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+<a href="_layer_release_constant_data_test_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_common_test_utils_8hpp.html">CommonTestUtils.hpp</a>&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;</div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_graph_8hpp.html">Graph.hpp</a>&gt;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_cpu_tensor_handle_8hpp.html">backendsCommon/CpuTensorHandle.hpp</a>&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_workload_data_8hpp.html">backendsCommon/WorkloadData.hpp</a>&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#include &lt;boost/cast.hpp&gt;</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &lt;boost/test/unit_test.hpp&gt;</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="preprocessor">#include &lt;utility&gt;</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacestd.html">std</a>;</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment">// The following test are created specifically to test ReleaseConstantData() method in the Layer</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment">// They build very simple graphs including the layer will be checked.</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="comment">// Checks weights and biases before the method called and after.</span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;<span class="comment"></span></div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<a class="code" href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(LayerReleaseConstantDataTest)</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;</div><div class="line"><a name="l00029"></a><span class="lineno"><a class="line" href="_layer_release_constant_data_test_8cpp.html#aee3821ff85a903d278148142db9e7f69">   29</a></span>&#160;<a class="code" href="namespacearmnn.html#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ReleaseBatchNormalizationLayerConstantDataTest)</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;{</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;    <span class="comment">// create the layer we&#39;re testing</span></div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    <a class="code" href="structarmnn_1_1_batch_normalization_descriptor.html">BatchNormalizationDescriptor</a> layerDesc;</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    layerDesc.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.html#a11c821c7524251004a72ed13c510853c">m_Eps</a> = 0.05f;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    <a class="code" href="classarmnn_1_1_batch_normalization_layer.html">BatchNormalizationLayer</a>* <span class="keyword">const</span> layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html">BatchNormalizationLayer</a>&gt;(layerDesc, <span class="stringliteral">&quot;layer&quot;</span>);</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> weightInfo({3}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#a3540afac8fad99bbe68b3f7b57590160">m_Mean</a>     = std::make_unique&lt;ScopedCpuTensorHandle&gt;(weightInfo);</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#aa5685ee78433980cf535d745d1fcab55">m_Variance</a> = std::make_unique&lt;ScopedCpuTensorHandle&gt;(weightInfo);</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#a77c30d191e7ee8917e2c0ff5e97f5640">m_Beta</a>     = std::make_unique&lt;ScopedCpuTensorHandle&gt;(weightInfo);</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#aec22bddf14a932c4a72796c30669066b">m_Gamma</a>    = std::make_unique&lt;ScopedCpuTensorHandle&gt;(weightInfo);</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#a3540afac8fad99bbe68b3f7b57590160">m_Mean</a>-&gt;Allocate();</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#aa5685ee78433980cf535d745d1fcab55">m_Variance</a>-&gt;Allocate();</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#a77c30d191e7ee8917e2c0ff5e97f5640">m_Beta</a>-&gt;Allocate();</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#aec22bddf14a932c4a72796c30669066b">m_Gamma</a>-&gt;Allocate();</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;    <span class="comment">// create extra layers</span></div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;    <span class="comment">// connect up</span></div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> tensorInfo({2, 3, 1, 1}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, layer, tensorInfo);</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(layer, output, tensorInfo);</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    <span class="comment">// check the constants that they are not NULL</span></div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#a3540afac8fad99bbe68b3f7b57590160">m_Mean</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#aa5685ee78433980cf535d745d1fcab55">m_Variance</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#a77c30d191e7ee8917e2c0ff5e97f5640">m_Beta</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#aec22bddf14a932c4a72796c30669066b">m_Gamma</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <span class="comment">// free up the constants..</span></div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a339bef86bc340c3d1393ed83950fe8af">ReleaseConstantData</a>();</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="comment">// check the constants that they are NULL now</span></div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#a3540afac8fad99bbe68b3f7b57590160">m_Mean</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#aa5685ee78433980cf535d745d1fcab55">m_Variance</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#a77c30d191e7ee8917e2c0ff5e97f5640">m_Beta</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_batch_normalization_layer.html#aec22bddf14a932c4a72796c30669066b">m_Gamma</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160; }</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;</div><div class="line"><a name="l00075"></a><span class="lineno"><a class="line" href="_layer_release_constant_data_test_8cpp.html#a2733618103ee4525089ef9476ff20892">   75</a></span>&#160; <a class="code" href="namespacearmnn.html#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ReleaseConvolution2dLayerConstantDataTest)</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160; {</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;     <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;     <span class="comment">// create the layer we&#39;re testing</span></div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;     <a class="code" href="structarmnn_1_1_convolution2d_descriptor.html">Convolution2dDescriptor</a> layerDesc;</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;     layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a> = 3;</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;     layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a> = 3;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;     layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a> = 1;</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;     layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a> = 1;</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;     layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a> = 2;</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;     layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a> = 4;</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;     layerDesc.