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| 87 | <a href="_convolution2d_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 © 2017 Arm Ltd. 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="_convolution2d_layer_8hpp.html">Convolution2dLayer.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_layer_clone_base_8hpp.html">LayerCloneBase.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_types_utils_8hpp.html">armnn/TypesUtils.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_data_layout_indexed_8hpp.html">armnnUtils/DataLayoutIndexed.hpp</a>></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"> 13</span> <span class="preprocessor">#include <<a class="code" href="_cpu_tensor_handle_8hpp.html">backendsCommon/CpuTensorHandle.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_workload_factory_8hpp.html">backendsCommon/WorkloadFactory.hpp</a>></span></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> <span class="preprocessor">#include <string></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"> 18</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn_utils.html">armnnUtils</a>;</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> {</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#ad026ad183e8c182f60d22a6cc39ae873"> 23</a></span> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#ad026ad183e8c182f60d22a6cc39ae873">Convolution2dLayer::Convolution2dLayer</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_convolution2d_descriptor.html">Convolution2dDescriptor</a>& param, <span class="keyword">const</span> <span class="keywordtype">char</span>* name)</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  : <a class="code" href="classarmnn_1_1_layer_with_parameters.html">LayerWithParameters</a>(1, 1, <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>::<a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">Convolution2d</a>, param, name)</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> {</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> }</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a2ca654770a1890f15e3c7aab98e434a5"> 29</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2ca654770a1890f15e3c7aab98e434a5">Convolution2dLayer::SerializeLayerParameters</a>(<a class="code" href="namespacearmnn.html#a8c42c6647e31ebe525aeba878d133e45">ParameterStringifyFunction</a>& fn)<span class="keyword"> const</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword"></span>{</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="comment">//using DescriptorType = Parameters;</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="keyword">const</span> std::vector<TensorShape>& inputShapes =</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  {</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <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>()-><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="l00035"></a><span class="lineno"> 35</span>  <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->GetTensorInfo().GetShape()</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="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> filterShape = inputShapes[1];</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">DataLayoutIndexed</a> dataLayoutIndex(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterWidth = filterShape[dataLayoutIndex.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">GetWidthIndex</a>()];</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterHeight = filterShape[dataLayoutIndex.<a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">GetHeightIndex</a>()];</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outChannels = filterShape[0];</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>  fn(<span class="stringliteral">"OutputChannels"</span>,std::to_string(outChannels));</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  fn(<span class="stringliteral">"FilterWidth"</span>,std::to_string(filterWidth));</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  fn(<span class="stringliteral">"FilterHeight"</span>,std::to_string(filterHeight));</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <a class="code" href="classarmnn_1_1_layer_with_parameters.html#a2ca654770a1890f15e3c7aab98e434a5">LayerWithParameters<Convolution2dDescriptor>::SerializeLayerParameters</a>(fn);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> }</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00049"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#adfa912d0c4c6c00f1af2cbfa799572b7"> 49</a></span> std::unique_ptr<IWorkload> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#adfa912d0c4c6c00f1af2cbfa799572b7">Convolution2dLayer::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="l00050"></a><span class="lineno"> 50</span> <span class="keyword"></span>{</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="comment">// on this level constant data should not be released..</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> != <span class="keyword">nullptr</span>, <span class="stringliteral">"Convolution2dLayer: Weights data should not be null."