShapesFromInputs</a></div><div class="ttdeci">void ValidateTensorShapesFromInputs() override</div><div class="ttdoc">Check if the input tensor shape(s) will lead to a valid configuration of ElementwiseBinaryLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_binary_layer_8cpp_source.html#l00069">ElementwiseBinaryLayer.cpp:69</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_tensor_shape_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorShape::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdoc">Function that returns the tensor rank.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.html#l00174">Tensor.cpp:174</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_elementwise_binary_layer_html_ad85d0f53bc6a30fba7ddc37614e2e7ab"><div class="ttname"><a href="classarmnn_1_1_elementwise_binary_layer.html#ad85d0f53bc6a30fba7ddc37614e2e7ab">armnn::ElementwiseBinaryLayer::Clone</a></div><div class="ttdeci">ElementwiseBinaryLayer * Clone(Graph &graph) const override</div><div class="ttdoc">Creates a dynamically-allocated copy of this layer.</div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_binary_layer_8cpp_source.html#l00026">ElementwiseBinaryLayer.cpp:26</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_with_parameters_html_a30a858b2b26d651a066537e499fbf40d"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#a30a858b2b26d651a066537e499fbf40d">armnn::LayerWithParameters< ElementwiseBinaryDescriptor >::PrepInfoAndDesc</a></div><div class="ttdeci">WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const</div><div class="ttdoc">Helper function to reduce duplication in *Layer::CreateWorkload.</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00044">LayerWithParameters.hpp:44</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_elementwise_binary_layer_html_adfa912d0c4c6c00f1af2cbfa799572b7"><div class="ttname"><a href="classarmnn_1_1_elementwise_binary_layer.html#adfa912d0c4c6c00f1af2cbfa799572b7">armnn::ElementwiseBinaryLayer::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override</div><div class="ttdoc">Makes a workload for the elementwiseBinary type.</div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_binary_layer_8cpp_source.html#l00018">ElementwiseBinaryLayer.cpp:18</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_i_workload_factory_html"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.html#l00022">WorkloadFactory.hpp:22</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html_a448afc716fda85394df1e8e5b7d530e8"><div class="ttname"><a href="classarmnn_1_1_layer.html#a448afc716fda85394df1e8e5b7d530e8">armnn::Layer::VerifyShapeInferenceType</a></div><div class="ttdeci">void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00504">Layer.cpp:504</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html_af7f0460d32511de0da525f1817d13e8c"><div class="ttname"><a href="classarmnn_1_1_layer.html#af7f0460d32511de0da525f1817d13e8c">armnn::Layer::SetAdditionalInfo</a></div><div class="ttdeci">void SetAdditionalInfo(QueueDescriptor &descriptor) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00287">Layer.cpp:287</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_elementwise_binary_layer_html"><div class="ttname"><a href="classarmnn_1_1_elementwise_binary_layer.html">armnn::ElementwiseBinaryLayer</a></div><div class="ttdoc">This layer represents a elementwiseBinary operation.</div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_binary_layer_8hpp_source.html#l00014">ElementwiseBinaryLayer.hpp:14</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="aclassarmnn_1_1_elementwise_binary_layer_html_a46fc3fdd4b2a5dd6d184e57983cf20bc"><div class="ttname"><a href="classarmnn_1_1_elementwise_binary_layer.html#a46fc3fdd4b2a5dd6d184e57983cf20bc">armnn::ElementwiseBinaryLayer::ExecuteStrategy</a></div><div class="ttdeci">void ExecuteStrategy(IStrategy &strategy) const override</div><div class="ttdoc">Apply a visitor to this layer.</div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_binary_layer_8cpp_source.html#l00085">ElementwiseBinaryLayer.cpp:85</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 & 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="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_layer_html_a0607e36e88f38c34c71c663164b76776"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0607e36e88f38c34c71c663164b76776">armnn::Layer::VerifyLayerConnections</a></div><div class="ttdeci">void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00391">Layer.cpp:391</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_elementwise_binary_layer_html_aa345377aa7ae6160626f84002cef78ff"><div class="ttname"><a href="classarmnn_1_1_elementwise_binary_layer.html#aa345377aa7ae6160626f84002cef78ff">armnn::ElementwiseBinaryLayer::ElementwiseBinaryLayer</a></div><div class="ttdeci">ElementwiseBinaryLayer(const ElementwiseBinaryDescriptor &param, const char *name)</div><div class="ttdoc">Constructor to create a ElementwiseBinaryLayer.</div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_binary_layer_8cpp_source.html#l00013">ElementwiseBinaryLayer.cpp:13</a></div></div>
<div class="ttc" id="aclassarmnn_1_1_layer_html_afe508761cc8318b15329ba4acf7fbfec"><div class="ttname"><a href="classarmnn_1_1_layer.html#afe508761cc8318b15329ba4acf7fbfec">armnn::Layer::m_ShapeInferenceMethod</a></div><div class="ttdeci">ShapeInferenceMethod m_ShapeInferenceMethod</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00441">Layer.hpp:441</a></div></div>
<div class="ttc" id="anamespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdoc">When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below.</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00491">Types.hpp:491</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_i_workload_factory_html_a694a8411c8c799da95306034d274930b"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a694a8411c8c799da95306034d274930b">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const =0</div><div class="ttdoc">Backends should implement their own CreateWorkload function with a switch statement.</div></div>
<div class="ttc" id="aclassarmnn_1_1_i_strategy_html_ad4f8c9ff973cf6a603d26b56c5b34967"><div class="ttname"><a href="classarmnn_1_1_i_strategy.html#ad4f8c9ff973cf6a603d26b56c5b34967">armnn::IStrategy::ExecuteStrategy</a></div><div class="ttdeci">virtual void ExecuteStrategy(const IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0</div></div>
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