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;     <a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>* <span class="keyword">const</span> layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html">Convolution2dLayer</a>&gt;(layerDesc, <span class="stringliteral">&quot;layer&quot;</span>);</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;     layer-&gt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique&lt;ScopedCpuTensorHandle&gt;(<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({2, 3, 5, 3},</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;                                                                          <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;     layer-&gt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>   = std::make_unique&lt;ScopedCpuTensorHandle&gt;</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;             (<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({2}, <a class="code" href="namespacearmnn.html#a872803f5667392efc3c8e5607bd453ad">GetBiasDataType</a>(<a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>)));</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;     layer-&gt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a>-&gt;Allocate();</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;     layer-&gt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>-&gt;Allocate();</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;     <span class="comment">// create extra layers</span></div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;     <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;     <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;     <span class="comment">// connect up</span></div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;     <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, layer, <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({2, 3, 8, 16}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;     <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(layer, output, <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({2, 2, 2, 10}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;     <span class="comment">// check the constants that they are not NULL</span></div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;     <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;     <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;     <span class="comment">// free up the constants..</span></div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;     layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a339bef86bc340c3d1393ed83950fe8af">ReleaseConstantData</a>();</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;     <span class="comment">// check the constants that they are NULL now</span></div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;     <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;     <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;}</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno"><a class="line" href="_layer_release_constant_data_test_8cpp.html#ae587bfb42916b2feb32eada9b385e0ea">  119</a></span>&#160;<a class="code" href="namespacearmnn.html#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ReleaseDepthwiseConvolution2dLayerConstantDataTest)</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;{</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    <span class="comment">// create the layer we&#39;re testing</span></div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;    <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">DepthwiseConvolution2dDescriptor</a> layerDesc;</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>         = 3;</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>        = 3;</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a>          = 1;</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>       = 1;</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>         = 2;</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>         = 4;</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    layerDesc.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a>     = <span class="keyword">true</span>;</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160; 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   layer-&gt;<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>   = std::make_unique&lt;ScopedCpuTensorHandle&gt;(<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({9}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>));</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a>-&gt;Allocate();</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>-&gt;Allocate();</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;    <span class="comment">// create extra layers</span></div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> output = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    <span class="comment">// connect up</span></div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, layer, <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({2, 3, 8, 16}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(layer, output, <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({2, 9, 2, 10}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="comment">// check the constants that they are not NULL</span></div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    <span class="comment">// free up the constants..</span></div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_layer.html#a339bef86bc340c3d1393ed83950fe8af">ReleaseConstantData</a>();</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    <span class="comment">// check the constants that they are NULL now</span></div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_depthwise_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a> == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;}</div><div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;</div><div class="line"><a name="l00160"></a><span class="lineno"><a class="line" href="_layer_release_constant_data_test_8cpp.html#a4086f4540f611d58a412ab43dd794535">  160</a></span>&#160;<a class="code" href="namespacearmnn.html#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ReleaseFullyConnectedLayerConstantDataTest)</div><div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;{</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;    <span class="comment">// create the layer we&#39;re testing</span></div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;    <a class="code" href="structarmnn_1_1_fully_connected_descriptor.html">FullyConnectedDescriptor</a> layerDesc;</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    layerDesc.