</span>);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.html">Convolution2dQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.html#a3369b66d9316a773a41711e3f590c041">m_Weight</a> = <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a>.get();</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>)</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>  BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> != <span class="keyword">nullptr</span>, <span class="stringliteral">"Convolution2dLayer: Bias data should not be null."</span>);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.html#ab3437cee6b0687812104fc1b37cbe8b3">m_Bias</a> = <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>.get();</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>  <span class="keywordflow">return</span> factory.<a class="code" href="classarmnn_1_1_i_workload_factory.html#a2184995027cd2c9f9980206de9658855">CreateConvolution2d</a>(descriptor, <a class="code" href="classarmnn_1_1_layer_with_parameters.html#a30a858b2b26d651a066537e499fbf40d">PrepInfoAndDesc</a>(descriptor));</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"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#acf7bec8b795447d4b23e0339a6561044"> 66</a></span> <a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>* <a class="code" href="classarmnn_1_1_convolution2d_layer.html#acf7bec8b795447d4b23e0339a6561044">Convolution2dLayer::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="l00067"></a><span class="lineno"> 67</span> <span class="keyword"></span>{</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keyword">auto</span> layer = CloneBase<Convolution2dLayer>(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="l00069"></a><span class="lineno"> 69</span> </div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordflow">if</span> (layer->m_Param.m_BiasEnabled)</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  layer->m_Bias = <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) : <span class="keyword">nullptr</span>;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  }</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="keywordflow">return</span> std::move(layer);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> }</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a65ca562c882ad619684445a1402f415a"> 80</a></span> std::vector<TensorShape> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a65ca562c882ad619684445a1402f415a">Convolution2dLayer::InferOutputShapes</a>(<span class="keyword">const</span> std::vector<TensorShape>& inputShapes)<span class="keyword"> const</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="keyword"></span>{</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  BOOST_ASSERT(inputShapes.size() == 2);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& inputShape = inputShapes[0];</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> filterShape = inputShapes[1];</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="comment">// If we support multiple batch dimensions in the future, then this assert will need to change.</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, <span class="stringliteral">"Convolutions will always have 4D input."</span>);</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>  <a class="code" href="classarmnn_utils_1_1_data_layout_indexed.html">DataLayoutIndexed</a> dataLayoutIndex(<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inWidth = inputShape[dataLayoutIndex.GetWidthIndex()];</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inHeight = inputShape[dataLayoutIndex.GetHeightIndex()];</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inBatchSize = inputShape[0];</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> </div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterWidth = filterShape[dataLayoutIndex.GetWidthIndex()];</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dilatedFilterWidth = filterWidth + (<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> - 1) * (filterWidth - 1);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> readWidth = (inWidth + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>) - dilatedFilterWidth;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outWidth = 1 + (readWidth / <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> filterHeight = filterShape[dataLayoutIndex.GetHeightIndex()];</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dilatedFilterHeight = filterHeight + (<a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> - 1) * (filterHeight - 1);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> readHeight = (inHeight + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> + <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>) - dilatedFilterHeight;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outHeight = 1 + (readHeight / <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>);</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outChannels = filterShape[0];</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outBatchSize = inBatchSize;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> tensorShape = <a class="code" href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">m_Param</a>.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> == <a class="code" href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a> ?