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  84 <div class="title">PreluLayer.cpp</div>  </div>
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  87 <a href="_prelu_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>&#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="_prelu_layer_8hpp.html">PreluLayer.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="_layer_clone_base_8hpp.html">LayerCloneBase.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="preprocessor">#include &lt;<a class="code" href="_workload_data_8hpp.html">backendsCommon/WorkloadData.hpp</a>&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_workload_factory_8hpp.html">backendsCommon/WorkloadFactory.hpp</a>&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_cpu_tensor_handle_8hpp.html">backendsCommon/CpuTensorHandle.hpp</a>&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.html">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_prelu_layer.html#ad3ae922a3829fa9cf40bd13bc211f40b">   17</a></span>&#160;<a class="code" href="classarmnn_1_1_prelu_layer.html#ad3ae922a3829fa9cf40bd13bc211f40b">PreluLayer::PreluLayer</a>(<span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;    : <a class="code" href="classarmnn_1_1_layer.html">Layer</a>(2, 1, <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>::<a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32">Prelu</a>, name)</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;</div><div class="line"><a name="l00021"></a><span class="lineno"><a class="line" href="classarmnn_1_1_prelu_layer.html#adfa912d0c4c6c00f1af2cbfa799572b7">   21</a></span>&#160;std::unique_ptr&lt;IWorkload&gt; <a class="code" href="classarmnn_1_1_prelu_layer.html#adfa912d0c4c6c00f1af2cbfa799572b7">PreluLayer::CreateWorkload</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_workload_factory.html">IWorkloadFactory</a>&amp; factory)<span class="keyword"> const</span></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;    <a class="code" href="structarmnn_1_1_prelu_queue_descriptor.html">PreluQueueDescriptor</a> descriptor;</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="keywordflow">return</span> factory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#adf4a93f605e4e7dad6aee0b4d2159171">CreatePrelu</a>(descriptor, <a class="code" href="classarmnn_1_1_layer.html#a30a858b2b26d651a066537e499fbf40d">PrepInfoAndDesc</a>(descriptor));</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;}</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"><a class="line" href="classarmnn_1_1_prelu_layer.html#af5dd85c2adbf7e9f95d9c984157620a9">   28</a></span>&#160;<a class="code" href="classarmnn_1_1_prelu_layer.html">PreluLayer</a>* <a class="code" href="classarmnn_1_1_prelu_layer.html#af5dd85c2adbf7e9f95d9c984157620a9">PreluLayer::Clone</a>(<a class="code" href="classarmnn_1_1_graph.html">Graph</a>&amp; graph)<span class="keyword"> const</span></div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;    <span class="keyword">auto</span> layer = CloneBase&lt;PreluLayer&gt;(graph, <a class="code" href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    <span class="keywordflow">return</span> std::move(layer);</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;</div><div class="line"><a name="l00035"></a><span class="lineno"><a class="line" href="classarmnn_1_1_prelu_layer.html#a65ca562c882ad619684445a1402f415a">   35</a></span>&#160;std::vector&lt;TensorShape&gt; <a class="code" href="classarmnn_1_1_prelu_layer.html#a65ca562c882ad619684445a1402f415a">PreluLayer::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="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    BOOST_ASSERT(inputShapes.size() == 2);</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; inputShape = inputShapes[0];</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>&amp; alphaShape = inputShapes[1];</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="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShapeDimensions = inputShape.<a class="code" href="classarmnn_1_1_tensor_shape.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> alphaShapeDimensions = alphaShape.