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<div class="title">SerializerTests.cpp</div>  </div>
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<a href="_serializer_tests_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd and Contributors. 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;../Serializer.hpp&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_serializer_test_utils_8hpp.xhtml">SerializerTestUtils.hpp</a>&quot;</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;</div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_descriptors_8hpp.xhtml">armnn/Descriptors.hpp</a>&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_i_network_8hpp.xhtml">armnn/INetwork.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="_types_utils_8hpp.xhtml">armnn/TypesUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_lstm_params_8hpp.xhtml">armnn/LstmParams.hpp</a>&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_quantized_lstm_params_8hpp.xhtml">armnn/QuantizedLstmParams.hpp</a>&gt;</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_i_deserializer_8hpp.xhtml">armnnDeserializer/IDeserializer.hpp</a>&gt;</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_ignore_unused_8hpp.xhtml">armnn/utility/IgnoreUnused.hpp</a>&gt;</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;</div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="preprocessor">#include &lt;random&gt;</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="preprocessor">#include &lt;vector&gt;</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="preprocessor">#include &lt;boost/test/unit_test.hpp&gt;</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="keyword">using</span> <a class="code" href="classarmnn_deserializer_1_1_i_deserializer.xhtml">armnnDeserializer::IDeserializer</a>;</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(SerializerTests)</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">   26</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeAbs)</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;{</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;abs&quot;</span>);</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo({1, 2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</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="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    <a class="code" href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> absLayer = network-&gt;AddAbsLayer(layerName.c_str());</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    <a class="code" href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(absLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    absLayer-&gt;GetOutputSlot(0).Connect(outputLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(tensorInfo);</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    absLayer-&gt;GetOutputSlot(0).SetTensorInfo(tensorInfo);</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    BOOST_CHECK(deserializedNetwork);</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;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {tensorInfo}, {tensorInfo});</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;}</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"><a class="line" href="_serializer_tests_8cpp.xhtml#aafd0924b96830cf275f533b32ade856e">   52</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeAddition)</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;{</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;addition&quot;</span>);</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo({1, 2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</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;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer0 = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1 = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> additionLayer = network-&gt;AddAdditionLayer(layerName.c_str());</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</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;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(tensorInfo);</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(tensorInfo);</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(tensorInfo);</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    std::string serializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network);</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(serializedNetwork);</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {tensorInfo, tensorInfo}, {tensorInfo});</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;}</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a0e876ee76e1b7b55c4a24cea29ee70ac">   79</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeArgMinMax)</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;{</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;argminmax&quot;</span>);</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({1, 2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({1, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>);</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    <a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a> descriptor;</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_arg_min_max_descriptor.xhtml#ab1ae6f520bb1a4da191a0ae907477f23">m_Function</a> = <a class="code" href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::ArgMinMaxFunction::Max</a>;</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    descriptor.m_Axis = 1;</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="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> argMinMaxLayer = network-&gt;AddArgMinMaxLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(argMinMaxLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;    argMinMaxLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    argMinMaxLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    BOOST_CHECK(deserializedNetwork);</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;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::ArgMinMaxDescriptor&gt;</a> verifier(layerName,</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;                                                                         {inputInfo},</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;                                                                         {outputInfo},</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;                                                                         descriptor);</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;}</div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;</div><div class="line"><a name="l00110"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#add359ae172212d256d7024a16b577fa8">  110</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeBatchNormalization)</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;{</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;batchNormalization&quot;</span>);</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo ({ 1, 3, 3, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({ 1, 3, 3, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> meanInfo({1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> varianceInfo({1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> betaInfo({1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> gammaInfo({1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</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="structarmnn_1_1_batch_normalization_descriptor.xhtml">armnn::BatchNormalizationDescriptor</a> descriptor;</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_batch_normalization_descriptor.xhtml#a11c821c7524251004a72ed13c510853c">m_Eps</a> = 0.0010000000475f;</div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    descriptor.m_DataLayout = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;</div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    std::vector&lt;float&gt; meanData({5.0});</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    std::vector&lt;float&gt; varianceData({2.0});</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;    std::vector&lt;float&gt; betaData({1.0});</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    std::vector&lt;float&gt; gammaData({0.0});</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;    std::vector&lt;armnn::ConstTensor&gt; constants;</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;    constants.emplace_back(<a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(meanInfo, meanData));</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    constants.emplace_back(<a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(varianceInfo, varianceData));</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;    