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<div class="title">LayerReleaseConstantDataTest.cpp</div> </div>
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<a href="_layer_release_constant_data_test_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_common_test_utils_8hpp.xhtml">CommonTestUtils.hpp</a>"</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="_graph_8hpp.xhtml">Graph.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="_cpu_tensor_handle_8hpp.xhtml">backendsCommon/CpuTensorHandle.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_workload_data_8hpp.xhtml">backendsCommon/WorkloadData.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <utility></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="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="keyword">using namespace </span><a class="code" href="namespacestd.xhtml">std</a>;</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"></span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment">/////////////////////////////////////////////////////////////////////////////////////////////</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"></span><span class="comment">// The following test are created specifically to test ReleaseConstantData() method in the Layer</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment">// They build very simple graphs including the layer will be checked.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment">// Checks weights and biases before the method called and after.</span><span class="comment"></span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="comment">/////////////////////////////////////////////////////////////////////////////////////////////</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="comment"></span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(LayerReleaseConstantDataTest)</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="_layer_release_constant_data_test_8cpp.xhtml#aee3821ff85a903d278148142db9e7f69"> 28</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ReleaseBatchNormalizationLayerConstantDataTest)</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">Graph</a> graph;</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <span class="comment">// create the layer we're testing</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml">BatchNormalizationDescriptor</a> layerDesc;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  layerDesc.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a> = 0.05f;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml">BatchNormalizationLayer</a>* <span class="keyword">const</span> layer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml">BatchNormalizationLayer</a>>(layerDesc, <span class="stringliteral">"layer"</span>);</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> </div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightInfo({3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#a3540afac8fad99bbe68b3f7b57590160">m_Mean</a> = std::make_unique<ScopedCpuTensorHandle>(weightInfo);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#aa5685ee78433980cf535d745d1fcab55">m_Variance</a> = std::make_unique<ScopedCpuTensorHandle>(weightInfo);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#a77c30d191e7ee8917e2c0ff5e97f5640">m_Beta</a> = std::make_unique<ScopedCpuTensorHandle>(weightInfo);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#aec22bddf14a932c4a72796c30669066b">m_Gamma</a> = std::make_unique<ScopedCpuTensorHandle>(weightInfo);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#a3540afac8fad99bbe68b3f7b57590160">m_Mean</a>->Allocate();</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#aa5685ee78433980cf535d745d1fcab55">m_Variance</a>->Allocate();</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#a77c30d191e7ee8917e2c0ff5e97f5640">m_Beta</a>->Allocate();</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#aec22bddf14a932c4a72796c30669066b">m_Gamma</a>->Allocate();</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="comment">// create extra layers</span></div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">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">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">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">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="comment">// connect up</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo({2, 3, 1, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, layer, tensorInfo);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(layer, output, tensorInfo);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">// check the constants that they are not NULL</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#a3540afac8fad99bbe68b3f7b57590160">m_Mean</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#aa5685ee78433980cf535d745d1fcab55">m_Variance</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#a77c30d191e7ee8917e2c0ff5e97f5640">m_Beta</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#aec22bddf14a932c4a72796c30669066b">m_Gamma</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> </div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// free up the constants..</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a339bef86bc340c3d1393ed83950fe8af">ReleaseConstantData</a>();</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>  <span class="comment">// check the constants that they are NULL now</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#a3540afac8fad99bbe68b3f7b57590160">m_Mean</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#aa5685ee78433980cf535d745d1fcab55">m_Variance</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#a77c30d191e7ee8917e2c0ff5e97f5640">m_Beta</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_batch_normalization_layer.xhtml#aec22bddf14a932c4a72796c30669066b">m_Gamma</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  }</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"><a class="line" href="_layer_release_constant_data_test_8cpp.xhtml#a2733618103ee4525089ef9476ff20892"> 74</a></span>  <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ReleaseConvolution2dLayerConstantDataTest)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> </div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="comment">// create the layer we're