</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>( { outBatchSize, outHeight, outWidth, outChannels } ) :</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>( { outBatchSize, outChannels, outHeight, outWidth });</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordflow">return</span> std::vector<TensorShape>({ tensorShape });</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> }</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> </div><div class="line"><a name="l00115"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a8c8f543d7e9729362c266d12ec169966"> 115</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a8c8f543d7e9729362c266d12ec169966">Convolution2dLayer::ValidateTensorShapesFromInputs</a>()</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <a class="code" href="classarmnn_1_1_layer.html#a0607e36e88f38c34c71c663164b76776">VerifyLayerConnections</a>(1, <a class="code" href="_exceptions_8hpp.html#aa3be76aec4ce713822a5ea1ecbb7bc61">CHECK_LOCATION</a>());</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="comment">// check if we m_Weight data is not nullptr</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  BOOST_ASSERT_MSG(<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> != <span class="keyword">nullptr</span>, <span class="stringliteral">"Convolution2dLayer: Weights data should not be null."</span>);</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="keyword">auto</span> inferredShapes = <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>({</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <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>()-><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="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->GetTensorInfo().GetShape() });</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  BOOST_ASSERT(inferredShapes.size() == 1);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  ConditionalThrowIfNotEqual<LayerValidationException>(</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="stringliteral">"Convolution2dLayer: TensorShape set on OutputSlot[0] does not match the inferred shape."</span>,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <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="l00131"></a><span class="lineno"> 131</span>  inferredShapes[0]);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> }</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#abe659a5afa7523f5dbc04bcba9b31f1a"> 134</a></span> <a class="code" href="classarmnn_1_1_layer.html#a585d59ec610af46a76487fd6c1c55ac1">Layer::ConstantTensors</a> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#abe659a5afa7523f5dbc04bcba9b31f1a">Convolution2dLayer::GetConstantTensorsByRef</a>()</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> {</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keywordflow">return</span> {<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a>, <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>};</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> }</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"><a class="line" href="classarmnn_1_1_convolution2d_layer.html#a75a50f464326fefa605ea84ae2c9be85"> 139</a></span> <span class="keywordtype">void</span> <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a75a50f464326fefa605ea84ae2c9be85">Convolution2dLayer::Accept</a>(<a class="code" href="classarmnn_1_1_i_layer_visitor.html">ILayerVisitor</a>& visitor)<span class="keyword"> const</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="keyword"></span>{</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a> weightsTensor(<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->GetTensorInfo(), <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->Map(<span class="keyword">true</span>)) ;</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="classarmnn_1_1_optional.html">Optional<ConstTensor></a> optionalBiasTensor = <a class="code" href="structarmnn_1_1_empty_optional.html">EmptyOptional</a>();</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> </div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordflow">if</span> (<a class="code" href="classarmnn_1_1_layer_with_parameters.html#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>().m_BiasEnabled)</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  {</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <a class="code" href="classarmnn_1_1_const_tensor.html">ConstTensor</a> biasTensor(<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>->GetTensorInfo(), <a class="code" href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>->Map(<span class="keyword">true</span>));</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  optionalBiasTensor = <a class="code" href="classarmnn_1_1_optional.html">Optional<ConstTensor></a>(biasTensor);</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  }</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> </div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  visitor.<a class="code" href="classarmnn_1_1_i_layer_visitor.html#abc8fe4c6cbc8fa2b13c525500dddfbf6">VisitConvolution2dLayer</a>(<span class="keyword">this</span>, <a class="code" href="classarmnn_1_1_layer_with_parameters.html#a502c06a1b13e6d90a6cbf47c081f1444">GetParameters</a>(), weightsTensor, optionalBiasTensor, <a class="code" href="classarmnn_1_1_layer.html#a7ddf0cf6f620d59c10e63495ace795d0">GetName</a>());</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> }</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> </div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> } <span class="comment">// namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_abe659a5afa7523f5dbc04bcba9b31f1a"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#abe659a5afa7523f5dbc04bcba9b31f1a">armnn::Convolution2dLayer::GetConstantTensorsByRef</a></div><div class="ttdeci">ConstantTensors GetConstantTensorsByRef() override</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00134">Convolution2dLayer.cpp:134</a></div></div> |
