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+<div class="title">MeanLayer.cpp</div> </div>
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+<a href="_mean_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="_mean_layer_8hpp.xhtml">MeanLayer.hpp</a>&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_layer_clone_base_8hpp.xhtml">LayerCloneBase.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="_cpu_tensor_handle_8hpp.xhtml">backendsCommon/CpuTensorHandle.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="_workload_data_8hpp.xhtml">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.xhtml">backendsCommon/WorkloadFactory.hpp</a>&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;</div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="preprocessor">#include &lt;cstring&gt;</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></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;</div><div class="line"><a name="l00018"></a><span class="lineno"><a class="line" href="classarmnn_1_1_mean_layer.xhtml#a08526b2efde1012437fb5992370dcfce"> 18</a></span>&#160;<a class="code" href="classarmnn_1_1_mean_layer.xhtml#a08526b2efde1012437fb5992370dcfce">MeanLayer::MeanLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_mean_descriptor.xhtml">armnn::MeanDescriptor</a>&amp; param, <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_with_parameters.xhtml">LayerWithParameters</a>(1, 1, <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>::<a class="code" href="namespacearmnn.xhtml#a165ae372a7f67cad64ef3395d30122ce">Mean</a>, param, 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"><a class="line" href="classarmnn_1_1_mean_layer.xhtml#adfa912d0c4c6c00f1af2cbfa799572b7"> 22</a></span>&#160;std::unique_ptr&lt;IWorkload&gt; <a class="code" href="classarmnn_1_1_mean_layer.xhtml#adfa912d0c4c6c00f1af2cbfa799572b7">MeanLayer::CreateWorkload</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>&amp; factory)<span class="keyword"> const</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; <a class="code" href="structarmnn_1_1_mean_queue_descriptor.xhtml">MeanQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a> = <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a>;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a28e0548abfc4e79c48f29a3d11a062e9">m_KeepDims</a> = <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a28e0548abfc4e79c48f29a3d11a062e9">m_KeepDims</a>;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; <span class="keywordflow">return</span> factory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#ac63f8f12f80efbe37b789d1540649470">CreateMean</a>(descriptor, <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#a30a858b2b26d651a066537e499fbf40d">PrepInfoAndDesc</a>(descriptor));</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;}</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"><a class="line" href="classarmnn_1_1_mean_layer.xhtml#a12a07b8514277e7db725c483e3ab6d03"> 31</a></span>&#160;<a class="code" href="classarmnn_1_1_mean_layer.xhtml">MeanLayer</a>* <a class="code" href="classarmnn_1_1_mean_layer.xhtml#a12a07b8514277e7db725c483e3ab6d03">MeanLayer::Clone</a>(<a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a>&amp; graph)<span class="keyword"> const</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keyword">auto</span> layer = CloneBase&lt;MeanLayer&gt;(graph, <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>, <a class="code" href="classarmnn_1_1_layer.xhtml#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</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"> 35</span>&#160; layer-&gt;<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a> = m_Param.m_Axis;</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; layer-&gt;m_Param.m_KeepDims = m_Param.m_KeepDims;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <span class="keywordflow">return</span> std::move(layer);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;}</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"><a class="line" href="classarmnn_1_1_mean_layer.xhtml#a8c8f543d7e9729362c266d12ec169966"> 41</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_mean_layer.xhtml#a8c8f543d7e9729362c266d12ec169966">MeanLayer::ValidateTensorShapesFromInputs</a>()</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160;{</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <a class="code" href="classarmnn_1_1_layer.xhtml#a0607e36e88f38c34c71c663164b76776">VerifyLayerConnections</a>(1, <a class="code" href="_exceptions_8hpp.xhtml#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</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; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; input = <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>();</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; BOOST_ASSERT_MSG(input.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() &gt; 0 &amp;&amp; input.