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<div class="title">InferOutputTests.hpp</div> </div>
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<a href="_infer_output_tests_8hpp.xhtml">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">#pragma once</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_test_utils_8hpp.xhtml">TestUtils.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_graph_8hpp.xhtml">Graph.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_arg_min_max_layer_8hpp.xhtml">layers/ArgMinMaxLayer.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_batch_to_space_nd_layer_8hpp.xhtml">layers/BatchToSpaceNdLayer.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_space_to_depth_layer_8hpp.xhtml">layers/SpaceToDepthLayer.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_prelu_layer_8hpp.xhtml">layers/PreluLayer.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_stack_layer_8hpp.xhtml">layers/StackLayer.hpp</a>></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div><div class="line"><a name="l00019"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a673e4af24225bb5d4e5e502befdaf122"> 19</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a673e4af24225bb5d4e5e502befdaf122">ArgMinMaxInferOutputShapeImpl</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a> descriptor,</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape>& inputShapes,</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  std::vector<armnn::TensorShape>& outputShapes)</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> {</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keyword">auto</span> argMinMaxLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_arg_min_max_layer.xhtml">armnn::ArgMinMaxLayer</a>>(descriptor, <span class="stringliteral">"argMinMax"</span>);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  outputShapes = argMinMaxLayer-><a class="code" href="classarmnn_1_1_arg_min_max_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(inputShapes);</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"><a class="line" href="_infer_output_tests_8hpp.xhtml#a61f78d19deeaf960ac03ed4a7db98b8d"> 28</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a61f78d19deeaf960ac03ed4a7db98b8d">ArgMinMaxInferOutputShape4dTest</a>()</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> {</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a> descriptor;</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = 2;</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>  <span class="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  {</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  { 1, 3, 2, 4 }</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  };</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  std::vector<armnn::TensorShape> outputShapes;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a673e4af24225bb5d4e5e502befdaf122">ArgMinMaxInferOutputShapeImpl</a>(descriptor, inputShapes, outputShapes));</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> </div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedOutputShape( { 1, 3, 4 } );</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  BOOST_CHECK(outputShapes.size() == 1);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  BOOST_CHECK(outputShapes[0] == expectedOutputShape);</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> }</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00047"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a5eba187ee3dcec0db603b27b0954cec9"> 47</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a5eba187ee3dcec0db603b27b0954cec9">ArgMinMaxInferOutputShape3dTest</a>()</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a> descriptor;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = 0;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> </div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  {</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  { 1, 3, 2 }</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  };</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  std::vector<armnn::TensorShape> outputShapes;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a673e4af24225bb5d4e5e502befdaf122">ArgMinMaxInferOutputShapeImpl</a>(descriptor, inputShapes, outputShapes));</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedOutputShape( { 3, 2 } );</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  BOOST_CHECK(outputShapes.size() == 1);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  BOOST_CHECK(outputShapes[0] == expectedOutputShape);</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="_infer_output_tests_8hpp.xhtml#ae58e3f211ae2a124b13290c8b89aa87b"> 66</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#ae58e3f211ae2a124b13290c8b89aa87b">ArgMinMaxInferOutputShape2dTest</a>()</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> {</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a> descriptor;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = 1;</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="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</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>  { 3, 2 }</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>  std::vector<armnn::TensorShape> outputShapes;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a673e4af24225bb5d4e5e502befdaf122">ArgMinMaxInferOutputShapeImpl</a>(descriptor, inputShapes, outputShapes));</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedOutputShape( { 3 } );</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  BOOST_CHECK(outputShapes.size() == 1);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  BOOST_CHECK(outputShapes[0] == expectedOutputShape);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> }</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a005b7c03146e5a090de781966172c6e1"> 85</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a005b7c03146e5a090de781966172c6e1">ArgMinMaxInferOutputShape1dTest</a>()</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> {</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a> descriptor;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = 0;</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="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  {</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  { 5 }</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> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  std::vector<armnn::TensorShape> outputShapes;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a673e4af24225bb5d4e5e502befdaf122">ArgMinMaxInferOutputShapeImpl</a>(descriptor, inputShapes, outputShapes));</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedOutputShape( { 1 } );</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  BOOST_CHECK(outputShapes.size() == 1);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  BOOST_CHECK(outputShapes[0] == expectedOutputShape);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> }</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> </div><div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#aae03eed4bebaa0196f549e0e9b81f164"> 104</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#aae03eed4bebaa0196f549e0e9b81f164">BatchToSpaceInferOutputShapeTest</a>()</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> {</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</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="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">armnn::BatchToSpaceNdDescriptor</a> descriptor;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">m_BlockShape</a> = {2, 2};</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a3941f674c071c9503e00d2b59e92e454">m_Crops</a> = {{0, 0}, {2, 0}};</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  descriptor.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <a class="code" href="classarmnn_1_1_batch_to_space_nd_layer.xhtml">armnn::BatchToSpaceNdLayer</a>* <span class="keyword">const</span> batchToSpaceLayer =</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_batch_to_space_nd_layer.xhtml">armnn::BatchToSpaceNdLayer</a>>(descriptor, <span class="stringliteral">"batchToSpace"</span>);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> </div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  std::vector<armnn::TensorShape> shapes;</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keyword">const</span> std::vector<unsigned int> theDimSizes = {8, 1, 3, 1};</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> shape(4, theDimSizes.data());</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  shapes.push_back(shape);</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keyword">const</span> std::vector<unsigned int> expectedDimSizes = {2, 2, 4, 1};</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedShape(4, expectedDimSizes.data());</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  BOOST_CHECK(expectedShape == batchToSpaceLayer-><a class="code" href="classarmnn_1_1_batch_to_space_nd_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(shapes).at(0));</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> </div><div class="line"><a name="l00127"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#aee284f22b73268f00e5e9f57bc17c525"> 127</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#aee284f22b73268f00e5e9f57bc17c525">SpaceToDepthInferOutputShapeTest</a>()</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> {</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml">armnn::SpaceToDepthDescriptor</a> descriptor;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a> = 2;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  descriptor.