<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>&#160;</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    BOOST_ASSERT(inputShapeDimensions &gt; 0);</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    BOOST_ASSERT(alphaShapeDimensions &gt; 0);</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="comment">// The size of the output is the maximum size along each dimension of the input operands,</span></div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;    <span class="comment">// it starts with the trailing dimensions, and works its way forward</span></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="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputDimensions = std::max(inputShapeDimensions, alphaShapeDimensions);</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_tensor_shape.html">TensorShape</a> outputShape(outputDimensions);</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="keywordtype">int</span> inputShapeIndex = boost::numeric_cast&lt;<span class="keywordtype">int</span>&gt;(inputShapeDimensions) - 1;</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <span class="keywordtype">int</span> alphaShapeIndex = boost::numeric_cast&lt;<span class="keywordtype">int</span>&gt;(alphaShapeDimensions) - 1;</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShapeIndex = outputDimensions - 1;</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;    <span class="comment">// Loop backwards through the common part of the shapes</span></div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <span class="keywordflow">while</span> (inputShapeIndex &gt;= 0 &amp;&amp; alphaShapeIndex &gt;= 0)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputDimension = inputShape[boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(inputShapeIndex)];</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> alphaDimension = alphaShape[boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(alphaShapeIndex)];</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">// Check that the inputs are broadcast compatible</span></div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;        BOOST_ASSERT_MSG(inputDimension == alphaDimension || inputDimension == 1 || alphaDimension == 1,</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;                         <span class="stringliteral">&quot;PreluLayer: Dimensions should either match or one should be of size 1&quot;</span>);</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;        outputShape[outputShapeIndex] = std::max(inputDimension, alphaDimension);</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;        inputShapeIndex--;</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        alphaShapeIndex--;</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        outputShapeIndex--;</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;</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    <span class="comment">// Loop backwards through the remaing part of the input shape (if any)</span></div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    <span class="keywordflow">while</span> (inputShapeIndex &gt;= 0)</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    {</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;        outputShape[outputShapeIndex] = inputShape[boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(inputShapeIndex)];</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;        inputShapeIndex--;</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;        outputShapeIndex--;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    }</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    <span class="comment">// Loop backwards through the remaing part of the alpha shape (if any)</span></div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    <span class="keywordflow">while</span> (alphaShapeIndex &gt;= 0)</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;        outputShape[outputShapeIndex] = alphaShape[boost::numeric_cast&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(alphaShapeIndex)];</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;        alphaShapeIndex--;</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;        outputShapeIndex--;</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">   94</span>&#160;    <span class="keywordflow">return</span> { outputShape };</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;</div><div class="line"><a name="l00097"></a><span class="lineno"><a class="line" href="classarmnn_1_1_prelu_layer.html#a8c8f543d7e9729362c266d12ec169966">   97</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_prelu_layer.html#a8c8f543d7e9729362c266d12ec169966">PreluLayer::ValidateTensorShapesFromInputs</a>()</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;{</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;    <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="l00100"></a><span class="lineno">  100</span>&#160;</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    std::vector&lt;TensorShape&gt; inferredShapes = <a class="code" href="classarmnn_1_1_prelu_layer.html#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(</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;        <a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(0).