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<div class="title">ElementwiseBaseLayer.cpp</div> </div>
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<a href="_elementwise_base_layer_8cpp.xhtml">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 © 2017 Arm Ltd. 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">#include &quot;<a class="code" href="_elementwise_base_layer_8hpp.xhtml">ElementwiseBaseLayer.hpp</a>&quot;</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="_internal_types_8hpp.xhtml">InternalTypes.hpp</a>&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_exceptions_8hpp.xhtml">armnn/Exceptions.hpp</a>&quot;</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_types_utils_8hpp.xhtml">armnn/TypesUtils.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="preprocessor">#include &lt;boost/assert.hpp&gt;</span></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"> 14</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></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"><a class="line" href="classarmnn_1_1_elementwise_base_layer.xhtml#a6aa67447c0f7d3aa62124c535e5b550b"> 17</a></span>&#160;<a class="code" href="classarmnn_1_1_elementwise_base_layer.xhtml#a6aa67447c0f7d3aa62124c535e5b550b">ElementwiseBaseLayer::ElementwiseBaseLayer</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputSlots, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numOutputSlots,</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a> type, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; : <a class="code" href="classarmnn_1_1_layer.xhtml">Layer</a>(numInputSlots, numOutputSlots, type, name)</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;{</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;}</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_1_elementwise_base_layer.xhtml#a65ca562c882ad619684445a1402f415a"> 23</a></span>&#160;std::vector&lt;TensorShape&gt; <a class="code" href="classarmnn_1_1_elementwise_base_layer.xhtml#a65ca562c882ad619684445a1402f415a">ElementwiseBaseLayer::InferOutputShapes</a>(<span class="keyword">const</span> std::vector&lt;TensorShape&gt;&amp; inputShapes)<span class="keyword"> const</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; BOOST_ASSERT(inputShapes.size() == 2);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; <span class="keyword">auto</span>&amp; input0 = inputShapes[0];</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; <span class="keyword">auto</span>&amp; input1 = inputShapes[1];</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <span class="comment">// Get the max of the inputs.</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; BOOST_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions());</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDims = input0.GetNumDimensions();</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; std::vector&lt;unsigned int&gt; dims(numDims);</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">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; numDims; i++)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> dim0 = input0[i];</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dim1 = input1[i];</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="preprocessor">#if !NDEBUG</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="comment">// Validate inputs are broadcast compatible.</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; BOOST_ASSERT_MSG(dim0 == dim1 || dim0 == 1 || dim1 == 1,</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="stringliteral">&quot;Dimensions should either match or one should be of size 1.&quot;</span>);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;<span class="preprocessor">#endif</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; dims[i] = std::max(dim0, dim1);</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; }</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> std::vector&lt;TensorShape&gt;({ <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(numDims, dims.data()) });</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"><a class="line" href="classarmnn_1_1_elementwise_base_layer.xhtml#a8c8f543d7e9729362c266d12ec169966"> 51</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_elementwise_base_layer.xhtml#a8c8f543d7e9729362c266d12ec169966">ElementwiseBaseLayer::ValidateTensorShapesFromInputs</a>()</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; <a class="code" href="classarmnn_1_1_layer.xhtml#a0607e36e88f38c34c71c663164b76776">VerifyLayerConnections</a>(2, <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</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; <span class="keyword">auto</span> inferredShapes = <a class="code" href="classarmnn_1_1_elementwise_base_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>({</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-&gt;<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <a class="code" href="classarmnn_1_1_layer.xhtml#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-&gt;<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; });</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; BOOST_ASSERT(inferredShapes.size() == 1);</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; std::string msg = <a class="code" href="namespacearmnn.xhtml#a9da573d7a1fc03726fd41f2130cbcf92">GetLayerTypeAsCString</a>(<a class="code" href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">GetType</a>());</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; msg += <span class="stringliteral">&quot;Layer: TensorShape set on OutputSlot[0] does not match the inferred shape.&quot;</span>;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; ConditionalThrowIfNotEqual&lt;LayerValidationException&gt;(msg,</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.xhtml#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; inferredShapes[0]);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160;}</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160;} <span class="comment">// namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#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.xhtml#l00088">Tensor.hpp:88</a></div></div>