testing</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a> layerDesc;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 3;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 3;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 1;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 1;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 4;</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">Convolution2dLayer</a>* <span class="keyword">const</span> layer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml">Convolution2dLayer</a>>(layerDesc, <span class="stringliteral">"layer"</span>);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<ScopedCpuTensorHandle>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 3, 5, 3},</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> = std::make_unique<ScopedCpuTensorHandle></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  (<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2}, <a class="code" href="namespacearmnn.xhtml#a872803f5667392efc3c8e5607bd453ad">GetBiasDataType</a>(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>)));</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>  layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->Allocate();</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>->Allocate();</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> </div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="comment">// create extra layers</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">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">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">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">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> </div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="comment">// connect up</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, layer, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 3, 8, 16}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(layer, output, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 2, 2, 10}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</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>  <span class="comment">// check the constants that they are not NULL</span></div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// free up the constants..</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a339bef86bc340c3d1393ed83950fe8af">ReleaseConstantData</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>  <span class="comment">// check the constants that they are NULL now</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> }</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00118"></a><span class="lineno"><a class="line" href="_layer_release_constant_data_test_8cpp.xhtml#ae587bfb42916b2feb32eada9b385e0ea"> 118</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ReleaseDepthwiseConvolution2dLayerConstantDataTest)</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> {</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> </div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <span class="comment">// create the layer we're testing</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">DepthwiseConvolution2dDescriptor</a> layerDesc;</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 3;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 3;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 1;</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 1;</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 4;</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">DepthwiseConvolution2dLayer</a>* <span class="keyword">const</span> layer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml">DepthwiseConvolution2dLayer</a>>(layerDesc, <span class="stringliteral">"layer"</span>);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<ScopedCpuTensorHandle>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({3, 3, 5, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>));</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> = std::make_unique<ScopedCpuTensorHandle>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({9}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>));</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->Allocate();</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>->Allocate();</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="comment">// create extra layers</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">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">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">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">OutputLayer</a>>(0, <span class="stringliteral">"output"</span>);</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="comment">// connect up</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, layer, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 3, 8, 16}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(layer, output, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 9, 2, 10}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> </div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="comment">// check the constants that they are not NULL</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="comment">// free up the constants..</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a339bef86bc340c3d1393ed83950fe8af">ReleaseConstantData</a>();</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> </div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="comment">// check the constants that they are NULL now</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> }</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> </div><div class="line"><a name="l00159"></a><span class="lineno"><a class="line" href="_layer_release_constant_data_test_8cpp.xhtml#a4086f4540f611d58a412ab43dd794535"> 159</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ReleaseFullyConnectedLayerConstantDataTest)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> </div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="comment">// create the layer we're testing</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">FullyConnectedDescriptor</a> layerDesc;</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  layerDesc.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  layerDesc.