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <a class="code" href="classarmnn_1_1_space_to_depth_layer.xhtml">armnn::SpaceToDepthLayer</a>* <span class="keyword">const</span> spaceToDepthLayer =</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_space_to_depth_layer.xhtml">armnn::SpaceToDepthLayer</a>>(descriptor, <span class="stringliteral">"spaceToDepth"</span>);</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>  std::vector<armnn::TensorShape> shapes;</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keyword">const</span> std::vector<unsigned int> dimSizes{ 1, 16, 8, 3 };</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> shape(4, dimSizes.data());</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  shapes.push_back(shape);</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="keyword">const</span> std::vector<unsigned int> expectedDimSizes{ 1, 8, 4, 12 };</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedShape(4, expectedDimSizes.data());</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>  BOOST_CHECK(expectedShape == spaceToDepthLayer-><a class="code" href="classarmnn_1_1_space_to_depth_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(shapes).at(0));</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> }</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a57ed098f3dd5d1a34fdb3ced4a5d73d8"> 149</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a57ed098f3dd5d1a34fdb3ced4a5d73d8">PreluInferOutputShapeImpl</a>(<span class="keyword">const</span> std::vector<armnn::TensorShape>& inputShapes,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  std::vector<armnn::TensorShape>& outputShapes)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <a class="code" href="classarmnn_1_1_prelu_layer.xhtml">armnn::PreluLayer</a>* <span class="keyword">const</span> preluLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_prelu_layer.xhtml">armnn::PreluLayer</a>>(<span class="stringliteral">"prelu"</span>);</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  outputShapes = preluLayer-><a class="code" href="classarmnn_1_1_prelu_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(inputShapes);</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span> }</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> </div><div class="line"><a name="l00157"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a23f861a85ba1016450691f7566eecfe2"> 157</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a23f861a85ba1016450691f7566eecfe2">PreluInferOutputShapeSameDimsTest</a>()</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> {</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  {</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  { 5, 1, 1, 7 }, <span class="comment">// Input shape</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  { 5, 4, 3, 1 } <span class="comment">// Alpha shape</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  };</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> expectedOutputShapes</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  {</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  { 5, 4, 3, 7 } <span class="comment">// Output shape</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  };</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> </div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  std::vector<armnn::TensorShape> outputShapes;</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a57ed098f3dd5d1a34fdb3ced4a5d73d8">PreluInferOutputShapeImpl</a>(inputShapes, outputShapes));</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  BOOST_CHECK(outputShapes.size() == 1);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  BOOST_CHECK(outputShapes[0] == expectedOutputShapes[0]);</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> }</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> </div><div class="line"><a name="l00177"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a9f353e3601ce891c0e0c2a3008b902e8"> 177</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a9f353e3601ce891c0e0c2a3008b902e8">PreluInferOutputShapeInputBiggerTest</a>()</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> {</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  {</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  { 4, 1, 4, 8 }, <span class="comment">// Input shape</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  { 5, 4, 1 } <span class="comment">// Alpha shape</span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  };</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> expectedOutputShapes</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  {</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  { 4, 5, 4, 8 } <span class="comment">// Output shape</span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  };</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> </div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  std::vector<armnn::TensorShape> outputShapes;</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a57ed098f3dd5d1a34fdb3ced4a5d73d8">PreluInferOutputShapeImpl</a>(inputShapes, outputShapes));</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> </div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  BOOST_CHECK(outputShapes.size() == 1);</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  BOOST_CHECK(outputShapes[0] == expectedOutputShapes[0]);</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> }</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00197"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a58a128d5e6ad6a3d1d393c2cf6b5fa63"> 197</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a58a128d5e6ad6a3d1d393c2cf6b5fa63">PreluInferOutputShapeAlphaBiggerTest</a>()</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> {</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  {</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  { 4, 1, 2 }, <span class="comment">// Input shape</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  { 5, 4, 3, 1 } <span class="comment">// Alpha shape</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  };</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> expectedOutputShapes</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  {</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  { 5, 4, 3, 2 } <span class="comment">// Output shape</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  };</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span> </div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  std::vector<armnn::TensorShape> outputShapes;</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a57ed098f3dd5d1a34fdb3ced4a5d73d8">PreluInferOutputShapeImpl</a>(inputShapes, outputShapes));</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  BOOST_CHECK(outputShapes.size() == 1);</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  BOOST_CHECK(outputShapes[0] == expectedOutputShapes[0]);</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> }</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> </div><div class="line"><a name="l00217"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a29704df6ecb907082856bbb7474f494e"> 217</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a29704df6ecb907082856bbb7474f494e">PreluInferOutputShapeNoMatchTest</a>()</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> {</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  {</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  { 4, 1, 2 }, <span class="comment">// Input shape</span></div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  { 5, 4, 3, 1 } <span class="comment">// Alpha shape</span></div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  };</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> </div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> expectedOutputShapes</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  {</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  { 5, 7, 3, 2 } <span class="comment">// Output shape</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  };</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> </div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  std::vector<armnn::TensorShape> outputShapes;</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a57ed098f3dd5d1a34fdb3ced4a5d73d8">PreluInferOutputShapeImpl</a>(inputShapes, outputShapes));</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> </div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  BOOST_CHECK(outputShapes.size() == 1);</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  BOOST_CHECK(outputShapes[0] != expectedOutputShapes[0]);</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> }</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div><div class="line"><a name="l00237"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#aef8723faea6131aaa1d535a17630df42"> 237</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#aef8723faea6131aaa1d535a17630df42">CreatePreluLayerHelper</a>(<a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a>& graph,</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& inputShape,</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& alphaShape,</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& outputShape)</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> {</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="comment">// Creates the PReLU layer</span></div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> preluLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_prelu_layer.xhtml">armnn::PreluLayer</a>>(<span class="stringliteral">"prelu"</span>);</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> </div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <span class="comment">// Creates extra layers</span></div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> input = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a>> (0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> alpha = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a>> (1, <span class="stringliteral">"alpha"</span>);</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">armnn::OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> </div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="comment">// Connects up</span></div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo (inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> alphaTensorInfo (alphaShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, preluLayer, inputTensorInfo, 0, 0);</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(alpha, preluLayer, alphaTensorInfo, 0, 1);</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(preluLayer, output, outputTensorInfo, 0, 0);</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> }</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> </div><div class="line"><a name="l00259"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a0e85eb8bf5d03adb0a5d86a37894a9ea"> 259</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a0e85eb8bf5d03adb0a5d86a37894a9ea">PreluValidateTensorShapesFromInputsMatchTest</a>()</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> {</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> </div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="comment">// Creates the PReLU layer</span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <a class="code" href="_infer_output_tests_8hpp.xhtml#aef8723faea6131aaa1d535a17630df42">CreatePreluLayerHelper</a>(graph, { 