constants.emplace_back(<a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(betaInfo, betaData));</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    constants.emplace_back(<a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>(gammaInfo, gammaData));</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> batchNormalizationLayer =</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;        network-&gt;AddBatchNormalizationLayer(descriptor,</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;                                            constants[0],</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;                                            constants[1],</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;                                            constants[2],</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;                                            constants[3],</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;                                            layerName.c_str());</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(batchNormalizationLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    batchNormalizationLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    batchNormalizationLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;</div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml">LayerVerifierBaseWithDescriptorAndConstants&lt;armnn::BatchNormalizationDescriptor&gt;</a> verifier(</div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;        layerName, {inputInfo}, {outputInfo}, descriptor, constants);</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</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">  160</span>&#160;</div><div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a51de9ca6ac8a186f48cca59f392e4b50">  161</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeBatchToSpaceNd)</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;{</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;spaceToBatchNd&quot;</span>);</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({4, 1, 2, 2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({1, 1, 4, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;</div><div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    <a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">armnn::BatchToSpaceNdDescriptor</a> desc;</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;    desc.<a class="code" href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;    desc.m_BlockShape = {2, 2};</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    desc.m_Crops = {{0, 0}, {0, 0}};</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> batchToSpaceNdLayer = network-&gt;AddBatchToSpaceNdLayer(desc, layerName.c_str());</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;</div><div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(batchToSpaceNdLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    batchToSpaceNdLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;    batchToSpaceNdLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::BatchToSpaceNdDescriptor&gt;</a> verifier(layerName,</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;                                                                              {inputInfo},</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;                                                                              {outputInfo},</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;                                                                              desc);</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;}</div><div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;</div><div class="line"><a name="l00193"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a16dc6220342037f5a890ad7a912594e7">  193</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeComparison)</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;{</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;comparison&quot;</span>);</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> shape{2, 1, 2, 4};</div><div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo  = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a>);</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;    <a class="code" href="structarmnn_1_1_comparison_descriptor.xhtml">armnn::ComparisonDescriptor</a> descriptor(<a class="code" href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca19bb0af2c3c530538cb41aff7f235b96">armnn::ComparisonOperation::NotEqual</a>);</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer0     = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1     = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> comparisonLayer = network-&gt;AddComparisonLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer     = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(comparisonLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(comparisonLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;    comparisonLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;    comparisonLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;</div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::ComparisonDescriptor&gt;</a> verifier(layerName,</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;                                                                          { inputInfo, inputInfo },</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;                                                                          { outputInfo },</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;                                                                          descriptor);</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;}</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;</div><div class="line"><a name="l00228"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a3c47c5c535712035fb962c91fffc3447">  228</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeConstant)</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;{</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;    <span class="keyword">class </span>ConstantLayerVerifier : <span class="keyword">public</span> <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a></div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;    {</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;    <span class="keyword">public</span>:</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;        ConstantLayerVerifier(<span class="keyword">const</span> std::string&amp; layerName,</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;                              <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; inputInfos,</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;                              <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; outputInfos,</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;                              <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants)</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;            : <a class="code" href="class_layer_verifier_base.xhtml#a39bdf94af97d9484d02649b749da327c">LayerVerifierBase</a>(layerName, inputInfos, outputInfos)</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;            , m_Constants(constants) {}</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;        <span class="keywordtype">void</span> <a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer,</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;                             <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_base_descriptor.xhtml">armnn::BaseDescriptor</a>&amp; descriptor,</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;                             <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants,</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;                             <span class="keyword">const</span> <span class="keywordtype">char</span>* name,</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;                             <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> <span class="keywordtype">id</span> = 0)<span class="keyword"> override</span></div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;<span class="keyword">        </span>{</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;            <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a>(descriptor, <span class="keywordtype">id</span>);</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;            <span class="keywordflow">switch</span> (layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">GetType</a>())</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;            {</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">armnn::LayerType::Addition</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;                <span class="keywordflow">default</span>:</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;                {</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;                    this-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a56e5da77beb8c601e09bf78371b95828">VerifyNameAndConnections</a>(layer, name);</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;                    <span class="keywordflow">for</span> (std::size_t i = 0; i &lt; constants.size(); i++)</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;                    {</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;                        <a class="code" href="_serializer_test_utils_8cpp.xhtml#a104f74b01c30ad4a17d765309a9731bd">CompareConstTensor</a>(constants[i], m_Constants[i]);</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;                    }</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;                }</div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;            }</div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;        }</div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;</div><div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;    <span class="keyword">private</span>:</div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;        <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt; m_Constants;</div><div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;    };</div><div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;</div><div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;constant&quot;</span>);</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> info({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;</div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;    std::vector&lt;float&gt; constantData = GenerateRandomData&lt;float&gt;(info.GetNumElements());</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> constTensor(info, constantData);</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>());</div><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* input = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* constant = network-&gt;AddConstantLayer(constTensor, layerName.c_str());</div><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* add = network-&gt;AddAdditionLayer();</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* output = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;</div><div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;    constant-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;    add-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;</div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;    constant-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;    add-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(info);</div><div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;</div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;    ConstantLayerVerifier verifier(layerName, {}, {info}, {constTensor});</div><div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;    deserializedNetwork-&gt;ExecuteStrategy(verifier);</div><div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;}</div><div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;</div><div class="line"><a name="l00296"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a5356190bf530f061bfad94d3b5842e07">  296</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeConvolution2d)</div><div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;{</div><div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;convolution2d&quot;</span>);</div><div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo ({ 1, 5, 5, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({ 1, 3, 3, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;</div><div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsInfo({ 1, 3, 3, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesInfo ({ 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;</div><div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;    std::vector&lt;float&gt; weightsData = GenerateRandomData&lt;float&gt;(weightsInfo.GetNumElements());</div><div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights(weightsInfo, weightsData);</div><div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;</div><div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;    std::vector&lt;float&gt; biasesData = GenerateRandomData&lt;float&gt;(biasesInfo.GetNumElements());</div><div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> biases(biasesInfo, biasesData);</div><div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;</div><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;    <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">armnn::Convolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>     = 1;</div><div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>    = 1;</div><div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a>      = 1;</div><div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>   = 1;</div><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>     = 2;</div><div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>     = 2;</div><div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a>   = 2;</div><div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a>   = 2;</div><div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;    descriptor.<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="l00321"></a><span class="lineno">  321</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>  = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;</div><div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer  = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> convLayer   =</div><div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;            network-&gt;AddConvolution2dLayer(descriptor,</div><div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;                                           weights,</div><div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;                                           <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional&lt;armnn::ConstTensor&gt;</a>(biases),</div><div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;                                           layerName.c_str());</div><div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;</div><div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(convLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;    convLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;</div><div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;    convLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;</div><div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;</div><div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;    <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants {weights, biases};</div><div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml">LayerVerifierBaseWithDescriptorAndConstants&lt;armnn::Convolution2dDescriptor&gt;</a> verifier(</div><div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;            layerName, {inputInfo}, {outputInfo}, descriptor, constants);</div><div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;}</div><div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;</div><div class="line"><a name="l00347"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a84fdfdaadeab7586421ae49e4eefb786">  347</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeConvolution2dWithPerAxisParams)</div><div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;{</div><div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;    <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;</div><div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;convolution2dWithPerAxis&quot;</span>);</div><div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo ({ 1, 3, 1, 2 }, DataType::QAsymmU8, 0.55f, 128);</div><div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 3, 1, 3 }, DataType::QAsymmU8, 0.75f, 128);</div><div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;</div><div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;    <span class="keyword">const</span> std::vector&lt;float&gt; quantScales{ 0.75f, 0.65f, 0.85f };</div><div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;    constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantDimension = 0;</div><div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;</div><div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> kernelInfo({ 3, 1, 1, 2 }, DataType::QSymmS8, quantScales, quantDimension);</div><div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;</div><div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;    <span class="keyword">const</span> std::vector&lt;float&gt; biasQuantScales{ 