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#a281fcaec86e17c97f7b8402633f6b55a">m_TransposeWeightMatrix</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml">FullyConnectedLayer</a>* <span class="keyword">const</span> layer = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a><<a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml">FullyConnectedLayer</a>>(layerDesc, <span class="stringliteral">"layer"</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>  <span class="keywordtype">float</span> inputsQScale = 1.0f;</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordtype">float</span> outputQScale = 2.0f;</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>  layer-><a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique<ScopedCpuTensorHandle>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({7, 20},</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>, inputsQScale, 0));</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  layer-><a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> = std::make_unique<ScopedCpuTensorHandle>(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({7},</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <a class="code" href="namespacearmnn.xhtml#a872803f5667392efc3c8e5607bd453ad">GetBiasDataType</a>(<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>), inputsQScale));</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  layer-><a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a>->Allocate();</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  layer-><a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>->Allocate();</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="comment">// create extra layers</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">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">InputLayer</a>>(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="classarmnn_1_1_layer.xhtml">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">OutputLayer</a>>(0, <span class="stringliteral">"output"</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>  <span class="comment">// connect up</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, layer, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({3, 1, 4, 5}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>, inputsQScale));</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(layer, output, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({3, 7}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>, outputQScale));</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="comment">// check the constants that they are not NULL</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> </div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="comment">// free up the constants..</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  layer-><a class="code" href="classarmnn_1_1_layer.xhtml#a339bef86bc340c3d1393ed83950fe8af">ReleaseConstantData</a>();</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> </div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="comment">// check the constants that they are NULL now</span></div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  BOOST_CHECK(layer-><a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> == <span class="keyword">nullptr</span>);</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> </div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> <a class="code" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div><div class="ttc" id="_output_shape_of_squeeze_8cpp_xhtml_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div>
<div class="ttc" id="classarmnn_1_1_layer_xhtml_a339bef86bc340c3d1393ed83950fe8af"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a339bef86bc340c3d1393ed83950fe8af">armnn::Layer::ReleaseConstantData</a></div><div class="ttdeci">virtual void ReleaseConstantData()</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00274">Layer.cpp:274</a></div></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="structarmnn_1_1_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00454">Descriptors.hpp:454</a></div></div>
<div class="ttc" id="_workload_data_8hpp_xhtml"><div class="ttname"><a href="_workload_data_8hpp.xhtml">WorkloadData.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_batch_normalization_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.xhtml">armnn::BatchNormalizationLayer</a></div><div class="ttdoc">This layer represents a batch normalization operation. </div><div class="ttdef"><b>Definition:</b> <a href="_batch_normalization_layer_8hpp_source.xhtml#l00015">BatchNormalizationLayer.hpp:15</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00506">Descriptors.hpp:506</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_fully_connected_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_fully_connected_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::FullyConnectedLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_fully_connected_layer_8hpp_source.xhtml#l00019">FullyConnectedLayer.hpp:19</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="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a39925bc24d3afcfb322a46a5884fadb9"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">armnn::DepthwiseConvolution2dLayer::m_Bias</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Bias</div><div class="ttdoc">A unique pointer to store Bias values. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.xhtml#l00021">DepthwiseConvolution2dLayer.hpp:21</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="structarmnn_1_1_fully_connected_descriptor_xhtml_a281fcaec86e17c97f7b8402633f6b55a"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml#a281fcaec86e17c97f7b8402633f6b55a">armnn::FullyConnectedDescriptor::m_TransposeWeightMatrix</a></div><div class="ttdeci">bool m_TransposeWeightMatrix</div><div class="ttdoc">Enable/disable transpose weight matrix. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00404">Descriptors.hpp:404</a></div></div>