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 });</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> </div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="comment">// Graph::InferTensorInfos calls Layer::ValidateTensorShapesFromInputs</span></div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> }</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> </div><div class="line"><a name="l00270"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a88b77508b2bd69bcec713ef1ab436b8c"> 270</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a88b77508b2bd69bcec713ef1ab436b8c">PreluValidateTensorShapesFromInputsNoMatchTest</a>()</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> {</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> </div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="comment">// Creates the PReLU layer</span></div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <a class="code" href="_infer_output_tests_8hpp.xhtml#aef8723faea6131aaa1d535a17630df42">CreatePreluLayerHelper</a>(graph, { 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 7, 3, 2 });</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> </div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="comment">// Graph::InferTensorInfos calls Layer::ValidateTensorShapesFromInputs</span></div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  BOOST_CHECK_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>(), <a class="code" href="classarmnn_1_1_layer_validation_exception.xhtml">armnn::LayerValidationException</a>);</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> }</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> </div><div class="line"><a name="l00281"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a2985b2f0f61fcad5f75e5119e7b9916e"> 281</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a2985b2f0f61fcad5f75e5119e7b9916e">StackInferOutputShapeImpl</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a> descriptor,</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape>& inputShapes,</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  std::vector<armnn::TensorShape>& outputShapes)</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> {</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <a class="code" href="classarmnn_1_1_stack_layer.xhtml">armnn::StackLayer</a>* <span class="keyword">const</span> stackLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_stack_layer.xhtml">armnn::StackLayer</a>>(descriptor, <span class="stringliteral">"stack"</span>);</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  outputShapes = stackLayer-><a class="code" href="classarmnn_1_1_stack_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(inputShapes);</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> }</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> </div><div class="line"><a name="l00290"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#abd1bb9e1b7783eccf8dca20d455064a3"> 290</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#abd1bb9e1b7783eccf8dca20d455064a3">StackInferOutputShapeFromInputsMatchTest</a>()</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> {</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> </div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a> descriptor;</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#ab218de7805899c8412d75d1fd1d846d2">m_Axis</a> = 1;</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">m_NumInputs</a> = 3;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#a2bea87b470268bb0b73457c3733dbc04">m_InputShape</a> = <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  (</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  { 4, 2 } <span class="comment">// Defined input shape</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  );</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> </div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  {</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  { 4, 2 }, <span class="comment">// Actual input shapes</span></div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  { 4, 2 },</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  { 4, 2 }</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  };</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> </div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  std::vector<armnn::TensorShape> outputShapes;</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a2985b2f0f61fcad5f75e5119e7b9916e">StackInferOutputShapeImpl</a>(descriptor, inputShapes, outputShapes));</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> </div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedOutputShape</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  (</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  { 4, 3, 2 }</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  );</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  BOOST_CHECK(outputShapes.size() == 1);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  BOOST_CHECK(outputShapes[0] == expectedOutputShape);</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> }</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> </div><div class="line"><a name="l00320"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a9195d0488c41fb4a5967f8a2c5bdb6e9"> 320</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a9195d0488c41fb4a5967f8a2c5bdb6e9">StackInferOutputShapeFromInputsNoMatchTest</a>()</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> {</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> </div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a> descriptor;</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#ab218de7805899c8412d75d1fd1d846d2">m_Axis</a> = 1;</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">m_NumInputs</a> = 3;</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#a2bea87b470268bb0b73457c3733dbc04">m_InputShape</a> = <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  (</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  { 4, 2 } <span class="comment">// Defined input shape</span></div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  );</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> </div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  {</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  { 4, 2 }, <span class="comment">// Actual input shapes</span></div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  { 4, 5 }, <span class="comment">// Incorrectly shaped input tensor</span></div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  { 4, 2 }</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  };</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> </div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="comment">// Output shape is inferred from the descriptor, so should still be correct despite mismatching input shapes</span></div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  std::vector<armnn::TensorShape> outputShapes;</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a2985b2f0f61fcad5f75e5119e7b9916e">StackInferOutputShapeImpl</a>(descriptor, inputShapes, outputShapes));</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span> </div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedOutputShape</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  (</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  { 4, 3, 2 }</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  );</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  BOOST_CHECK(outputShapes.size() == 1);</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  BOOST_CHECK(outputShapes[0] == expectedOutputShape);</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> }</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span> </div><div class="line"><a name="l00351"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#adad94ff1ff901704556db7b602d46a05"> 351</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#adad94ff1ff901704556db7b602d46a05">CreateStackLayerHelper</a>(<a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a>& graph,</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a>& descriptor,</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape>& inputShapes,</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& outputShape)</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> {</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="comment">// Creates the Stack layer</span></div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> stackLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_stack_layer.xhtml">armnn::StackLayer</a>>(descriptor, <span class="stringliteral">"stack"</span>);</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> </div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="comment">// Creates extra layers</span></div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  std::vector<armnn::Layer*> inputs;</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<inputShapes.size(); ++i)</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  {</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  inputs.push_back(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a>>(static_cast<int>(i), <span class="stringliteral">"input"</span>));</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  }</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">armnn::Layer</a>* <span class="keyword">const</span> output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_output_layer.xhtml">armnn::OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span> </div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="comment">// Connects up</span></div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  std::vector<armnn::TensorInfo> inputTensorInfos;</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<inputs.size(); ++i)</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  {</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  inputTensorInfos.push_back(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(inputShapes[i], <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  }</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> </div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i=0; i<inputs.size(); ++i)</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  {</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(inputs[i], stackLayer, inputTensorInfos[i], 0, i);</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  }</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(stackLayer, output, outputTensorInfo, 0, 