0.25f, 0.50f, 0.75f };</div><div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> biasInfo({ 3 }, DataType::Signed32, biasQuantScales, quantDimension);</div><div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;</div><div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;    std::vector&lt;int8_t&gt; kernelData = GenerateRandomData&lt;int8_t&gt;(kernelInfo.GetNumElements());</div><div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights(kernelInfo, kernelData);</div><div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;    std::vector&lt;int32_t&gt; biasData = GenerateRandomData&lt;int32_t&gt;(biasInfo.GetNumElements());</div><div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> biases(biasInfo, biasData);</div><div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;</div><div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;    <a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml">Convolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>     = 1;</div><div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>     = 1;</div><div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>     = 0;</div><div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>    = 0;</div><div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a>      = 0;</div><div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>   = 0;</div><div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160;    descriptor.<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="l00376"></a><span class="lineno">  376</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>  = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;</div><div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer  = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> convLayer   =</div><div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;        network-&gt;AddConvolution2dLayer(descriptor,</div><div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160;                                       weights,</div><div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;                                       <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional&lt;armnn::ConstTensor&gt;</a>(biases),</div><div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160;                                       layerName.c_str());</div><div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;</div><div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(convLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;    convLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;</div><div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;    convLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;</div><div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;</div><div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;    <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants {weights, biases};</div><div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml">LayerVerifierBaseWithDescriptorAndConstants&lt;Convolution2dDescriptor&gt;</a> verifier(</div><div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;            layerName, {inputInfo}, {outputInfo}, descriptor, constants);</div><div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;}</div><div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;</div><div class="line"><a name="l00402"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a38de5ca76565a5326549aa88153f5aec">  402</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeDepthToSpace)</div><div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;{</div><div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;depthToSpace&quot;</span>);</div><div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;</div><div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo ({ 1,  8, 4, 12 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({ 1, 16, 8,  3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;</div><div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;    <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml">armnn::DepthToSpaceDescriptor</a> desc;</div><div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160;    desc.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a>  = 2;</div><div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;    desc.m_DataLayout = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;</div><div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer        = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> depthToSpaceLayer = network-&gt;AddDepthToSpaceLayer(desc, layerName.c_str());</div><div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer       = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;</div><div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(depthToSpaceLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;    depthToSpaceLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;</div><div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;    depthToSpaceLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;</div><div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;</div><div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::DepthToSpaceDescriptor&gt;</a> verifier(layerName, {inputInfo}, {outputInfo}, desc);</div><div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;}</div><div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;</div><div class="line"><a name="l00431"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a119be6a507d98bdd38a54db9f7036139">  431</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeDepthwiseConvolution2d)</div><div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;{</div><div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;depwiseConvolution2d&quot;</span>);</div><div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo ({ 1, 5, 5, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({ 1, 3, 3, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;</div><div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsInfo({ 1, 3, 3, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesInfo ({ 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;</div><div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;    std::vector&lt;float&gt; weightsData = GenerateRandomData&lt;float&gt;(weightsInfo.GetNumElements());</div><div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights(weightsInfo, weightsData);</div><div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;</div><div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;    std::vector&lt;int32_t&gt; biasesData = GenerateRandomData&lt;int32_t&gt;(biasesInfo.GetNumElements());</div><div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> biases(biasesInfo, biasesData);</div><div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;</div><div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;    <a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml">armnn::DepthwiseConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>     = 1;</div><div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>    = 1;</div><div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a>      = 1;</div><div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>   = 1;</div><div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>     = 2;</div><div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>     = 2;</div><div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a>   = 2;</div><div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a>   = 2;</div><div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;    descriptor.