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() &lt;= 4,</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <span class="stringliteral">&quot;MeanLayer: Mean supports up to 4D input.&quot;</span>);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> rank = input.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>();</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputRank = 0;</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; <span class="comment">// Calculate output dimension</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a28e0548abfc4e79c48f29a3d11a062e9">m_KeepDims</a>)</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; {</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; outputRank = rank;</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; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a>.empty())</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; outputRank = 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; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a>.size() &gt;= input.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>())</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; <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_layer_validation_exception.xhtml">LayerValidationException</a>(<span class="stringliteral">&quot;MeanLayer: Dimensions to reduce can not be bigger than input dimensions&quot;</span>);</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="keywordflow">else</span></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; outputRank = input.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() - <a class="code" href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">boost::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a>.size());</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="keywordflow">if</span> (outputRank == 0)</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; outputRank = 1;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; }</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;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; std::vector&lt;unsigned int&gt; dimSizes(outputRank, 1);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keywordflow">if</span> (!<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a>.empty())</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="comment">// Skip the dimension that has been reduced unless keepDims is true.</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputIndex = 0;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; input.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; {</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="keywordflow">if</span> (std::find(<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a>.begin(), <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a>.end(), i) == <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a>.end())</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; dimSizes[outputIndex] = <a class="code" href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">boost::numeric_cast</a>&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;(input.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[i]);</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; ++outputIndex;</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; <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a28e0548abfc4e79c48f29a3d11a062e9">m_KeepDims</a>)</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; dimSizes[outputIndex] = 1;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; ++outputIndex;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; }</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>&amp; inferredShape = <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(outputRank, dimSizes.data());</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; ConditionalThrowIfNotEqual&lt;LayerValidationException&gt;(</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <span class="stringliteral">&quot;MeanLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.&quot;</span>,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</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="l00099"></a><span class="lineno"> 99</span>&#160; inferredShape);</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;</div><div class="line"><a name="l00102"></a><span class="lineno"><a class="line" href="classarmnn_1_1_mean_layer.xhtml#a75a50f464326fefa605ea84ae2c9be85"> 102</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_mean_layer.xhtml#a75a50f464326fefa605ea84ae2c9be85">MeanLayer::Accept</a>(<a class="code" href="classarmnn_1_1_i_layer_visitor.xhtml">ILayerVisitor</a>&amp; visitor)<span class="keyword"> const</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160;<span class="keyword"></span>{</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; visitor.