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    layerDesc.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.html#a281fcaec86e17c97f7b8402633f6b55a">m_TransposeWeightMatrix</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;    <a class="code" href="classarmnn_1_1_fully_connected_layer.html">FullyConnectedLayer</a>* <span class="keyword">const</span> layer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_fully_connected_layer.html">FullyConnectedLayer</a>&gt;(layerDesc, <span class="stringliteral">&quot;layer&quot;</span>);</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;    <span class="keywordtype">float</span> inputsQScale = 1.0f;</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;    <span class="keywordtype">float</span> outputQScale = 2.0f;</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_fully_connected_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique&lt;ScopedCpuTensorHandle&gt;(<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({7, 20},</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;                                                          <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>, inputsQScale, 0));</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_fully_connected_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>   = std::make_unique&lt;ScopedCpuTensorHandle&gt;(<a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({7},</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;                                                          <a class="code" href="namespacearmnn.html#a872803f5667392efc3c8e5607bd453ad">GetBiasDataType</a>(<a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>), inputsQScale));</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_fully_connected_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a>-&gt;Allocate();</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_fully_connected_layer.html#a39925bc24d3afcfb322a46a5884fadb9">m_Bias</a>-&gt;Allocate();</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;    <span class="comment">// create extra layers</span></div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> input = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160; 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   <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(layer, output, <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>({3, 7}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>, outputQScale));</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    <span class="comment">// check the constants that they are not NULL</span></div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;<a class="code" href="classarmnn_1_1_fully_connected_layer.html#a2664044e28e69309ea08ef385fe53903">m_Weight</a> != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160; 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ScopedCpuTensorHandle &gt; 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.html#l00019">FullyConnectedLayer.hpp:19</a></div></div>
+<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#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.html#l00482">Descriptors.hpp:482</a></div></div>
+<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#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.html#l00480">Descriptors.hpp:480</a></div></div>
+<div class="ttc" id="classarmnn_1_1_input_layer_html"><div class="ttname"><a href="classarmnn_1_1_input_layer.html">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.html#l00013">InputLayer.hpp:13</a></div></div>
+<div class="ttc" id="classarmnn_1_1_convolution2d_layer_html_a39925bc24d3afcfb322a46a5884fadb9"><div class="ttname"><a href="classarmnn_1_1_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">armnn::Convolution2dLayer::m_Bias</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_Bias</div><div class="ttdoc">A unique pointer to store Bias values. </div><div class="ttdef"><b>Definition:</b> <a href="_convolution2d_layer_8hpp_source.html#l00022">Convolution2dLayer.hpp:22</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a002bc30e590d78cbb4f4d12171055ca7">armnn::Convolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00424">Descriptors.hpp:424</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_html_a339bef86bc340c3d1393ed83950fe8af"><div class="ttname"><a href="classarmnn_1_1_layer.html#a339bef86bc340c3d1393ed83950fe8af">armnn::Layer::ReleaseConstantData</a></div><div class="ttdeci">virtual void ReleaseConstantData()</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00263">Layer.cpp:263</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
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+<div class="ttc" id="classarmnn_1_1_batch_normalization_layer_html_aec22bddf14a932c4a72796c30669066b"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.html#aec22bddf14a932c4a72796c30669066b">armnn::BatchNormalizationLayer::m_Gamma</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; 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.html#l00025">BatchNormalizationLayer.hpp:25</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_html"><div class="ttname"><a href="classarmnn_1_1_layer.html">armnn::Layer</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00209">Layer.hpp:209</a></div></div>
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+<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="namespacearmnn_html_a10d15f3df1ab52b3b915a4be1dbf386b"><div class="ttname"><a href="namespacearmnn.html#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.html#l00170">ConstTensorLayerVisitor.cpp:170</a></div></div>
+<div class="ttc" id="namespacestd_html"><div class="ttname"><a href="namespacestd.html">std</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_id_8hpp_source.html#l00147">BackendId.hpp:147</a></div></div>
+<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_html_a39925bc24d3afcfb322a46a5884fadb9"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.html#a39925bc24d3afcfb322a46a5884fadb9">armnn::DepthwiseConvolution2dLayer::m_Bias</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; 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.html#l00021">DepthwiseConvolution2dLayer.hpp:21</a></div></div>
+<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.html">armnn::BatchNormalizationDescriptor</a></div><div class="ttdoc">A BatchNormalizationDescriptor for the BatchNormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00610">Descriptors.hpp:610</a></div></div>
+<div class="ttc" id="classarmnn_1_1_graph_html_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &amp;&amp;... 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.html#l00397">Graph.hpp:397</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aa9e49717ebdb741e8c767741647fc618">armnn::Convolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00428">Descriptors.hpp:428</a></div></div>