<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="l00456"></a><span class="lineno">  456</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>  = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;</div><div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> depthwiseConvLayer =</div><div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;        network-&gt;AddDepthwiseConvolution2dLayer(descriptor,</div><div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;                                                weights,</div><div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;                                                <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional&lt;armnn::ConstTensor&gt;</a>(biases),</div><div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;                                                layerName.c_str());</div><div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;</div><div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(depthwiseConvLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;    depthwiseConvLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;</div><div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;    depthwiseConvLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;</div><div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;</div><div class="line"><a name="l00476"></a><span class="lineno">  476</span>&#160;    <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants {weights, biases};</div><div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml">LayerVerifierBaseWithDescriptorAndConstants&lt;armnn::DepthwiseConvolution2dDescriptor&gt;</a> verifier(</div><div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;            layerName, {inputInfo}, {outputInfo}, descriptor, constants);</div><div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;}</div><div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;</div><div class="line"><a name="l00482"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a37b1e96904fb8290684dcd7eb40fc87f">  482</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeDepthwiseConvolution2dWithPerAxisParams)</div><div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;{</div><div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;    <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;</div><div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;depwiseConvolution2dWithPerAxis&quot;</span>);</div><div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> inputInfo ({ 1, 3, 3, 2 }, DataType::QAsymmU8, 0.55f, 128);</div><div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> outputInfo({ 1, 2, 2, 4 }, DataType::QAsymmU8, 0.75f, 128);</div><div class="line"><a name="l00489"></a><span class="lineno">  489</span>&#160;</div><div class="line"><a name="l00490"></a><span class="lineno">  490</span>&#160;    <span class="keyword">const</span> std::vector&lt;float&gt; quantScales{ 0.75f, 0.80f, 0.90f, 0.95f };</div><div class="line"><a name="l00491"></a><span class="lineno">  491</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> quantDimension = 0;</div><div class="line"><a name="l00492"></a><span class="lineno">  492</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a> kernelInfo({ 2, 2, 2, 2 }, DataType::QSymmS8, quantScales, quantDimension);</div><div class="line"><a name="l00493"></a><span class="lineno">  493</span>&#160;</div><div class="line"><a name="l00494"></a><span class="lineno">  494</span>&#160;    <span class="keyword">const</span> std::vector&lt;float&gt; biasQuantScales{ 0.25f, 0.35f, 0.45f, 0.55f };</div><div class="line"><a name="l00495"></a><span class="lineno">  495</span>&#160;    constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> biasQuantDimension = 0;</div><div class="line"><a name="l00496"></a><span class="lineno">  496</span>&#160; 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   descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a>      = 0;</div><div class="line"><a name="l00509"></a><span class="lineno">  509</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>   = 0;</div><div class="line"><a name="l00510"></a><span class="lineno">  510</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">m_DilationX</a>   = 1;</div><div class="line"><a name="l00511"></a><span class="lineno">  511</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">m_DilationY</a>   = 1;</div><div class="line"><a name="l00512"></a><span class="lineno">  512</span>&#160;    descriptor.<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="l00513"></a><span class="lineno">  513</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>  = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00514"></a><span class="lineno">  514</span>&#160;</div><div class="line"><a name="l00515"></a><span class="lineno">  515</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00516"></a><span class="lineno">  516</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00517"></a><span class="lineno">  517</span>&#160; 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   inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(depthwiseConvLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00525"></a><span class="lineno">  525</span>&#160;    depthwiseConvLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00526"></a><span class="lineno">  526</span>&#160;</div><div class="line"><a name="l00527"></a><span class="lineno">  527</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00528"></a><span class="lineno">  528</span>&#160;    depthwiseConvLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00529"></a><span class="lineno">  529</span>&#160;</div><div class="line"><a name="l00530"></a><span class="lineno">  530</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00531"></a><span class="lineno">  531</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00532"></a><span class="lineno">  532</span>&#160;</div><div class="line"><a name="l00533"></a><span class="lineno">  533</span>&#160;    <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants {weights, biases};</div><div class="line"><a name="l00534"></a><span class="lineno">  534</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml">LayerVerifierBaseWithDescriptorAndConstants&lt;armnn::DepthwiseConvolution2dDescriptor&gt;</a> verifier(</div><div class="line"><a name="l00535"></a><span class="lineno">  535</span>&#160;            layerName, {inputInfo}, {outputInfo}, descriptor, constants);</div><div class="line"><a name="l00536"></a><span class="lineno">  536</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00537"></a><span class="lineno">  537</span>&#160;}</div><div class="line"><a name="l00538"></a><span class="lineno">  538</span>&#160;</div><div class="line"><a name="l00539"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a20970cfb9b49e5080b90f605ae840761">  539</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeDequantize)</div><div class="line"><a name="l00540"></a><span class="lineno">  540</span>&#160;{</div><div class="line"><a name="l00541"></a><span class="lineno">  541</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;dequantize&quot;</span>);</div><div class="line"><a name="l00542"></a><span class="lineno">  542</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({ 1, 5, 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>, 0.5f, 1);</div><div class="line"><a name="l00543"></a><span class="lineno">  543</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({ 1, 5, 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00544"></a><span class="lineno">  544</span>&#160;</div><div class="line"><a name="l00545"></a><span class="lineno">  545</span>&#160; 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   inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(dequantizeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00551"></a><span class="lineno">  551</span>&#160;    dequantizeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00552"></a><span class="lineno">  552</span>&#160;</div><div class="line"><a name="l00553"></a><span class="lineno">  553</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00554"></a><span class="lineno">  554</span>&#160;    dequantizeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00555"></a><span class="lineno">  555</span>&#160;</div><div class="line"><a name="l00556"></a><span class="lineno">  556</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00557"></a><span class="lineno">  557</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00558"></a><span class="lineno">  558</span>&#160;</div><div class="line"><a name="l00559"></a><span class="lineno">  559</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {inputInfo}, {outputInfo});</div><div class="line"><a name="l00560"></a><span class="lineno">  560</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00561"></a><span class="lineno">  561</span>&#160;}</div><div class="line"><a name="l00562"></a><span class="lineno">  562</span>&#160;</div><div class="line"><a name="l00563"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a855eea3f4f96815bb7a4cefde6791a3a">  563</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeDeserializeDetectionPostProcess)</div><div class="line"><a name="l00564"></a><span class="lineno">  564</span>&#160;{</div><div class="line"><a name="l00565"></a><span class="lineno">  565</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;detectionPostProcess&quot;</span>);</div><div class="line"><a name="l00566"></a><span class="lineno">  566</span>&#160;</div><div class="line"><a name="l00567"></a><span class="lineno">  567</span>&#160;    <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt; inputInfos({</div><div class="line"><a name="l00568"></a><span class="lineno">  568</span>&#160;        <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({ 1, 6, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>),</div><div class="line"><a name="l00569"></a><span class="lineno">  569</span>&#160;        <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({ 