| 88 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a75a50f464326fefa605ea84ae2c9be85"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a75a50f464326fefa605ea84ae2c9be85">armnn::Convolution2dLayer::Accept</a></div><div class="ttdeci">void Accept(ILayerVisitor &visitor) const override</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00139">Convolution2dLayer.cpp:139</a></div></div> |
| 89 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00440">Descriptors.hpp:440</a></div></div> |
| 90 | <div class="ttc" id="_workload_factory_8hpp_html"><div class="ttname"><a href="_workload_factory_8hpp.html">WorkloadFactory.hpp</a></div></div> |
| 91 | <div class="ttc" id="classarmnn_1_1_layer_with_parameters_html_a2ca654770a1890f15e3c7aab98e434a5"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#a2ca654770a1890f15e3c7aab98e434a5">armnn::LayerWithParameters::SerializeLayerParameters</a></div><div class="ttdeci">void SerializeLayerParameters(ParameterStringifyFunction &fn) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00022">LayerWithParameters.hpp:22</a></div></div> |
| 92 | <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> |
| 93 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a2ca654770a1890f15e3c7aab98e434a5"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a2ca654770a1890f15e3c7aab98e434a5">armnn::Convolution2dLayer::SerializeLayerParameters</a></div><div class="ttdeci">void SerializeLayerParameters(ParameterStringifyFunction &fn) const override</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00029">Convolution2dLayer.cpp:29</a></div></div> |
| 94 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a39925bc24d3afcfb322a46a5884fadb9"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">armnn::Convolution2dLayer::m_Bias</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Bias</div><div class="ttdoc">A unique pointer to store Bias values. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00022">Convolution2dLayer.hpp:22</a></div></div> |
| 95 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">armnn::Convolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00424">Descriptors.hpp:424</a></div></div> |
| 96 | <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> |
| 97 | <div class="ttc" id="classarmnn_1_1_i_layer_visitor_html_abc8fe4c6cbc8fa2b13c525500dddfbf6"><div class="ttname"><a href="classarmnn_1_1_i_layer_visitor.html#abc8fe4c6cbc8fa2b13c525500dddfbf6">armnn::ILayerVisitor::VisitConvolution2dLayer</a></div><div class="ttdeci">virtual void VisitConvolution2dLayer(const IConnectableLayer *layer, const Convolution2dDescriptor &convolution2dDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)=0</div></div> |
| 98 | <div class="ttc" id="classarmnn_1_1_const_tensor_html"><div class="ttname"><a href="classarmnn_1_1_const_tensor.html">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00199">Tensor.hpp:199</a></div></div> |
| 99 | <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 & GetTensorInfo() const =0</div></div> |
| 100 | <div class="ttc" id="structarmnn_1_1_convolution2d_queue_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.html">armnn::Convolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00168">WorkloadData.hpp:168</a></div></div> |
| 101 | <div class="ttc" id="classarmnn_1_1_optional_html"><div class="ttname"><a href="classarmnn_1_1_optional.html">armnn::Optional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.html#l00270">Optional.hpp:270</a></div></div> |
| 102 | <div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a61c00316c443adc233c24e85c6c5b740"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a61c00316c443adc233c24e85c6c5b740">armnnUtils::DataLayoutIndexed::GetHeightIndex</a></div><div class="ttdeci">unsigned int GetHeightIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00024">DataLayoutIndexed.hpp:24</a></div></div> |
| 103 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html">armnn::Convolution2dLayer</a></div><div class="ttdoc">This layer represents a convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00015">Convolution2dLayer.hpp:15</a></div></div> |
| 104 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">armnn::Convolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00020">Convolution2dLayer.hpp:20</a></div></div> |
| 105 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">armnn::Convolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00428">Descriptors.hpp:428</a></div></div> |
| 106 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a8c8f543d7e9729362c266d12ec169966"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a8c8f543d7e9729362c266d12ec169966">armnn::Convolution2dLayer::ValidateTensorShapesFromInputs</a></div><div class="ttdeci">void ValidateTensorShapesFromInputs() override</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00115">Convolution2dLayer.cpp:115</a></div></div> |