<a class="code" href="classarmnn_1_1_input_slot.html#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-&gt;<a class="code" href="classarmnn_1_1_i_output_slot.html#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;        <a class="code" href="classarmnn_1_1_layer.html#acf8b8e23bf647836592982f97088d375">GetInputSlot</a>(1).<a class="code" href="classarmnn_1_1_input_slot.html#a3153abb7c0c0a84629079b2fac7db54f">GetConnection</a>()-&gt;<a class="code" href="classarmnn_1_1_i_output_slot.html#a9943775a364fc4ab53b85ac88f311886">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()</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;</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    BOOST_ASSERT(inferredShapes.size() == 1);</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    ConditionalThrowIfNotEqual&lt;LayerValidationException&gt;(</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;        <span class="stringliteral">&quot;PreluLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.&quot;</span>,</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;        <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="l00112"></a><span class="lineno">  112</span>&#160;        inferredShapes[0]);</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;</div><div class="line"><a name="l00115"></a><span class="lineno"><a class="line" href="classarmnn_1_1_prelu_layer.html#a75a50f464326fefa605ea84ae2c9be85">  115</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_prelu_layer.html#a75a50f464326fefa605ea84ae2c9be85">PreluLayer::Accept</a>(<a class="code" href="classarmnn_1_1_i_layer_visitor.html">ILayerVisitor</a>&amp; visitor)<span class="keyword"> const</span></div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    visitor.<a class="code" href="classarmnn_1_1_i_layer_visitor.html#a4f6971a5d2c164c691dc7943f4befd5c">VisitPreluLayer</a>(<span class="keyword">this</span>, <a class="code" href="classarmnn_1_1_layer.html#a7ddf0cf6f620d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  88 <div class="ttc" id="_workload_factory_8hpp_html"><div class="ttname"><a href="_workload_factory_8hpp.html">WorkloadFactory.hpp</a></div></div>
  89 <div class="ttc" id="classarmnn_1_1_prelu_layer_html"><div class="ttname"><a href="classarmnn_1_1_prelu_layer.html">armnn::PreluLayer</a></div><div class="ttdef"><b>Definition:</b> <a href="_prelu_layer_8hpp_source.html#l00014">PreluLayer.hpp:14</a></div></div>
  90 <div class="ttc" id="classarmnn_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="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00305">Layer.hpp:305</a></div></div>
  91 <div class="ttc" id="classarmnn_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="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00043">Tensor.hpp:43</a></div></div>
  92 <div class="ttc" id="classarmnn_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#l00021">WorkloadFactory.hpp:21</a></div></div>
  93 <div class="ttc" id="classarmnn_1_1_i_output_slot_html_a9943775a364fc4ab53b85ac88f311886"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.html#a9943775a364fc4ab53b85ac88f311886">armnn::IOutputSlot::GetTensorInfo</a></div><div class="ttdeci">virtual const TensorInfo &amp; GetTensorInfo() const =0</div></div>
  94 <div class="ttc" id="classarmnn_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#l00209">Layer.hpp:209</a></div></div>
  95 <div class="ttc" id="classarmnn_1_1_layer_html_a30a858b2b26d651a066537e499fbf40d"><div class="ttname"><a href="classarmnn_1_1_layer.html#a30a858b2b26d651a066537e499fbf40d">armnn::Layer::PrepInfoAndDesc</a></div><div class="ttdeci">WorkloadInfo PrepInfoAndDesc(QueueDescriptor &amp;descriptor) const</div><div class="ttdoc">Helper function to reduce duplication in *LayerCreateWorkload. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00344">Layer.hpp:344</a></div></div>
  96 <div class="ttc" id="classarmnn_1_1_prelu_layer_html_adfa912d0c4c6c00f1af2cbfa799572b7"><div class="ttname"><a href="classarmnn_1_1_prelu_layer.html#adfa912d0c4c6c00f1af2cbfa799572b7">armnn::PreluLayer::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateWorkload(const IWorkloadFactory &amp;factory) const override</div><div class="ttdef"><b>Definition:</b> <a href="_prelu_layer_8cpp_source.html#l00021">PreluLayer.cpp:21</a></div></div>
  97 <div class="ttc" id="_prelu_layer_8hpp_html"><div class="ttname"><a href="_prelu_layer_8hpp.html">PreluLayer.hpp</a></div></div>
  98 <div class="ttc" id="_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#l00169">Exceptions.hpp:169</a></div></div>
  99 <div class="ttc" id="classarmnn_1_1_prelu_layer_html_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_prelu_layer.html#a8c8f543d7e9729362c266d12ec169966">armnn::PreluLayer::ValidateTensorShapesFromInputs</a></div><div class="ttdeci">void ValidateTensorShapesFromInputs() override</div><div class="ttdef"><b>Definition:</b> <a href="_prelu_layer_8cpp_source.html#l00097">PreluLayer.cpp:97</a></div></div>