1, 6, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>)</div><div class="line"><a name="l00570"></a><span class="lineno">  570</span>&#160;    });</div><div class="line"><a name="l00571"></a><span class="lineno">  571</span>&#160;</div><div class="line"><a name="l00572"></a><span class="lineno">  572</span>&#160;    <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt; outputInfos({</div><div class="line"><a name="l00573"></a><span class="lineno">  573</span>&#160;        <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({ 1, 3, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>),</div><div class="line"><a name="l00574"></a><span class="lineno">  574</span>&#160;        <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({ 1, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>),</div><div class="line"><a name="l00575"></a><span class="lineno">  575</span>&#160;        <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({ 1, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>),</div><div class="line"><a name="l00576"></a><span class="lineno">  576</span>&#160;        <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({ 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>)</div><div class="line"><a name="l00577"></a><span class="lineno">  577</span>&#160;    });</div><div class="line"><a name="l00578"></a><span class="lineno">  578</span>&#160;</div><div class="line"><a name="l00579"></a><span class="lineno">  579</span>&#160;    <a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a> descriptor;</div><div class="line"><a name="l00580"></a><span class="lineno">  580</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">m_UseRegularNms</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00581"></a><span class="lineno">  581</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">m_MaxDetections</a> = 3;</div><div class="line"><a name="l00582"></a><span class="lineno">  582</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a9ae2c9796692ebeafe19a4d3f09c8ea8">m_MaxClassesPerDetection</a> = 1;</div><div class="line"><a name="l00583"></a><span class="lineno">  583</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7e2f87544b8bc7e497e1dec8d3ca4055">m_DetectionsPerClass</a> =1;</div><div class="line"><a name="l00584"></a><span class="lineno">  584</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a4392dd6b4862cc9cf95ae8f1001ba592">m_NmsScoreThreshold</a> = 0.0;</div><div class="line"><a name="l00585"></a><span class="lineno">  585</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a53c8a7f33a40e1e240256bcfcf41b101">m_NmsIouThreshold</a> = 0.5;</div><div class="line"><a name="l00586"></a><span class="lineno">  586</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a3a04b0ccee4bb2f21721ee5045e83df4">m_NumClasses</a> = 2;</div><div class="line"><a name="l00587"></a><span class="lineno">  587</span>&#160; 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       0.5f, 10.5f, 1.0f, 1.0f,</div><div class="line"><a name="l00599"></a><span class="lineno">  599</span>&#160;        0.5f, 100.5f, 1.0f, 1.0f</div><div class="line"><a name="l00600"></a><span class="lineno">  600</span>&#160;    });</div><div class="line"><a name="l00601"></a><span class="lineno">  601</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> <a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a>(<a class="code" href="_neon_end_to_end_tests_8cpp.xhtml#a358cb7cd3c0647b25be049fd734b8c22">anchorsInfo</a>, anchorsData);</div><div class="line"><a name="l00602"></a><span class="lineno">  602</span>&#160;</div><div class="line"><a name="l00603"></a><span class="lineno">  603</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00604"></a><span class="lineno">  604</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> detectionLayer =</div><div class="line"><a name="l00605"></a><span class="lineno">  605</span>&#160;        network-&gt;AddDetectionPostProcessLayer(descriptor, anchors, layerName.c_str());</div><div class="line"><a name="l00606"></a><span class="lineno">  606</span>&#160;</div><div class="line"><a name="l00607"></a><span class="lineno">  607</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; 2; i++)</div><div class="line"><a name="l00608"></a><span class="lineno">  608</span>&#160;    {</div><div class="line"><a name="l00609"></a><span class="lineno">  609</span>&#160;        <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(static_cast&lt;int&gt;(i));</div><div class="line"><a name="l00610"></a><span class="lineno">  610</span>&#160;        inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(detectionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(i));</div><div class="line"><a name="l00611"></a><span class="lineno">  611</span>&#160;        inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfos[i]);</div><div class="line"><a name="l00612"></a><span class="lineno">  612</span>&#160;    }</div><div class="line"><a name="l00613"></a><span class="lineno">  613</span>&#160;</div><div class="line"><a name="l00614"></a><span class="lineno">  614</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; 4; i++)</div><div class="line"><a name="l00615"></a><span class="lineno">  615</span>&#160;    {</div><div class="line"><a name="l00616"></a><span class="lineno">  616</span>&#160;        <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(static_cast&lt;int&gt;(i));</div><div class="line"><a name="l00617"></a><span class="lineno">  617</span>&#160;        detectionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(i).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00618"></a><span class="lineno">  618</span>&#160;        detectionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(i).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfos[i]);</div><div class="line"><a name="l00619"></a><span class="lineno">  619</span>&#160;    }</div><div class="line"><a name="l00620"></a><span class="lineno">  620</span>&#160;</div><div class="line"><a name="l00621"></a><span class="lineno">  621</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00622"></a><span class="lineno">  622</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00623"></a><span class="lineno">  623</span>&#160;</div><div class="line"><a name="l00624"></a><span class="lineno">  624</span>&#160;    <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants {anchors};</div><div class="line"><a name="l00625"></a><span class="lineno">  625</span>&#160; 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   <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;division&quot;</span>);</div><div class="line"><a name="l00633"></a><span class="lineno">  633</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 5, 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00634"></a><span class="lineno">  634</span>&#160;</div><div class="line"><a name="l00635"></a><span class="lineno">  635</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00636"></a><span class="lineno">  636</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer0 = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00637"></a><span class="lineno">  637</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1 = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l00638"></a><span class="lineno">  638</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> divisionLayer = network-&gt;AddDivisionLayer(layerName.c_str());</div><div class="line"><a name="l00639"></a><span class="lineno">  639</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00640"></a><span class="lineno">  640</span>&#160;</div><div class="line"><a name="l00641"></a><span class="lineno">  641</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(divisionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00642"></a><span class="lineno">  642</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(divisionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00643"></a><span class="lineno">  643</span>&#160;    divisionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00644"></a><span class="lineno">  644</span>&#160;</div><div class="line"><a name="l00645"></a><span class="lineno">  645</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l00646"></a><span class="lineno">  646</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l00647"></a><span class="lineno">  647</span>&#160;    divisionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l00648"></a><span class="lineno">  648</span>&#160;</div><div class="line"><a name="l00649"></a><span class="lineno">  649</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00650"></a><span class="lineno">  650</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00651"></a><span class="lineno">  651</span>&#160;</div><div class="line"><a name="l00652"></a><span class="lineno">  652</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {info});</div><div