<div class="ttc" id="classarmnn_1_1_elementwise_base_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_elementwise_base_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::ElementwiseBaseLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector&lt; TensorShape &gt; InferOutputShapes(const std::vector&lt; TensorShape &gt; &amp;inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_base_layer_8cpp_source.xhtml#l00023">ElementwiseBaseLayer.cpp:23</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="classarmnn_1_1_input_slot_xhtml_a3153abb7c0c0a84629079b2fac7db54f"><div class="ttname"><a href="classarmnn_1_1_input_slot.xhtml#a3153abb7c0c0a84629079b2fac7db54f">armnn::InputSlot::GetConnection</a></div><div class="ttdeci">const IOutputSlot * GetConnection() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00199">Layer.hpp:199</a></div></div>
<div class="ttc" id="_internal_types_8hpp_xhtml"><div class="ttname"><a href="_internal_types_8hpp.xhtml">InternalTypes.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0607e36e88f38c34c71c663164b76776"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0607e36e88f38c34c71c663164b76776">armnn::Layer::VerifyLayerConnections</a></div><div class="ttdeci">void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &amp;location) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00338">Layer.cpp:338</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_acf8b8e23bf647836592982f97088d375"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#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.xhtml#l00310">Layer.hpp:310</a></div></div>
<div class="ttc" id="_types_utils_8hpp_xhtml"><div class="ttname"><a href="_types_utils_8hpp.xhtml">TypesUtils.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a9da573d7a1fc03726fd41f2130cbcf92"><div class="ttname"><a href="namespacearmnn.xhtml#a9da573d7a1fc03726fd41f2130cbcf92">armnn::GetLayerTypeAsCString</a></div><div class="ttdeci">char const * GetLayerTypeAsCString(LayerType type)</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8cpp_source.xhtml#l00013">InternalTypes.cpp:13</a></div></div>
<div class="ttc" id="_exceptions_8hpp_xhtml_aa3be76aec4ce713822a5ea1ecbb7bc61"><div class="ttname"><a href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a></div><div class="ttdeci">#define CHECK_LOCATION()</div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00192">Exceptions.hpp:192</a></div></div>
<div class="ttc" id="classarmnn_1_1_elementwise_base_layer_xhtml_a6aa67447c0f7d3aa62124c535e5b550b"><div class="ttname"><a href="classarmnn_1_1_elementwise_base_layer.xhtml#a6aa67447c0f7d3aa62124c535e5b550b">armnn::ElementwiseBaseLayer::ElementwiseBaseLayer</a></div><div class="ttdeci">ElementwiseBaseLayer(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)</div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_base_layer_8cpp_source.xhtml#l00017">ElementwiseBaseLayer.cpp:17</a></div></div>
<div class="ttc" id="_exceptions_8hpp_xhtml"><div class="ttname"><a href="_exceptions_8hpp.xhtml">Exceptions.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_aaef29472862381822654ab6cbf7cba2a"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#aaef29472862381822654ab6cbf7cba2a">armnn::Layer::GetType</a></div><div class="ttdeci">LayerType GetType() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00259">Layer.hpp:259</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#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.xhtml#l00312">Layer.hpp:312</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a9943775a364fc4ab53b85ac88f311886"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a9943775a364fc4ab53b85ac88f311886">armnn::IOutputSlot::GetTensorInfo</a></div><div class="ttdeci">virtual const TensorInfo &amp; GetTensorInfo() const =0</div></div>
<div class="ttc" id="_elementwise_base_layer_8hpp_xhtml"><div class="ttname"><a href="_elementwise_base_layer_8hpp.xhtml">ElementwiseBaseLayer.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#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.xhtml#l00063">Layer.cpp:63</a></div></div>
<div class="ttc" id="classarmnn_1_1_elementwise_base_layer_xhtml_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_elementwise_base_layer.xhtml#a8c8f543d7e9729362c266d12ec169966">armnn::ElementwiseBaseLayer::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 the element wise operation...</div><div class="ttdef"><b>Definition:</b> <a href="_elementwise_base_layer_8cpp_source.xhtml#l00051">ElementwiseBaseLayer.cpp:51</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00209">Layer.hpp:209</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8hpp_source.xhtml#l00014">InternalTypes.hpp:14</a></div></div>
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