 100 <div class="ttc" id="classarmnn_1_1_input_slot_html_a3153abb7c0c0a84629079b2fac7db54f"><div class="ttname"><a href="classarmnn_1_1_input_slot.html#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.html#l00199">Layer.hpp:199</a></div></div>
 101 <div class="ttc" id="_layer_clone_base_8hpp_html"><div class="ttname"><a href="_layer_clone_base_8hpp.html">LayerCloneBase.hpp</a></div></div>
 102 <div class="ttc" id="classarmnn_1_1_i_layer_visitor_html"><div class="ttname"><a href="classarmnn_1_1_i_layer_visitor.html">armnn::ILayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_layer_visitor_8hpp_source.html#l00016">ILayerVisitor.hpp:16</a></div></div>
 103 <div class="ttc" id="classarmnn_1_1_prelu_layer_html_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_prelu_layer.html#a65ca562c882ad619684445a1402f415a">armnn::PreluLayer::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="ttdef"><b>Definition:</b> <a href="_prelu_layer_8cpp_source.html#l00035">PreluLayer.cpp:35</a></div></div>
 104 <div class="ttc" id="classarmnn_1_1_i_layer_visitor_html_a4f6971a5d2c164c691dc7943f4befd5c"><div class="ttname"><a href="classarmnn_1_1_i_layer_visitor.html#a4f6971a5d2c164c691dc7943f4befd5c">armnn::ILayerVisitor::VisitPreluLayer</a></div><div class="ttdeci">virtual void VisitPreluLayer(const IConnectableLayer *layer, const char *name=nullptr)=0</div></div>
 105 <div class="ttc" id="classarmnn_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 &amp;location) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00337">Layer.cpp:337</a></div></div>
 106 <div class="ttc" id="namespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a0c5967f09e0669c840ebb1ed0da85e32">armnn::LayerType::Prelu</a></div></div>
 107 <div class="ttc" id="_workload_data_8hpp_html"><div class="ttname"><a href="_workload_data_8hpp.html">WorkloadData.hpp</a></div></div>
 108 <div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
 109 <div class="ttc" id="structarmnn_1_1_prelu_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_prelu_queue_descriptor.html">armnn::PreluQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00489">WorkloadData.hpp:489</a></div></div>
 110 <div class="ttc" id="_cpu_tensor_handle_8hpp_html"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.html">CpuTensorHandle.hpp</a></div></div>
 111 <div class="ttc" id="classarmnn_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>
 112 <div class="ttc" id="classarmnn_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#l00029">Graph.hpp:29</a></div></div>
 113 <div class="ttc" id="classarmnn_1_1_i_workload_factory_html_adf4a93f605e4e7dad6aee0b4d2159171"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#adf4a93f605e4e7dad6aee0b4d2159171">armnn::IWorkloadFactory::CreatePrelu</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreatePrelu(const PreluQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01335">WorkloadFactory.cpp:1335</a></div></div>
 114 <div class="ttc" id="classarmnn_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#l00088">Tensor.hpp:88</a></div></div>
 115 <div class="ttc" id="classarmnn_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#l00063">Layer.cpp:63</a></div></div>
 116 <div class="ttc" id="classarmnn_1_1_prelu_layer_html_a75a50f464326fefa605ea84ae2c9be85"><div class="ttname"><a href="classarmnn_1_1_prelu_layer.html#a75a50f464326fefa605ea84ae2c9be85">armnn::PreluLayer::Accept</a></div><div class="ttdeci">void Accept(ILayerVisitor &amp;visitor) const override</div><div class="ttdef"><b>Definition:</b> <a href="_prelu_layer_8cpp_source.html#l00115">PreluLayer.cpp:115</a></div></div>
 117 <div class="ttc" id="classarmnn_1_1_prelu_layer_html_af5dd85c2adbf7e9f95d9c984157620a9"><div class="ttname"><a href="classarmnn_1_1_prelu_layer.html#af5dd85c2adbf7e9f95d9c984157620a9">armnn::PreluLayer::Clone</a></div><div class="ttdeci">PreluLayer * Clone(Graph &amp;graph) const override</div><div class="ttdef"><b>Definition:</b> <a href="_prelu_layer_8cpp_source.html#l00028">PreluLayer.cpp:28</a></div></div>
 118 <div class="ttc" id="classarmnn_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="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</a></div></div>
 119 <div class="ttc" id="namespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8hpp_source.html#l00014">InternalTypes.hpp:14</a></div></div>
 120 <div class="ttc" id="classarmnn_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="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00310">Layer.hpp:310</a></div></div>
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