+<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#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.html#l00478">Descriptors.hpp:478</a></div></div>
+<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.html#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.html#l00386">Descriptors.hpp:386</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#ac1fe174bbadfb39a2b636940c2e647c8">armnn::Convolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00432">Descriptors.hpp:432</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
+<div class="ttc" id="classarmnn_1_1_depthwise_convolution2d_layer_html_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_depthwise_convolution2d_layer.html#a2664044e28e69309ea08ef385fe53903">armnn::DepthwiseConvolution2dLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; 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.html#l00019">DepthwiseConvolution2dLayer.hpp:19</a></div></div>
+<div class="ttc" id="classarmnn_1_1_fully_connected_layer_html"><div class="ttname"><a href="classarmnn_1_1_fully_connected_layer.html">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.html#l00015">FullyConnectedLayer.hpp:15</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#a56b51f56cef50cdfa554258eecdab046">armnn::Convolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00426">Descriptors.hpp:426</a></div></div>
+<div class="ttc" id="_common_test_utils_8hpp_html"><div class="ttname"><a href="_common_test_utils_8hpp.html">CommonTestUtils.hpp</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::Convolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00422">Descriptors.hpp:422</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#afe6a3377c4531315354def9023c8fdda">armnn::Convolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00430">Descriptors.hpp:430</a></div></div>
+<div class="ttc" id="classarmnn_1_1_batch_normalization_layer_html_aa5685ee78433980cf535d745d1fcab55"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.html#aa5685ee78433980cf535d745d1fcab55">armnn::BatchNormalizationLayer::m_Variance</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; 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.html#l00021">BatchNormalizationLayer.hpp:21</a></div></div>
+<div class="ttc" id="_file_only_profiling_decorator_tests_8cpp_html_a0c262ba6f6c189a2d092d127c1b7627b"><div class="ttname"><a href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a></div><div class="ttdeci">BOOST_CHECK(profilingService.GetCurrentState()==ProfilingState::WaitingForAck)</div></div>
+<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.html">armnn::FullyConnectedDescriptor</a></div><div class="ttdoc">A FullyConnectedDescriptor for the FullyConnectedLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00373">Descriptors.hpp:373</a></div></div>
+<div class="ttc" id="classarmnn_1_1_output_layer_html"><div class="ttname"><a href="classarmnn_1_1_output_layer.html">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.html#l00013">OutputLayer.hpp:13</a></div></div>
+<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_html_a281fcaec86e17c97f7b8402633f6b55a"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.html#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.html#l00388">Descriptors.hpp:388</a></div></div>
+<div class="ttc" id="structarmnn_1_1_batch_normalization_descriptor_html_a11c821c7524251004a72ed13c510853c"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_descriptor.html#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.html#l00623">Descriptors.hpp:623</a></div></div>
+<div class="ttc" id="_workload_data_8hpp_html"><div class="ttname"><a href="_workload_data_8hpp.html">WorkloadData.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html#aea202e14d8874cefd9a0f778022b7e25">armnn::Convolution2dDescriptor::m_BiasEnabled</a></div><div class="ttdeci">bool m_BiasEnabled</div><div class="ttdoc">Enable/disable bias. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00438">Descriptors.hpp:438</a></div></div>
+<div class="ttc" id="_profiler_tests_8cpp_html_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div>
+<div class="ttc" id="_test_utils_8cpp_html_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &amp;tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.html#l00012">TestUtils.cpp:12</a></div></div>
+<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#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.html#l00490">Descriptors.hpp:490</a></div></div>
+<div class="ttc" id="_cpu_tensor_handle_8hpp_html"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.html">CpuTensorHandle.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_batch_normalization_layer_html_a3540afac8fad99bbe68b3f7b57590160"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.html#a3540afac8fad99bbe68b3f7b57590160">armnn::BatchNormalizationLayer::m_Mean</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; 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.html#l00019">BatchNormalizationLayer.hpp:19</a></div></div>
+<div class="ttc" id="classarmnn_1_1_graph_html"><div class="ttname"><a href="classarmnn_1_1_graph.html">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.html#l00029">Graph.hpp:29</a></div></div>
+<div class="ttc" id="_output_shape_of_squeeze_8cpp_html_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div>
+<div class="ttc" id="namespacearmnn_html_a872803f5667392efc3c8e5607bd453ad"><div class="ttname"><a href="namespacearmnn.html#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.html#l00025">WorkloadData.cpp:25</a></div></div>
+<div class="ttc" id="classarmnn_1_1_batch_normalization_layer_html_a77c30d191e7ee8917e2c0ff5e97f5640"><div class="ttname"><a href="classarmnn_1_1_batch_normalization_layer.html#a77c30d191e7ee8917e2c0ff5e97f5640">armnn::BatchNormalizationLayer::m_Beta</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; 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.html#l00023">BatchNormalizationLayer.hpp:23</a></div></div>
+<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html">armnn::DepthwiseConvolution2dDescriptor</a></div><div class="ttdoc">A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00444">Descriptors.hpp:444</a></div></div>
+<div class="ttc" id="_graph_8hpp_html"><div class="ttname"><a href="_graph_8hpp.html">Graph.hpp</a></div></div>
+<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.html">armnn::Convolution2dDescriptor</a></div><div class="ttdoc">A Convolution2dDescriptor for the Convolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00392">Descriptors.hpp:392</a></div></div>
+<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#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.html#l00484">Descriptors.hpp:484</a></div></div>
+<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_html_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.html#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.html#l00476">Descriptors.hpp:476</a></div></div>
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