<a class="code" href="classarmnn_1_1_i_layer_visitor.xhtml#ab33e9cae83e312ccc9e12adcf53494e3">VisitMeanLayer</a>(<span class="keyword">this</span>, <a class="code" href="classarmnn_1_1_layer_with_parameters.xhtml#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>(), <a class="code" href="classarmnn_1_1_layer.xhtml#a7ddf0cf6f620d59c10e63495ace795d0">GetName</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;} <span class="comment">// namespace armnn</span></div><div class="ttc" id="_workload_data_8hpp_xhtml"><div class="ttname"><a href="_workload_data_8hpp.xhtml">WorkloadData.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_with_parameters_xhtml_ad32ac22bc72e28dfd6b466d143c8e262"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.xhtml#ad32ac22bc72e28dfd6b466d143c8e262">armnn::LayerWithParameters&lt; MeanDescriptor &gt;::m_Param</a></div><div class="ttdeci">MeanDescriptor 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.xhtml#l00050">LayerWithParameters.hpp:50</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_with_parameters_xhtml_a502c06a1b13e6d90a6cbf47c081f1444"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.xhtml#a502c06a1b13e6d90a6cbf47c081f1444">armnn::LayerWithParameters&lt; MeanDescriptor &gt;::GetParameters</a></div><div class="ttdeci">const MeanDescriptor &amp; GetParameters() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.xhtml#l00018">LayerWithParameters.hpp:18</a></div></div>
+<div class="ttc" id="classarmnn_1_1_mean_layer_xhtml_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_mean_layer.xhtml#a8c8f543d7e9729362c266d12ec169966">armnn::MeanLayer::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 MeanLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_mean_layer_8cpp_source.xhtml#l00041">MeanLayer.cpp:41</a></div></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="_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_workload_factory_8hpp.xhtml">WorkloadFactory.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.xhtml#l00021">WorkloadFactory.hpp:21</a></div></div>
+<div class="ttc" id="classarmnn_1_1_mean_layer_xhtml_a12a07b8514277e7db725c483e3ab6d03"><div class="ttname"><a href="classarmnn_1_1_mean_layer.xhtml#a12a07b8514277e7db725c483e3ab6d03">armnn::MeanLayer::Clone</a></div><div class="ttdeci">MeanLayer * Clone(Graph &amp;graph) const override</div><div class="ttdoc">Creates a dynamically-allocated copy of this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_mean_layer_8cpp_source.xhtml#l00031">MeanLayer.cpp:31</a></div></div>
+<div class="ttc" id="classarmnn_1_1_mean_layer_xhtml_adfa912d0c4c6c00f1af2cbfa799572b7"><div class="ttname"><a href="classarmnn_1_1_mean_layer.xhtml#adfa912d0c4c6c00f1af2cbfa799572b7">armnn::MeanLayer::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateWorkload(const IWorkloadFactory &amp;factory) const override</div><div class="ttdoc">Makes a workload for the Mean type. </div><div class="ttdef"><b>Definition:</b> <a href="_mean_layer_8cpp_source.xhtml#l00022">MeanLayer.cpp:22</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_mean_layer_xhtml_a08526b2efde1012437fb5992370dcfce"><div class="ttname"><a href="classarmnn_1_1_mean_layer.xhtml#a08526b2efde1012437fb5992370dcfce">armnn::MeanLayer::MeanLayer</a></div><div class="ttdeci">MeanLayer(const MeanDescriptor &amp;param, const char *name)</div><div class="ttdoc">Constructor to create a MeanLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_mean_layer_8cpp_source.xhtml#l00018">MeanLayer.cpp:18</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="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00049">WorkloadData.hpp:49</a></div></div>
+<div class="ttc" id="classarmnn_1_1_mean_layer_xhtml_a75a50f464326fefa605ea84ae2c9be85"><div class="ttname"><a href="classarmnn_1_1_mean_layer.xhtml#a75a50f464326fefa605ea84ae2c9be85">armnn::MeanLayer::Accept</a></div><div class="ttdeci">void Accept(ILayerVisitor &amp;visitor) const override</div><div class="ttdoc">Apply a visitor to this layer. </div><div class="ttdef"><b>Definition:</b> <a href="_mean_layer_8cpp_source.xhtml#l00102">MeanLayer.cpp:102</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_layer_visitor_xhtml_ab33e9cae83e312ccc9e12adcf53494e3"><div class="ttname"><a href="classarmnn_1_1_i_layer_visitor.xhtml#ab33e9cae83e312ccc9e12adcf53494e3">armnn::ILayerVisitor::VisitMeanLayer</a></div><div class="ttdeci">virtual void VisitMeanLayer(const IConnectableLayer *layer, const MeanDescriptor &amp;meanDescriptor, const char *name=nullptr)=0</div><div class="ttdoc">Function a Mean layer should call back to when its Accept(ILayerVisitor&amp;) function is invoked...</div></div>