| 107 | <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> |
| 108 | <div class="ttc" id="_types_utils_8hpp_html"><div class="ttname"><a href="_types_utils_8hpp.html">TypesUtils.hpp</a></div></div> |
| 109 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00432">Descriptors.hpp:432</a></div></div> |
| 110 | <div class="ttc" id="structarmnn_1_1_convolution2d_queue_descriptor_html_a3369b66d9316a773a41711e3f590c041"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.html#a3369b66d9316a773a41711e3f590c041">armnn::Convolution2dQueueDescriptor::m_Weight</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Weight</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00176">WorkloadData.hpp:176</a></div></div> |
| 111 | <div class="ttc" id="classarmnn_1_1_layer_html_a585d59ec610af46a76487fd6c1c55ac1"><div class="ttname"><a href="classarmnn_1_1_layer.html#a585d59ec610af46a76487fd6c1c55ac1">armnn::Layer::ConstantTensors</a></div><div class="ttdeci">std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >> ConstantTensors</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00356">Layer.hpp:356</a></div></div> |
| 112 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">armnn::Convolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00426">Descriptors.hpp:426</a></div></div> |
| 113 | <div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html_a414e6f95548e6f7a01d5028b55ad3941"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html#a414e6f95548e6f7a01d5028b55ad3941">armnnUtils::DataLayoutIndexed::GetWidthIndex</a></div><div class="ttdeci">unsigned int GetWidthIndex() const</div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00025">DataLayoutIndexed.hpp:25</a></div></div> |
| 114 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Convolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00422">Descriptors.hpp:422</a></div></div> |
| 115 | <div class="ttc" id="namespacearmnn_utils_html"><div class="ttname"><a href="namespacearmnn_utils.html">armnnUtils</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00013">DataLayoutIndexed.hpp:13</a></div></div> |
| 116 | <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> |
| 117 | <div class="ttc" id="_layer_clone_base_8hpp_html"><div class="ttname"><a href="_layer_clone_base_8hpp.html">LayerCloneBase.hpp</a></div></div> |
| 118 | <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> |
| 119 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00430">Descriptors.hpp:430</a></div></div> |
| 120 | <div class="ttc" id="classarmnn_1_1_layer_with_parameters_html_a502c06a1b13e6d90a6cbf47c081f1444"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#a502c06a1b13e6d90a6cbf47c081f1444">armnn::LayerWithParameters< Convolution2dDescriptor >::GetParameters</a></div><div class="ttdeci">const Convolution2dDescriptor & GetParameters() const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_with_parameters_8hpp_source.html#l00018">LayerWithParameters.hpp:18</a></div></div> |
| 121 | <div class="ttc" id="classarmnn_1_1_layer_with_parameters_html_ad32ac22bc72e28dfd6b466d143c8e262"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#ad32ac22bc72e28dfd6b466d143c8e262">armnn::LayerWithParameters< Convolution2dDescriptor >::m_Param</a></div><div class="ttdeci">Convolution2dDescriptor 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#l00050">LayerWithParameters.hpp:50</a></div></div> |
| 122 | <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 &location) const</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00337">Layer.cpp:337</a></div></div> |
| 123 | <div class="ttc" id="classarmnn_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#l00013">LayerWithParameters.hpp:13</a></div></div> |
| 124 | <div class="ttc" id="classarmnn_1_1_layer_with_parameters_html_a30a858b2b26d651a066537e499fbf40d"><div class="ttname"><a href="classarmnn_1_1_layer_with_parameters.html#a30a858b2b26d651a066537e499fbf40d">armnn::LayerWithParameters< Convolution2dDescriptor >::PrepInfoAndDesc</a></div><div class="ttdeci">WorkloadInfo PrepInfoAndDesc(QueueDescriptor &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.html#l00043">LayerWithParameters.hpp:43</a></div></div> |
| 125 | <div class="ttc" id="structarmnn_1_1_empty_optional_html"><div class="ttname"><a href="structarmnn_1_1_empty_optional.html">armnn::EmptyOptional</a></div><div class="ttdef"><b>Definition:</b> <a href="_optional_8hpp_source.html#l00032">Optional.hpp:32</a></div></div> |
| 126 | <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> |
| 127 | <div class="ttc" id="structarmnn_1_1_convolution2d_queue_descriptor_html_ab3437cee6b0687812104fc1b37cbe8b3"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.html#ab3437cee6b0687812104fc1b37cbe8b3">armnn::Convolution2dQueueDescriptor::m_Bias</a></div><div class="ttdeci">const ConstCpuTensorHandle * m_Bias</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.html#l00177">WorkloadData.hpp:177</a></div></div> |
| 128 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00438">Descriptors.hpp:438</a></div></div> |
| 129 | <div class="ttc" id="_data_layout_indexed_8hpp_html"><div class="ttname"><a href="_data_layout_indexed_8hpp.html">DataLayoutIndexed.hpp</a></div></div> |