0);</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> }</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span> </div><div class="line"><a name="l00382"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a9a2a494f5a3ff1885fa9d62c6c500e52"> 382</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a9a2a494f5a3ff1885fa9d62c6c500e52">StackValidateTensorShapesFromInputsMatchTest</a>()</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> {</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> </div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a> descriptor;</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#ab218de7805899c8412d75d1fd1d846d2">m_Axis</a> = 0;</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">m_NumInputs</a> = 3;</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#a2bea87b470268bb0b73457c3733dbc04">m_InputShape</a> = <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  (</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  { 2, 5 } <span class="comment">// Defined input shape</span></div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  );</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> </div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  {</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  { 2, 5 }, <span class="comment">// Actual input shapes</span></div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  { 2, 5 },</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  { 2, 5 }</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  };</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span> </div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="comment">// Creates the Stack layer</span></div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <a class="code" href="_infer_output_tests_8hpp.xhtml#adad94ff1ff901704556db7b602d46a05">CreateStackLayerHelper</a>(graph, descriptor, inputShapes, { 3, 2, 5 });</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span> </div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="comment">// Graph::InferTensorInfos calls Layer::ValidateTensorShapesFromInputs</span></div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  BOOST_CHECK_NO_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>());</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span> }</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span> </div><div class="line"><a name="l00408"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#af061819a84da0c72056b016d02d239f3"> 408</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#af061819a84da0c72056b016d02d239f3">StackValidateTensorShapesFromInputsNoMatchTest</a>()</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> {</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> </div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a> descriptor;</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#ab218de7805899c8412d75d1fd1d846d2">m_Axis</a> = 0;</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">m_NumInputs</a> = 3;</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  descriptor.<a class="code" href="structarmnn_1_1_stack_descriptor.xhtml#a2bea87b470268bb0b73457c3733dbc04">m_InputShape</a> = <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  (</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  { 2, 5 } <span class="comment">// Defined input shape</span></div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  );</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> </div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape> inputShapes</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  {</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  { 2, 5 }, <span class="comment">// Actual input shapes</span></div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  { 2, 2 }, <span class="comment">// Incorrectly shaped input tensor</span></div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  { 2, 5 }</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  };</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> </div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <span class="comment">// Creates the Stack layer</span></div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <a class="code" href="_infer_output_tests_8hpp.xhtml#adad94ff1ff901704556db7b602d46a05">CreateStackLayerHelper</a>(graph, descriptor, inputShapes, { 3, 2, 5 });</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span> </div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="comment">// Graph::InferTensorInfos calls Layer::ValidateTensorShapesFromInputs</span></div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  BOOST_CHECK_THROW(graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">InferTensorInfos</a>(), <a class="code" href="classarmnn_1_1_layer_validation_exception.xhtml">armnn::LayerValidationException</a>);</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span> }</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span> </div><div class="line"><a name="l00434"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a3f1ec6ab0066448f4438bbe852b4f3e2"> 434</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a3f1ec6ab0066448f4438bbe852b4f3e2">Convolution2dInferOutputShapeTest</a>()</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span> {</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span> </div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = 2;</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = 2;</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 1;</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 1;</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 1;</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 1;</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 3;</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 3;</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span> </div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">armnn::Convolution2dLayer</a>* <span class="keyword">const</span> convolution2dLayer =</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">armnn::Convolution2dLayer</a>>(descriptor, <span class="stringliteral">"convolution2d"</span>);</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> </div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  std::vector<armnn::TensorShape> shapes;</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="keyword">const</span> std::vector<unsigned int> inputSize = {1, 2, 10, 10};</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputShape(4, inputSize.data());</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  shapes.push_back(inputShape);</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="keyword">const</span> std::vector<unsigned int> filterSize = { 1, 2, 2, 2};</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> filterShape(4, filterSize.data());</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  shapes.push_back(filterShape);</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span> </div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <span class="keyword">const</span> std::vector<unsigned int> expectedOutputSizes = {1, 1, 4, 4};</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedOutputShape(4, expectedOutputSizes.data());</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span> </div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  BOOST_CHECK(expectedOutputShape == convolution2dLayer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(shapes).at(0));</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span> }</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span> </div><div class="line"><a name="l00467"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#af74f1701b2b4a9313a682ab673edf2f5"> 467</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#af74f1701b2b4a9313a682ab673edf2f5">TransposeConvolution2dInferOutputShapeTest</a>()</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span> {</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span> </div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">armnn::TransposeConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 0;</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 1;</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 0;</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 1;</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span> </div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <a class="code" href="classarmnn_1_1_transpose_convolution2d_layer.xhtml">armnn::TransposeConvolution2dLayer</a>* <span class="keyword">const</span> transposeConvolution2dLayer =</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_transpose_convolution2d_layer.xhtml">armnn::TransposeConvolution2dLayer</a>>(descriptor, <span class="stringliteral">"TransposeConvolution2d"</span>);</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span> </div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  std::vector<armnn::TensorShape> shapes;</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="keyword">const</span> std::vector<unsigned int> inputSize = {1, 2, 3, 3};</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputShape(4, inputSize.data());</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  shapes.push_back(inputShape);</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span> </div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <span class="keyword">const</span> std::vector<unsigned int> filterSize = { 1, 2, 3, 3};</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> filterShape(4, filterSize.data());</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  shapes.push_back(filterShape);</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span> </div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <span class="keyword">const</span> std::vector<unsigned int> expectedOutputSizes = {1, 1, 6, 6};</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedOutputShape(4, expectedOutputSizes.data());</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span> </div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  BOOST_CHECK(expectedOutputShape == transposeConvolution2dLayer-><a class="code" href="classarmnn_1_1_transpose_convolution2d_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(shapes).at(0));</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span> }</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span> </div><div class="line"><a name="l00498"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a0443e325bae088a453cef63002516742"> 