class="line"><a name="l00653"></a><span class="lineno">  653</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00654"></a><span class="lineno">  654</span>&#160;}</div><div class="line"><a name="l00655"></a><span class="lineno">  655</span>&#160;</div><div class="line"><a name="l00656"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a2432685a52cbbe74becf5f9a13627da1">  656</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeDeserializeEqual)</div><div class="line"><a name="l00657"></a><span class="lineno">  657</span>&#160;{</div><div class="line"><a name="l00658"></a><span class="lineno">  658</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;EqualLayer&quot;</span>);</div><div class="line"><a name="l00659"></a><span class="lineno">  659</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo1 = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({2, 1, 2, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00660"></a><span class="lineno">  660</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo2 = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({2, 1, 2, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00661"></a><span class="lineno">  661</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({2, 1, 2, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a>);</div><div class="line"><a name="l00662"></a><span class="lineno">  662</span>&#160;</div><div class="line"><a name="l00663"></a><span class="lineno">  663</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00664"></a><span class="lineno">  664</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1 = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00665"></a><span class="lineno">  665</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer2 = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l00666"></a><span class="lineno">  666</span>&#160;    <a class="code" href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l00667"></a><span class="lineno">  667</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> equalLayer = network-&gt;AddEqualLayer(layerName.c_str());</div><div class="line"><a name="l00668"></a><span class="lineno">  668</span>&#160;    <a class="code" href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="line"><a name="l00669"></a><span class="lineno">  669</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00670"></a><span class="lineno">  670</span>&#160;</div><div class="line"><a name="l00671"></a><span class="lineno">  671</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(equalLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00672"></a><span class="lineno">  672</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputTensorInfo1);</div><div class="line"><a name="l00673"></a><span class="lineno">  673</span>&#160;    inputLayer2-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(equalLayer-&gt;GetInputSlot(1));</div><div class="line"><a name="l00674"></a><span class="lineno">  674</span>&#160;    inputLayer2-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputTensorInfo2);</div><div class="line"><a name="l00675"></a><span class="lineno">  675</span>&#160;    equalLayer-&gt;GetOutputSlot(0).Connect(outputLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00676"></a><span class="lineno">  676</span>&#160;    equalLayer-&gt;GetOutputSlot(0).SetTensorInfo(outputTensorInfo);</div><div class="line"><a name="l00677"></a><span class="lineno">  677</span>&#160;</div><div class="line"><a name="l00678"></a><span class="lineno">  678</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00679"></a><span class="lineno">  679</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00680"></a><span class="lineno">  680</span>&#160;</div><div class="line"><a name="l00681"></a><span class="lineno">  681</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {inputTensorInfo1, inputTensorInfo2}, {outputTensorInfo});</div><div class="line"><a name="l00682"></a><span class="lineno">  682</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00683"></a><span class="lineno">  683</span>&#160;}</div><div class="line"><a name="l00684"></a><span class="lineno">  684</span>&#160;</div><div class="line"><a name="l00685"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a307116d0fabcf2058e5f4140d95f0775">  685</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeFill)</div><div class="line"><a name="l00686"></a><span class="lineno">  686</span>&#160;{</div><div class="line"><a name="l00687"></a><span class="lineno">  687</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;fill&quot;</span>);</div><div class="line"><a name="l00688"></a><span class="lineno">  688</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>);</div><div class="line"><a name="l00689"></a><span class="lineno">  689</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({1, 3, 3, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00690"></a><span class="lineno">  690</span>&#160;</div><div class="line"><a name="l00691"></a><span class="lineno">  691</span>&#160;    <a class="code" href="structarmnn_1_1_fill_descriptor.xhtml">armnn::FillDescriptor</a> descriptor(1.0f);</div><div class="line"><a name="l00692"></a><span class="lineno">  692</span>&#160;</div><div class="line"><a name="l00693"></a><span class="lineno">  693</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00694"></a><span class="lineno">  694</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00695"></a><span class="lineno">  695</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> fillLayer = network-&gt;AddFillLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l00696"></a><span class="lineno">  696</span>&#160; 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   inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00702"></a><span class="lineno">  702</span>&#160;    fillLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00703"></a><span class="lineno">  703</span>&#160;</div><div class="line"><a name="l00704"></a><span class="lineno">  704</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00705"></a><span class="lineno">  705</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00706"></a><span class="lineno">  706</span>&#160;</div><div class="line"><a name="l00707"></a><span class="lineno">  707</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::FillDescriptor&gt;</a> verifier(layerName, {inputInfo}, {outputInfo}, descriptor);</div><div class="line"><a name="l00708"></a><span class="lineno">  708</span>&#160;</div><div class="line"><a name="l00709"></a><span class="lineno">  709</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00710"></a><span class="lineno">  710</span>&#160;}</div><div class="line"><a name="l00711"></a><span class="lineno">  711</span>&#160;</div><div class="line"><a name="l00712"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a9e151842e28471a4e04ee9c5f5c05a74">  712</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeFloor)</div><div class="line"><a name="l00713"></a><span class="lineno">  713</span>&#160;{</div><div class="line"><a name="l00714"></a><span class="lineno">  714</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;floor&quot;</span>);</div><div class="line"><a name="l00715"></a><span class="lineno">  715</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({4,4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00716"></a><span class="lineno">  716</span>&#160;</div><div class="line"><a name="l00717"></a><span class="lineno">  717</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00718"></a><span class="lineno">  718</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00719"></a><span class="lineno">  719</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> floorLayer = network-&gt;AddFloorLayer(layerName.c_str());</div><div class="line"><a name="l00720"></a><span class="lineno">  720</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00721"></a><span class="lineno">  721</span>&#160;</div><div class="line"><a name="l00722"></a><span class="lineno">  722</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(floorLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00723"></a><span class="lineno">  723</span>&#160;    floorLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00724"></a><span class="lineno">  724</span>&#160;</div><div class="line"><a name="l00725"></a><span class="lineno">  725</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l00726"></a><span class="lineno">  726</span>&#160;    floorLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l00727"></a><span class="lineno">  727</span>&#160;</div><div class="line"><a name="l00728"></a><span class="lineno">  728</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00729"></a><span class="lineno">  729</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00730"></a><span class="lineno">  