| 130 | <div class="ttc" id="namespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4adb033d2f81b68f9a17e8f62de69fed4a">armnn::LayerType::Convolution2d</a></div></div> |
| 131 | <div class="ttc" id="_cpu_tensor_handle_8hpp_html"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.html">CpuTensorHandle.hpp</a></div></div> |
| 132 | <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> |
| 133 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_acf7bec8b795447d4b23e0339a6561044"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#acf7bec8b795447d4b23e0339a6561044">armnn::Convolution2dLayer::Clone</a></div><div class="ttdeci">Convolution2dLayer * Clone(Graph &graph) const override</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00066">Convolution2dLayer.cpp:66</a></div></div> |
| 134 | <div class="ttc" id="namespacearmnn_html_a8c42c6647e31ebe525aeba878d133e45"><div class="ttname"><a href="namespacearmnn.html#a8c42c6647e31ebe525aeba878d133e45">armnn::ParameterStringifyFunction</a></div><div class="ttdeci">std::function< void(const std::string &name, const std::string &value)> ParameterStringifyFunction</div><div class="ttdef"><b>Definition:</b> <a href="_serialize_layer_parameters_8hpp_source.html#l00014">SerializeLayerParameters.hpp:14</a></div></div> |
| 135 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_ad026ad183e8c182f60d22a6cc39ae873"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#ad026ad183e8c182f60d22a6cc39ae873">armnn::Convolution2dLayer::Convolution2dLayer</a></div><div class="ttdeci">Convolution2dLayer(const Convolution2dDescriptor &param, const char *name)</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00023">Convolution2dLayer.cpp:23</a></div></div> |
| 136 | <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> |
| 137 | <div class="ttc" id="classarmnn_1_1_i_workload_factory_html_a2184995027cd2c9f9980206de9658855"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.html#a2184995027cd2c9f9980206de9658855">armnn::IWorkloadFactory::CreateConvolution2d</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateConvolution2d(const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.html#l01142">WorkloadFactory.cpp:1142</a></div></div> |
| 138 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a302b688d88dd73cde0fb1faef6679907">armnn::Convolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation along y axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00436">Descriptors.hpp:436</a></div></div> |
| 139 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_adfa912d0c4c6c00f1af2cbfa799572b7"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#adfa912d0c4c6c00f1af2cbfa799572b7">armnn::Convolution2dLayer::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00049">Convolution2dLayer.cpp:49</a></div></div> |
| 140 | <div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a65ca562c882ad619684445a1402f415a">armnn::Convolution2dLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.html#l00080">Convolution2dLayer.cpp:80</a></div></div> |
| 141 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00392">Descriptors.hpp:392</a></div></div> |
| 142 | <div class="ttc" id="classarmnn_utils_1_1_data_layout_indexed_html"><div class="ttname"><a href="classarmnn_utils_1_1_data_layout_indexed.html">armnnUtils::DataLayoutIndexed</a></div><div class="ttdef"><b>Definition:</b> <a href="_data_layout_indexed_8hpp_source.html#l00017">DataLayoutIndexed.hpp:17</a></div></div> |
| 143 | <div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::Convolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation along x axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00434">Descriptors.hpp:434</a></div></div> |
| 144 | <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 & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00088">Tensor.hpp:88</a></div></div> |
| 145 | <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 & GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00063">Layer.cpp:63</a></div></div> |
| 146 | <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 & 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> |
| 147 | <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> |
| 148 | <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 & 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> |
| 149 | <div class="ttc" id="_convolution2d_layer_8hpp_html"><div class="ttname"><a href="_convolution2d_layer_8hpp.html">Convolution2dLayer.hpp</a></div></div> |
| 150 | <div class="ttc" id="namespacearmnn_html_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.html#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div> |
| 151 | </div><!-- fragment --></div><!-- contents --> |
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| 156 | <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.html">src</a></li><li class="navelem"><a class="el" href="dir_e0a84d05c80a2ef4231141dcbbeac5c8.html">armnn</a></li><li class="navelem"><a class="el" href="dir_9da6642ce0fd5a8c83524f1b621275be.html">layers</a></li><li class="navelem"><a class="el" href="_convolution2d_layer_8cpp.html">Convolution2dLayer.cpp</a></li> |
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| 161 | </div> |
| 162 | </body> |
| 163 | </html> |