498</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a0443e325bae088a453cef63002516742">DepthwiseConvolution2dInferOutputShapeTest</a>()</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span> {</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span> </div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a> = 3;</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a> = 3;</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 1;</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 2;</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 1;</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 2;</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 2;</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span> </div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">armnn::DepthwiseConvolution2dLayer</a>* <span class="keyword">const</span> depthwiseConvolution2dLayer =</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">armnn::DepthwiseConvolution2dLayer</a>>(descriptor, <span class="stringliteral">"DepthwiseConvolution2d"</span>);</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span> </div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  std::vector<armnn::TensorShape> shapes;</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <span class="keyword">const</span> std::vector<unsigned int> inputSize = {1, 2, 10, 10};</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputShape(4, inputSize.data());</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  shapes.push_back(inputShape);</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span> </div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <span class="keyword">const</span> std::vector<unsigned int> filterSize = { 1, 2, 3, 3};</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> filterShape(4, filterSize.data());</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  shapes.push_back(filterShape);</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span> </div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  <span class="keyword">const</span> std::vector<unsigned int> expectedOutputSizes = {1, 2, 4, 4};</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> expectedOutputShape(4, expectedOutputSizes.data());</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span> </div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  BOOST_CHECK(expectedOutputShape == depthwiseConvolution2dLayer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(shapes).at(0));</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span> }</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span> </div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span> <span class="comment">// QLstm</span></div><div class="line"><a name="l00532"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a07bb1afd2b46d4bf83bab05ef89fc154"> 532</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a07bb1afd2b46d4bf83bab05ef89fc154">QLstmInferOutputShapeImpl</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml">armnn::QLstmDescriptor</a> descriptor,</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="keyword">const</span> std::vector<armnn::TensorShape>& inputShapes,</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  std::vector<armnn::TensorShape>& outputShapes)</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span> {</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  <a class="code" href="classarmnn_1_1_q_lstm_layer.xhtml">armnn::QLstmLayer</a>* <span class="keyword">const</span> qLstmLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_q_lstm_layer.xhtml">armnn::QLstmLayer</a>>(descriptor, <span class="stringliteral">"qLstm"</span>);</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  outputShapes = qLstmLayer-><a class="code" href="classarmnn_1_1_q_lstm_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(inputShapes);</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span> }</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span> </div><div class="line"><a name="l00541"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a9c7ba1f02c1532cf22a54f624aa6fd4e"> 541</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a9c7ba1f02c1532cf22a54f624aa6fd4e">QLstmInferOutputShapeTest</a>()</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span> {</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  <a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml">armnn::QLstmDescriptor</a> descriptor;</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  descriptor.<a class="code" href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span> </div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <span class="comment">// Input shapes</span></div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <span class="keyword">const</span> std::vector<unsigned int> inputShape{ 2, 5 };</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <span class="keyword">const</span> std::vector<unsigned int> previousOutputInShape{ 2, 4 };</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  <span class="keyword">const</span> std::vector<unsigned int> previousCellStateInShape{ 2, 4 };</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span> </div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputTensorShape(2, inputShape.data());</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> previousOutputInTensorShape(2, previousOutputInShape.data());</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> previousCellStateInTensorShape(2, previousCellStateInShape.data());</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span> </div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  std::vector<armnn::TensorShape> inShapes</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  {</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  inputTensorShape,</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  previousOutputInTensorShape,</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  previousCellStateInTensorShape</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  };</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span> </div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  <span class="comment">// Output shapes</span></div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <span class="keyword">const</span> std::vector<unsigned int> outputStateOutShape{ 2, 4 };</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <span class="keyword">const</span> std::vector<unsigned int> cellStateOutShape{ 2, 4 };</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="keyword">const</span> std::vector<unsigned int> outputShape{ 2, 4 };</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> outputStateOutTensorShape(2, outputShape.data());</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> cellStateOutTensorShape(2, cellStateOutShape.data());</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> outputTensorShape(2, outputShape.data());</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span> </div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  std::vector<armnn::TensorShape> expectedOutShapes</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  {</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  outputStateOutTensorShape,</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  cellStateOutTensorShape,</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  outputTensorShape</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  };</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span> </div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  std::vector<armnn::TensorShape> actualOutShapes;</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a07bb1afd2b46d4bf83bab05ef89fc154">QLstmInferOutputShapeImpl</a>(descriptor, inShapes, actualOutShapes));</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span> </div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  BOOST_CHECK(actualOutShapes.size() == 3);</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  BOOST_CHECK(expectedOutShapes[0] == actualOutShapes[0]);</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  BOOST_CHECK(expectedOutShapes[1] == actualOutShapes[1]);</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  BOOST_CHECK(expectedOutShapes[2] == actualOutShapes[2]);</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span> }</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span> </div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span> <span class="comment">// QuantizedLstm</span></div><div class="line"><a name="l00589"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a4a13b517c2553b8173c26d286cba4a13"> 589</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a4a13b517c2553b8173c26d286cba4a13">QuantizedLstmInferOutputShapeImpl</a>(<span class="keyword">const</span> std::vector<armnn::TensorShape>& inputShapes,</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  std::vector<armnn::TensorShape>& outputShapes)</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span> {</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml">armnn::QuantizedLstmLayer</a>* <span class="keyword">const</span> quantizedLstmLayer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml">armnn::QuantizedLstmLayer</a>>(<span class="stringliteral">"quantizedLstm"</span>);</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  outputShapes = quantizedLstmLayer-><a class="code" href="classarmnn_1_1_quantized_lstm_layer.xhtml#a65ca562c882ad619684445a1402f415a">InferOutputShapes</a>(inputShapes);</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span> }</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span> </div><div class="line"><a name="l00597"></a><span class="lineno"><a class="line" href="_infer_output_tests_8hpp.xhtml#a4e21fe15b65644bb6a7beb25fbd04f14"> 597</a></span> <span class="keywordtype">void</span> <a class="code" href="_infer_output_tests_8hpp.xhtml#a4e21fe15b65644bb6a7beb25fbd04f14">QuantizedLstmInferOutputShapeTest</a>()</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span> {</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <span class="comment">// Input shapes</span></div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keyword">const</span> std::vector<unsigned int> inputShape{ 2, 5 };</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <span class="keyword">const</span> std::vector<unsigned int> previousCellStateInShape{ 2, 10 };</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  <span class="keyword">const</span> std::vector<unsigned int> previousOutputInShape{ 2, 10 };</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> inputTensorShape(2, inputShape.data());</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> previousCellStateInTensorShape(2, previousCellStateInShape.data());</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> previousOutputInTensorShape(2, previousOutputInShape.data());</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span> </div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  std::vector<armnn::TensorShape> inShapes</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  {</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  inputTensorShape,</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  previousCellStateInTensorShape,</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  previousOutputInTensorShape</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  };</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span> </div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  <span class="comment">// Output shapes</span></div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  <span class="keyword">const</span> std::vector<unsigned int> cellStateOutShape{ 2, 10 };</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <span class="keyword">const</span> std::vector<unsigned int> outputShape{ 2, 10 };</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> cellStateOutTensorShape(2, cellStateOutShape.data());</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> outputTensorShape(2, outputShape.data());</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span> </div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  std::vector<armnn::TensorShape> expectedOutShapes</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  {</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  cellStateOutTensorShape,</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  outputTensorShape</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  };</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span> </div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  std::vector<armnn::TensorShape> actualOutShapes;</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  BOOST_CHECK_NO_THROW(<a class="code" href="_infer_output_tests_8hpp.xhtml#a4a13b517c2553b8173c26d286cba4a13">QuantizedLstmInferOutputShapeImpl</a>(inShapes, actualOutShapes));</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span> </div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  BOOST_CHECK(actualOutShapes.size() == 2);</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  BOOST_CHECK(expectedOutShapes[0] == actualOutShapes[0]);</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  BOOST_CHECK(expectedOutShapes[1] == actualOutShapes[1]);</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span> }</div><div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00444">Descriptors.hpp:444</a></div></div>
<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::DepthwiseConvolution2dLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8cpp_source.xhtml#l00085">DepthwiseConvolution2dLayer.cpp:85</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a2985b2f0f61fcad5f75e5119e7b9916e"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a2985b2f0f61fcad5f75e5119e7b9916e">StackInferOutputShapeImpl</a></div><div class="ttdeci">void StackInferOutputShapeImpl(const armnn::StackDescriptor descriptor, const std::vector< armnn::TensorShape > &inputShapes, std::vector< armnn::TensorShape > &outputShapes)</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00281">InferOutputTests.hpp:281</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00456">Descriptors.hpp:456</a></div></div>
<div class="ttc" id="structarmnn_1_1_stack_descriptor_xhtml_ab218de7805899c8412d75d1fd1d846d2"><div class="ttname"><a href="structarmnn_1_1_stack_descriptor.xhtml#ab218de7805899c8412d75d1fd1d846d2">armnn::StackDescriptor::m_Axis</a></div><div class="ttdeci">uint32_t m_Axis</div><div class="ttdoc">0-based axis along which to stack the input tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01046">Descriptors.hpp:1046</a></div></div>
<div class="ttc" id="classarmnn_1_1_batch_to_space_nd_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_batch_to_space_nd_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::BatchToSpaceNdLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_layer_8cpp_source.xhtml#l00060">BatchToSpaceNdLayer.cpp:60</a></div></div>
<div class="ttc" id="classarmnn_1_1_transpose_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_transpose_convolution2d_layer.xhtml">armnn::TransposeConvolution2dLayer</a></div><div class="ttdoc">This layer represents a 2D transpose convolution operation. </div><div class="ttdef"><b>Definition:</b> <a href="_transpose_convolution2d_layer_8hpp_source.xhtml#l00015">TransposeConvolution2dLayer.hpp:15</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a4e21fe15b65644bb6a7beb25fbd04f14"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a4e21fe15b65644bb6a7beb25fbd04f14">QuantizedLstmInferOutputShapeTest</a></div><div class="ttdeci">void QuantizedLstmInferOutputShapeTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00597">InferOutputTests.hpp:597</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01213">Descriptors.hpp:1213</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::DepthwiseConvolution2dDescriptor::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.xhtml#l00496">Descriptors.hpp:496</a></div></div>
<div class="ttc" id="classarmnn_1_1_stack_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_stack_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::StackLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_stack_layer_8cpp_source.xhtml#l00035">StackLayer.cpp:35</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::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.xhtml#l00508">Descriptors.hpp:508</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#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">armnn::DepthwiseConvolution2dLayer</a></div><div class="ttdoc">This layer represents a depthwise convolution 2d operation. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.xhtml#l00015">DepthwiseConvolution2dLayer.hpp:15</a></div></div>
<div class="ttc" id="structarmnn_1_1_stack_descriptor_xhtml_a2bea87b470268bb0b73457c3733dbc04"><div class="ttname"><a href="structarmnn_1_1_stack_descriptor.xhtml#a2bea87b470268bb0b73457c3733dbc04">armnn::StackDescriptor::m_InputShape</a></div><div class="ttdeci">TensorShape m_InputShape</div><div class="ttdoc">Required shape of all input tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01050">Descriptors.hpp:1050</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &&... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00402">Graph.hpp:402</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a0e85eb8bf5d03adb0a5d86a37894a9ea"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a0e85eb8bf5d03adb0a5d86a37894a9ea">PreluValidateTensorShapesFromInputsMatchTest</a></div><div class="ttdeci">void PreluValidateTensorShapesFromInputsMatchTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00259">InferOutputTests.hpp:259</a></div></div>
<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::QLstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01193">Descriptors.hpp:1193</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00408">Descriptors.hpp:408</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::DepthwiseConvolution2dDescriptor::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.xhtml#l00490">Descriptors.hpp:490</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a005b7c03146e5a090de781966172c6e1"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a005b7c03146e5a090de781966172c6e1">ArgMinMaxInferOutputShape1dTest</a></div><div class="ttdeci">void ArgMinMaxInferOutputShape1dTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00085">InferOutputTests.hpp:85</a></div></div>
<div class="ttc" id="classarmnn_1_1_space_to_depth_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_space_to_depth_layer.xhtml">armnn::SpaceToDepthLayer</a></div><div class="ttdoc">This layer represents a SpaceToDepth operation. </div><div class="ttdef"><b>Definition:</b> <a href="_space_to_depth_layer_8hpp_source.xhtml#l00014">SpaceToDepthLayer.hpp:14</a></div></div>
<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::BatchToSpaceNdDescriptor::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.xhtml#l00700">Descriptors.hpp:700</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a9f353e3601ce891c0e0c2a3008b902e8"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a9f353e3601ce891c0e0c2a3008b902e8">PreluInferOutputShapeInputBiggerTest</a></div><div class="ttdeci">void PreluInferOutputShapeInputBiggerTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00177">InferOutputTests.hpp:177</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00440">Descriptors.hpp:440</a></div></div>
<div class="ttc" id="_test_utils_8hpp_xhtml"><div class="ttname"><a href="_test_utils_8hpp.xhtml">TestUtils.hpp</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_af74f1701b2b4a9313a682ab673edf2f5"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#af74f1701b2b4a9313a682ab673edf2f5">TransposeConvolution2dInferOutputShapeTest</a></div><div class="ttdeci">void TransposeConvolution2dInferOutputShapeTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00467">InferOutputTests.hpp:467</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a61f78d19deeaf960ac03ed4a7db98b8d"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a61f78d19deeaf960ac03ed4a7db98b8d">ArgMinMaxInferOutputShape4dTest</a></div><div class="ttdeci">void ArgMinMaxInferOutputShape4dTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00028">InferOutputTests.hpp:28</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::TransposeConvolution2dDescriptor::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.xhtml#l01248">Descriptors.hpp:1248</a></div></div>
<div class="ttc" id="_batch_to_space_nd_layer_8hpp_xhtml"><div class="ttname"><a href="_batch_to_space_nd_layer_8hpp.xhtml">BatchToSpaceNdLayer.hpp</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="structarmnn_1_1_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00452">Descriptors.hpp:452</a></div></div>
<div class="ttc" id="structarmnn_1_1_space_to_depth_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml">armnn::SpaceToDepthDescriptor</a></div><div class="ttdoc">A SpaceToDepthDescriptor for the SpaceToDepthLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00884">Descriptors.hpp:884</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::DepthwiseConvolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation factor value for height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00504">Descriptors.hpp:504</a></div></div>