+<div class="ttc" id="structarmnn_1_1_mean_descriptor_xhtml_a1f0d67b087c491248bd1cde3ff995a95"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">armnn::MeanDescriptor::m_Axis</a></div><div class="ttdeci">std::vector&lt; unsigned int &gt; m_Axis</div><div class="ttdoc">Values for the dimensions to reduce. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00895">Descriptors.hpp:895</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="structarmnn_1_1_mean_descriptor_xhtml_a28e0548abfc4e79c48f29a3d11a062e9"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml#a28e0548abfc4e79c48f29a3d11a062e9">armnn::MeanDescriptor::m_KeepDims</a></div><div class="ttdeci">bool m_KeepDims</div><div class="ttdoc">Enable/disable keep dimensions. If true, then the reduced dimensions that are of length 1 are kept...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00897">Descriptors.hpp:897</a></div></div>
+<div class="ttc" id="_mean_layer_8hpp_xhtml"><div class="ttname"><a href="_mean_layer_8hpp.xhtml">MeanLayer.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_validation_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer_validation_exception.xhtml">armnn::LayerValidationException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00105">Exceptions.hpp:105</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a37fa39012e90d568df7f774cd6d1e956"><div class="ttname"><a href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t&lt; std::is_unsigned&lt; Source &gt;::value &amp;&amp;std::is_unsigned&lt; Dest &gt;::value, Dest &gt; numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00033">NumericCast.hpp:33</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_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div>
+<div class="ttc" id="_cpu_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.xhtml">CpuTensorHandle.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_ac63f8f12f80efbe37b789d1540649470"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#ac63f8f12f80efbe37b789d1540649470">armnn::IWorkloadFactory::CreateMean</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreateMean(const MeanQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;Info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01274">WorkloadFactory.cpp:1274</a></div></div>
+<div class="ttc" id="structarmnn_1_1_mean_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml">armnn::MeanDescriptor</a></div><div class="ttdoc">A MeanDescriptor for the MeanLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00877">Descriptors.hpp:877</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_with_parameters_xhtml_a30a858b2b26d651a066537e499fbf40d"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.xhtml#a30a858b2b26d651a066537e499fbf40d">armnn::LayerWithParameters&lt; MeanDescriptor &gt;::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_with_parameters_8hpp_source.xhtml#l00043">LayerWithParameters.hpp:43</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a165ae372a7f67cad64ef3395d30122ce"><div class="ttname"><a href="namespacearmnn.xhtml#a165ae372a7f67cad64ef3395d30122ce">armnn::Mean</a></div><div class="ttdeci">void Mean(const armnn::TensorInfo &amp;inputInfo, const armnn::TensorInfo &amp;outputInfo, const std::vector&lt; unsigned int &gt; &amp;axis, Decoder&lt; float &gt; &amp;input, Encoder&lt; float &gt; &amp;output)</div><div class="ttdef"><b>Definition:</b> <a href="backends_2reference_2workloads_2_mean_8cpp_source.xhtml#l00071">Mean.cpp:71</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_layer_visitor_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_layer_visitor.xhtml">armnn::ILayerVisitor</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_layer_visitor_8hpp_source.xhtml#l00016">ILayerVisitor.hpp:16</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="classarmnn_1_1_layer_xhtml_a7ddf0cf6f620d59c10e63495ace795d0"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#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.xhtml#l00305">Layer.hpp:305</a></div></div>
+<div class="ttc" id="classarmnn_1_1_mean_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_mean_layer.xhtml">armnn::MeanLayer</a></div><div class="ttdoc">This layer represents a mean operation. </div><div class="ttdef"><b>Definition:</b> <a href="_mean_layer_8hpp_source.xhtml#l00014">MeanLayer.hpp:14</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_with_parameters_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.xhtml">armnn::LayerWithParameters</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.xhtml#l00013">LayerWithParameters.hpp:13</a></div></div>
+<div class="ttc" id="structarmnn_1_1_mean_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mean_queue_descriptor.xhtml">armnn::MeanQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00246">WorkloadData.hpp:246</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_tensor_info_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#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.xhtml#l00092">Tensor.hpp:92</a></div></div>
+<div class="ttc" id="_layer_clone_base_8hpp_xhtml"><div class="ttname"><a href="_layer_clone_base_8hpp.xhtml">LayerCloneBase.hpp</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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