<div class="ttc" id="classarmnn_1_1_convolution2d_layer_xhtml_a39925bc24d3afcfb322a46a5884fadb9"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">armnn::Convolution2dLayer::m_Bias</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Bias</div><div class="ttdoc">A unique pointer to store Bias values. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.xhtml#l00022">Convolution2dLayer.hpp:22</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="structarmnn_1_1_batch_normalization_descriptor_xhtml_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">armnn::BatchNormalizationDescriptor::m_Eps</a></div><div class="ttdeci">float m_Eps</div><div class="ttdoc">Value to add to the variance. Used to avoid dividing by zero. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00639">Descriptors.hpp:639</a></div></div>
<div class="ttc" id="classarmnn_1_1_batch_normalization_layer_xhtml_aec22bddf14a932c4a72796c30669066b"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.xhtml#aec22bddf14a932c4a72796c30669066b">armnn::BatchNormalizationLayer::m_Gamma</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Gamma</div><div class="ttdoc">A unique pointer to store Gamma values. </div><div class="ttdef"><b>Definition:</b> <a href="_batch_normalization_layer_8hpp_source.xhtml#l00025">BatchNormalizationLayer.hpp:25</a></div></div>
<div class="ttc" id="classarmnn_1_1_batch_normalization_layer_xhtml_aa5685ee78433980cf535d745d1fcab55"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.xhtml#aa5685ee78433980cf535d745d1fcab55">armnn::BatchNormalizationLayer::m_Variance</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Variance</div><div class="ttdoc">A unique pointer to store Variance values. </div><div class="ttdef"><b>Definition:</b> <a href="_batch_normalization_layer_8hpp_source.xhtml#l00021">BatchNormalizationLayer.hpp:21</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="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div>
<div class="ttc" id="_common_test_utils_8hpp_xhtml"><div class="ttname"><a href="_common_test_utils_8hpp.xhtml">CommonTestUtils.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_batch_normalization_layer_xhtml_a77c30d191e7ee8917e2c0ff5e97f5640"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.xhtml#a77c30d191e7ee8917e2c0ff5e97f5640">armnn::BatchNormalizationLayer::m_Beta</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Beta</div><div class="ttdoc">A unique pointer to store Beta values. </div><div class="ttdef"><b>Definition:</b> <a href="_batch_normalization_layer_8hpp_source.xhtml#l00023">BatchNormalizationLayer.hpp:23</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="namespacestd_xhtml"><div class="ttname"><a href="namespacestd.xhtml">std</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.xhtml#l00147">BackendId.hpp:147</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="classarmnn_1_1_fully_connected_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_fully_connected_layer.xhtml">armnn::FullyConnectedLayer</a></div><div class="ttdoc">This layer represents a fully connected operation. </div><div class="ttdef"><b>Definition:</b> <a href="_fully_connected_layer_8hpp_source.xhtml#l00015">FullyConnectedLayer.hpp:15</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_batch_normalization_layer_xhtml_a3540afac8fad99bbe68b3f7b57590160"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.xhtml#a3540afac8fad99bbe68b3f7b57590160">armnn::BatchNormalizationLayer::m_Mean</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Mean</div><div class="ttdoc">A unique pointer to store Mean values. </div><div class="ttdef"><b>Definition:</b> <a href="_batch_normalization_layer_8hpp_source.xhtml#l00019">BatchNormalizationLayer.hpp:19</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="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml">armnn::FullyConnectedDescriptor</a></div><div class="ttdoc">A FullyConnectedDescriptor for the FullyConnectedLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00389">Descriptors.hpp:389</a></div></div>
<div class="ttc" id="classarmnn_1_1_convolution2d_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::Convolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.xhtml#l00020">Convolution2dLayer.hpp:20</a></div></div>
<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::FullyConnectedDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00402">Descriptors.hpp:402</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a10d15f3df1ab52b3b915a4be1dbf386b"><div class="ttname"><a href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">armnn::BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00268">ConstTensorLayerVisitor.cpp:268</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="namespacearmnn_xhtml_a872803f5667392efc3c8e5607bd453ad"><div class="ttname"><a href="namespacearmnn.xhtml#a872803f5667392efc3c8e5607bd453ad">armnn::GetBiasDataType</a></div><div class="ttdeci">DataType GetBiasDataType(DataType inputDataType)</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8cpp_source.xhtml#l00025">WorkloadData.cpp:25</a></div></div>
<div class="ttc" id="_cpu_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.xhtml">CpuTensorHandle.hpp</a></div></div>
<div class="ttc" id="_profiler_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</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="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="classarmnn_1_1_fully_connected_layer_xhtml_a39925bc24d3afcfb322a46a5884fadb9"><div class="ttname"><a href="classarmnn_1_1_fully_connected_layer.xhtml#a39925bc24d3afcfb322a46a5884fadb9">armnn::FullyConnectedLayer::m_Bias</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Bias</div><div class="ttdoc">A unique pointer to store Bias values. </div><div class="ttdef"><b>Definition:</b> <a href="_fully_connected_layer_8hpp_source.xhtml#l00021">FullyConnectedLayer.hpp:21</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="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="classarmnn_1_1_depthwise_convolution2d_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::DepthwiseConvolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr< ScopedCpuTensorHandle > m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_depthwise_convolution2d_layer_8hpp_source.xhtml#l00019">DepthwiseConvolution2dLayer.hpp:19</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_batch_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.xhtml">armnn::BatchNormalizationDescriptor</a></div><div class="ttdoc">A BatchNormalizationDescriptor for the BatchNormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00626">Descriptors.hpp:626</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="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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