<div class="ttc" id="_arg_min_max_layer_8hpp_xhtml"><div class="ttname"><a href="_arg_min_max_layer_8hpp.xhtml">ArgMinMaxLayer.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">armnn::BatchToSpaceNdDescriptor</a></div><div class="ttdoc">A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00673">Descriptors.hpp:673</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a0443e325bae088a453cef63002516742"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a0443e325bae088a453cef63002516742">DepthwiseConvolution2dInferOutputShapeTest</a></div><div class="ttdeci">void DepthwiseConvolution2dInferOutputShapeTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00498">InferOutputTests.hpp:498</a></div></div>
<div class="ttc" id="structarmnn_1_1_stack_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a></div><div class="ttdoc">A StackDescriptor for the StackLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01024">Descriptors.hpp:1024</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00442">Descriptors.hpp:442</a></div></div>
<div class="ttc" id="_prelu_layer_8hpp_xhtml"><div class="ttname"><a href="_prelu_layer_8hpp.xhtml">PreluLayer.hpp</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a58a128d5e6ad6a3d1d393c2cf6b5fa63"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a58a128d5e6ad6a3d1d393c2cf6b5fa63">PreluInferOutputShapeAlphaBiggerTest</a></div><div class="ttdeci">void PreluInferOutputShapeAlphaBiggerTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00197">InferOutputTests.hpp:197</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a9a2a494f5a3ff1885fa9d62c6c500e52"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a9a2a494f5a3ff1885fa9d62c6c500e52">StackValidateTensorShapesFromInputsMatchTest</a></div><div class="ttdeci">void StackValidateTensorShapesFromInputsMatchTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00382">InferOutputTests.hpp:382</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a9195d0488c41fb4a5967f8a2c5bdb6e9"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a9195d0488c41fb4a5967f8a2c5bdb6e9">StackInferOutputShapeFromInputsNoMatchTest</a></div><div class="ttdeci">void StackInferOutputShapeFromInputsNoMatchTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00320">InferOutputTests.hpp:320</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00446">Descriptors.hpp:446</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::DepthwiseConvolution2dDescriptor::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.xhtml#l00498">Descriptors.hpp:498</a></div></div>
<div class="ttc" id="classarmnn_1_1_output_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_output_layer.xhtml">armnn::OutputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_output_layer_8hpp_source.xhtml#l00013">OutputLayer.hpp:13</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_adad94ff1ff901704556db7b602d46a05"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#adad94ff1ff901704556db7b602d46a05">CreateStackLayerHelper</a></div><div class="ttdeci">void CreateStackLayerHelper(armnn::Graph &graph, const armnn::StackDescriptor &descriptor, const std::vector< armnn::TensorShape > &inputShapes, const armnn::TensorShape &outputShape)</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00351">InferOutputTests.hpp:351</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_aee284f22b73268f00e5e9f57bc17c525"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#aee284f22b73268f00e5e9f57bc17c525">SpaceToDepthInferOutputShapeTest</a></div><div class="ttdeci">void SpaceToDepthInferOutputShapeTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00127">InferOutputTests.hpp:127</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_aae03eed4bebaa0196f549e0e9b81f164"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#aae03eed4bebaa0196f549e0e9b81f164">BatchToSpaceInferOutputShapeTest</a></div><div class="ttdeci">void BatchToSpaceInferOutputShapeTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00104">InferOutputTests.hpp:104</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::DepthwiseConvolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation factor value for width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00502">Descriptors.hpp:502</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::DepthwiseConvolution2dDescriptor::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.xhtml#l00494">Descriptors.hpp:494</a></div></div>
<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml">armnn::QuantizedLstmLayer</a></div><div class="ttdoc">This layer represents a QuantizedLstm operation. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8hpp_source.xhtml#l00045">QuantizedLstmLayer.hpp:45</a></div></div>
<div class="ttc" id="classarmnn_1_1_prelu_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_prelu_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::PreluLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_prelu_layer_8cpp_source.xhtml#l00038">PreluLayer.cpp:38</a></div></div>
<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a02e143524aefddd40b485fcf7dea6696"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a02e143524aefddd40b485fcf7dea6696">armnn::BatchToSpaceNdDescriptor::m_BlockShape</a></div><div class="ttdeci">std::vector< unsigned int > m_BlockShape</div><div class="ttdoc">Block shape values. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00696">Descriptors.hpp:696</a></div></div>
<div class="ttc" id="_graph_8hpp_xhtml"><div class="ttname"><a href="_graph_8hpp.xhtml">Graph.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_arg_min_max_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a></div><div class="ttdoc">An ArgMinMaxDescriptor for ArgMinMaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00056">Descriptors.hpp:56</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_aef8723faea6131aaa1d535a17630df42"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#aef8723faea6131aaa1d535a17630df42">CreatePreluLayerHelper</a></div><div class="ttdeci">void CreatePreluLayerHelper(armnn::Graph &graph, const armnn::TensorShape &inputShape, const armnn::TensorShape &alphaShape, const armnn::TensorShape &outputShape)</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00237">InferOutputTests.hpp:237</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="classarmnn_1_1_stack_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_stack_layer.xhtml">armnn::StackLayer</a></div><div class="ttdoc">This layer represents a stack operation. </div><div class="ttdef"><b>Definition:</b> <a href="_stack_layer_8hpp_source.xhtml#l00013">StackLayer.hpp:13</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a3f1ec6ab0066448f4438bbe852b4f3e2"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a3f1ec6ab0066448f4438bbe852b4f3e2">Convolution2dInferOutputShapeTest</a></div><div class="ttdeci">void Convolution2dInferOutputShapeTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00434">InferOutputTests.hpp:434</a></div></div>
<div class="ttc" id="classarmnn_1_1_batch_to_space_nd_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_batch_to_space_nd_layer.xhtml">armnn::BatchToSpaceNdLayer</a></div><div class="ttdoc">This layer represents a BatchToSpaceNd operation. </div><div class="ttdef"><b>Definition:</b> <a href="_batch_to_space_nd_layer_8hpp_source.xhtml#l00013">BatchToSpaceNdLayer.hpp:13</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a5eba187ee3dcec0db603b27b0954cec9"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a5eba187ee3dcec0db603b27b0954cec9">ArgMinMaxInferOutputShape3dTest</a></div><div class="ttdeci">void ArgMinMaxInferOutputShape3dTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00047">InferOutputTests.hpp:47</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::TransposeConvolution2dDescriptor::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.xhtml#l01246">Descriptors.hpp:1246</a></div></div>
<div class="ttc" id="classarmnn_1_1_arg_min_max_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_arg_min_max_layer.xhtml">armnn::ArgMinMaxLayer</a></div><div class="ttdoc">This layer represents a ArgMinMax operation. </div><div class="ttdef"><b>Definition:</b> <a href="_arg_min_max_layer_8hpp_source.xhtml#l00014">ArgMinMaxLayer.hpp:14</a></div></div>
<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml">armnn::QLstmDescriptor</a></div><div class="ttdoc">A QLstmDescriptor for the QLstmLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01153">Descriptors.hpp:1153</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a07bb1afd2b46d4bf83bab05ef89fc154"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a07bb1afd2b46d4bf83bab05ef89fc154">QLstmInferOutputShapeImpl</a></div><div class="ttdeci">void QLstmInferOutputShapeImpl(const armnn::QLstmDescriptor descriptor, const std::vector< armnn::TensorShape > &inputShapes, std::vector< armnn::TensorShape > &outputShapes)</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00532">InferOutputTests.hpp:532</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a673e4af24225bb5d4e5e502befdaf122"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a673e4af24225bb5d4e5e502befdaf122">ArgMinMaxInferOutputShapeImpl</a></div><div class="ttdeci">void ArgMinMaxInferOutputShapeImpl(const armnn::ArgMinMaxDescriptor descriptor, const std::vector< armnn::TensorShape > &inputShapes, std::vector< armnn::TensorShape > &outputShapes)</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00019">InferOutputTests.hpp:19</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::TransposeConvolution2dDescriptor::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.xhtml#l01256">Descriptors.hpp:1256</a></div></div>
<div class="ttc" id="structarmnn_1_1_stack_descriptor_xhtml_aed6086070440ceb94129bef06f70173f"><div class="ttname"><a href="structarmnn_1_1_stack_descriptor.xhtml#aed6086070440ceb94129bef06f70173f">armnn::StackDescriptor::m_NumInputs</a></div><div class="ttdeci">uint32_t m_NumInputs</div><div class="ttdoc">Number of input tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01048">Descriptors.hpp:1048</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a4a13b517c2553b8173c26d286cba4a13"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a4a13b517c2553b8173c26d286cba4a13">QuantizedLstmInferOutputShapeImpl</a></div><div class="ttdeci">void QuantizedLstmInferOutputShapeImpl(const std::vector< armnn::TensorShape > &inputShapes, std::vector< armnn::TensorShape > &outputShapes)</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00589">InferOutputTests.hpp:589</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00448">Descriptors.hpp:448</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="structarmnn_1_1_space_to_depth_descriptor_xhtml_a6c6b8957f1e176867e5fb05b1a1a1486"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">armnn::SpaceToDepthDescriptor::m_BlockSize</a></div><div class="ttdeci">unsigned int m_BlockSize</div><div class="ttdoc">Scalar specifying the input block size. It must be >= 1. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00901">Descriptors.hpp:901</a></div></div>
<div class="ttc" id="classarmnn_1_1_q_lstm_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_q_lstm_layer.xhtml">armnn::QLstmLayer</a></div><div class="ttdoc">This layer represents a QLstm operation. </div><div class="ttdef"><b>Definition:</b> <a href="_q_lstm_layer_8hpp_source.xhtml#l00079">QLstmLayer.hpp:79</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00450">Descriptors.hpp:450</a></div></div>
<div class="ttc" id="structarmnn_1_1_space_to_depth_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::SpaceToDepthDescriptor::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.xhtml#l00904">Descriptors.hpp:904</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a23f861a85ba1016450691f7566eecfe2"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a23f861a85ba1016450691f7566eecfe2">PreluInferOutputShapeSameDimsTest</a></div><div class="ttdeci">void PreluInferOutputShapeSameDimsTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00157">InferOutputTests.hpp:157</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::TransposeConvolution2dDescriptor::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.xhtml#l01242">Descriptors.hpp:1242</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::TransposeConvolution2dDescriptor::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.xhtml#l01250">Descriptors.hpp:1250</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_af061819a84da0c72056b016d02d239f3"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#af061819a84da0c72056b016d02d239f3">StackValidateTensorShapesFromInputsNoMatchTest</a></div><div class="ttdeci">void StackValidateTensorShapesFromInputsNoMatchTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00408">InferOutputTests.hpp:408</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::DepthwiseConvolution2dDescriptor::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.xhtml#l00500">Descriptors.hpp:500</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a57ed098f3dd5d1a34fdb3ced4a5d73d8"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a57ed098f3dd5d1a34fdb3ced4a5d73d8">PreluInferOutputShapeImpl</a></div><div class="ttdeci">void PreluInferOutputShapeImpl(const std::vector< armnn::TensorShape > &inputShapes, std::vector< armnn::TensorShape > &outputShapes)</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00149">InferOutputTests.hpp:149</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::TransposeConvolution2dDescriptor::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.xhtml#l01252">Descriptors.hpp:1252</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a88b77508b2bd69bcec713ef1ab436b8c"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a88b77508b2bd69bcec713ef1ab436b8c">PreluValidateTensorShapesFromInputsNoMatchTest</a></div><div class="ttdeci">void PreluValidateTensorShapesFromInputsNoMatchTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00270">InferOutputTests.hpp:270</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_abd1bb9e1b7783eccf8dca20d455064a3"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#abd1bb9e1b7783eccf8dca20d455064a3">StackInferOutputShapeFromInputsMatchTest</a></div><div class="ttdeci">void StackInferOutputShapeFromInputsMatchTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00290">InferOutputTests.hpp:290</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml_a2ceda8d369e861997d558fac74d79c33"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a2ceda8d369e861997d558fac74d79c33">armnn::Graph::InferTensorInfos</a></div><div class="ttdeci">void InferTensorInfos()</div><div class="ttdef"><b>Definition:</b> <a href="_graph_8cpp_source.xhtml#l00529">Graph.cpp:529</a></div></div>
<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a3941f674c071c9503e00d2b59e92e454"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a3941f674c071c9503e00d2b59e92e454">armnn::BatchToSpaceNdDescriptor::m_Crops</a></div><div class="ttdeci">std::vector< std::pair< unsigned int, unsigned int > > m_Crops</div><div class="ttdoc">The values to crop from the input dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00698">Descriptors.hpp:698</a></div></div>
<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::QLstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01195">Descriptors.hpp:1195</a></div></div>
<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.xhtml#l00013">InputLayer.hpp:13</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::TransposeConvolution2dDescriptor::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.xhtml#l01244">Descriptors.hpp:1244</a></div></div>
<div class="ttc" id="classarmnn_1_1_prelu_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_prelu_layer.xhtml">armnn::PreluLayer</a></div><div class="ttdef"><b>Definition:</b> <a href="_prelu_layer_8hpp_source.xhtml#l00014">PreluLayer.hpp:14</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="structarmnn_1_1_arg_min_max_descriptor_xhtml_a214c3636fdf0ea5bac8edb42d0e6c7f0"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml#a214c3636fdf0ea5bac8edb42d0e6c7f0">armnn::ArgMinMaxDescriptor::m_Axis</a></div><div class="ttdeci">int m_Axis</div><div class="ttdoc">Axis to reduce across the input tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00072">Descriptors.hpp:72</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_ae58e3f211ae2a124b13290c8b89aa87b"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#ae58e3f211ae2a124b13290c8b89aa87b">ArgMinMaxInferOutputShape2dTest</a></div><div class="ttdeci">void ArgMinMaxInferOutputShape2dTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00066">InferOutputTests.hpp:66</a></div></div>
<div class="ttc" id="classarmnn_1_1_convolution2d_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml">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.xhtml#l00015">Convolution2dLayer.hpp:15</a></div></div>
<div class="ttc" id="_test_utils_8cpp_xhtml_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00012">TestUtils.cpp:12</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div>
<div class="ttc" id="classarmnn_1_1_convolution2d_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::Convolution2dLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8cpp_source.xhtml#l00083">Convolution2dLayer.cpp:83</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a9c7ba1f02c1532cf22a54f624aa6fd4e"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a9c7ba1f02c1532cf22a54f624aa6fd4e">QLstmInferOutputShapeTest</a></div><div class="ttdeci">void QLstmInferOutputShapeTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00541">InferOutputTests.hpp:541</a></div></div>
<div class="ttc" id="classarmnn_1_1_arg_min_max_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_arg_min_max_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::ArgMinMaxLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">Infers the output shape from a given input shape and axis parameter. </div><div class="ttdef"><b>Definition:</b> <a href="_arg_min_max_layer_8cpp_source.xhtml#l00037">ArgMinMaxLayer.cpp:37</a></div></div>
<div class="ttc" id="_infer_output_tests_8hpp_xhtml_a29704df6ecb907082856bbb7474f494e"><div class="ttname"><a href="_infer_output_tests_8hpp.xhtml#a29704df6ecb907082856bbb7474f494e">PreluInferOutputShapeNoMatchTest</a></div><div class="ttdeci">void PreluInferOutputShapeNoMatchTest()</div><div class="ttdef"><b>Definition:</b> <a href="_infer_output_tests_8hpp_source.xhtml#l00217">InferOutputTests.hpp:217</a></div></div>
<div class="ttc" id="classarmnn_1_1_q_lstm_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_q_lstm_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::QLstmLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_q_lstm_layer_8cpp_source.xhtml#l00153">QLstmLayer.cpp:153</a></div></div>
<div class="ttc" id="classarmnn_1_1_transpose_convolution2d_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_transpose_convolution2d_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::TransposeConvolution2dLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">Infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_transpose_convolution2d_layer_8cpp_source.xhtml#l00057">TransposeConvolution2dLayer.cpp:57</a></div></div>
<div class="ttc" id="classarmnn_1_1_quantized_lstm_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_quantized_lstm_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::QuantizedLstmLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_quantized_lstm_layer_8cpp_source.xhtml#l00081">QuantizedLstmLayer.cpp:81</a></div></div>
<div class="ttc" id="classarmnn_1_1_space_to_depth_layer_xhtml_a65ca562c882ad619684445a1402f415a"><div class="ttname"><a href="classarmnn_1_1_space_to_depth_layer.xhtml#a65ca562c882ad619684445a1402f415a">armnn::SpaceToDepthLayer::InferOutputShapes</a></div><div class="ttdeci">std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override</div><div class="ttdoc">By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties. </div><div class="ttdef"><b>Definition:</b> <a href="_space_to_depth_layer_8cpp_source.xhtml#l00044">SpaceToDepthLayer.cpp:44</a></div></div>
<div class="ttc" id="structarmnn_1_1_q_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_q_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::QLstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable CIFG (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01191">Descriptors.hpp:1191</a></div></div>
<div class="ttc" id="_space_to_depth_layer_8hpp_xhtml"><div class="ttname"><a href="_space_to_depth_layer_8hpp.xhtml">SpaceToDepthLayer.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00460">Descriptors.hpp:460</a></div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00210">Layer.hpp:210</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#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.xhtml#l00438">Descriptors.hpp:438</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
<div class="ttc" id="_stack_layer_8hpp_xhtml"><div class="ttname"><a href="_stack_layer_8hpp.xhtml">StackLayer.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::DepthwiseConvolution2dDescriptor::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.xhtml#l00492">Descriptors.hpp:492</a></div></div>
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