730</span>&#160;</div><div class="line"><a name="l00731"></a><span class="lineno">  731</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>});</div><div class="line"><a name="l00732"></a><span class="lineno">  732</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00733"></a><span class="lineno">  733</span>&#160;}</div><div class="line"><a name="l00734"></a><span class="lineno">  734</span>&#160;</div><div class="line"><a name="l00735"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a0d3a0736e9d014001bd37e232c54ff48">  735</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeFullyConnected)</div><div class="line"><a name="l00736"></a><span class="lineno">  736</span>&#160;{</div><div class="line"><a name="l00737"></a><span class="lineno">  737</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;fullyConnected&quot;</span>);</div><div class="line"><a name="l00738"></a><span class="lineno">  738</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo ({ 2, 5, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00739"></a><span class="lineno">  739</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00740"></a><span class="lineno">  740</span>&#160;</div><div class="line"><a name="l00741"></a><span class="lineno">  741</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsInfo({ 5, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00742"></a><span class="lineno">  742</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesInfo ({ 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00743"></a><span class="lineno">  743</span>&#160;    std::vector&lt;float&gt; weightsData = GenerateRandomData&lt;float&gt;(weightsInfo.GetNumElements());</div><div class="line"><a name="l00744"></a><span class="lineno">  744</span>&#160;    std::vector&lt;float&gt; biasesData  = GenerateRandomData&lt;float&gt;(biasesInfo.GetNumElements());</div><div class="line"><a name="l00745"></a><span class="lineno">  745</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights(weightsInfo, weightsData);</div><div class="line"><a name="l00746"></a><span class="lineno">  746</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> biases(biasesInfo, biasesData);</div><div class="line"><a name="l00747"></a><span class="lineno">  747</span>&#160;</div><div class="line"><a name="l00748"></a><span class="lineno">  748</span>&#160;    <a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">armnn::FullyConnectedDescriptor</a> descriptor;</div><div class="line"><a name="l00749"></a><span class="lineno">  749</span>&#160;    descriptor.<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="l00750"></a><span class="lineno">  750</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml#a281fcaec86e17c97f7b8402633f6b55a">m_TransposeWeightMatrix</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00751"></a><span class="lineno">  751</span>&#160;</div><div class="line"><a name="l00752"></a><span class="lineno">  752</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00753"></a><span class="lineno">  753</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00754"></a><span class="lineno">  754</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> fullyConnectedLayer =</div><div class="line"><a name="l00755"></a><span class="lineno">  755</span>&#160;        network-&gt;AddFullyConnectedLayer(descriptor,</div><div class="line"><a name="l00756"></a><span class="lineno">  756</span>&#160;                                        weights,</div><div class="line"><a name="l00757"></a><span class="lineno">  757</span>&#160;                                        <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional&lt;armnn::ConstTensor&gt;</a>(biases),</div><div class="line"><a name="l00758"></a><span class="lineno">  758</span>&#160;                                        layerName.c_str());</div><div class="line"><a name="l00759"></a><span class="lineno">  759</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00760"></a><span class="lineno">  760</span>&#160;</div><div class="line"><a name="l00761"></a><span class="lineno">  761</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(fullyConnectedLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00762"></a><span class="lineno">  762</span>&#160;    fullyConnectedLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00763"></a><span class="lineno">  763</span>&#160;</div><div class="line"><a name="l00764"></a><span class="lineno">  764</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00765"></a><span class="lineno">  765</span>&#160;    fullyConnectedLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00766"></a><span class="lineno">  766</span>&#160;</div><div class="line"><a name="l00767"></a><span class="lineno">  767</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00768"></a><span class="lineno">  768</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00769"></a><span class="lineno">  769</span>&#160;</div><div class="line"><a name="l00770"></a><span class="lineno">  770</span>&#160;    <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt; constants {weights, biases};</div><div class="line"><a name="l00771"></a><span class="lineno">  771</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml">LayerVerifierBaseWithDescriptorAndConstants&lt;armnn::FullyConnectedDescriptor&gt;</a> verifier(</div><div class="line"><a name="l00772"></a><span class="lineno">  772</span>&#160;            layerName, {inputInfo}, {outputInfo}, descriptor, constants);</div><div class="line"><a name="l00773"></a><span class="lineno">  773</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00774"></a><span class="lineno">  774</span>&#160;}</div><div class="line"><a name="l00775"></a><span class="lineno">  775</span>&#160;</div><div class="line"><a name="l00776"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a5174c1e8962eda5aab37f17d72506c75">  776</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeGather)</div><div class="line"><a name="l00777"></a><span class="lineno">  777</span>&#160;{</div><div class="line"><a name="l00778"></a><span class="lineno">  778</span>&#160;    <span class="keyword">using</span> <a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">GatherDescriptor</a> = <a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">armnn::GatherDescriptor</a>;</div><div class="line"><a name="l00779"></a><span class="lineno">  779</span>&#160;    <span class="keyword">class </span>GatherLayerVerifier : <span class="keyword">public</span> <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor</a>&lt;GatherDescriptor&gt;</div><div class="line"><a name="l00780"></a><span class="lineno">  780</span>&#160;    {</div><div class="line"><a name="l00781"></a><span class="lineno">  781</span>&#160;    <span class="keyword">public</span>:</div><div class="line"><a name="l00782"></a><span class="lineno">  782</span>&#160;        GatherLayerVerifier(<span class="keyword">const</span> std::string&amp; layerName,</div><div class="line"><a name="l00783"></a><span class="lineno">  783</span>&#160;                            <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; inputInfos,</div><div class="line"><a name="l00784"></a><span class="lineno">  784</span>&#160;                            <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; outputInfos,</div><div class="line"><a name="l00785"></a><span class="lineno">  785</span>&#160;                            <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">GatherDescriptor</a>&amp; descriptor)</div><div class="line"><a name="l00786"></a><span class="lineno">  786</span>&#160;            : <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;GatherDescriptor&gt;</a>(layerName, inputInfos, outputInfos, descriptor) {}</div><div class="line"><a name="l00787"></a><span class="lineno">  787</span>&#160;</div><div class="line"><a name="l00788"></a><span class="lineno">  788</span>&#160;        <span class="keywordtype">void</span> ExecuteStrategy(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer,</div><div class="line"><a name="l00789"></a><span class="lineno">  789</span>&#160;                             <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_base_descriptor.xhtml">armnn::BaseDescriptor</a>&amp; descriptor,</div><div class="line"><a name="l00790"></a><span class="lineno">  790</span>&#160;                             <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants,</div><div class="line"><a name="l00791"></a><span class="lineno">  791</span>&#160;                             <span class="keyword">const</span> <span class="keywordtype">char</span>* name,</div><div class="line"><a name="l00792"></a><span class="lineno">  792</span>&#160;                             <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> <span class="keywordtype">id</span> = 0)<span class="keyword"> override</span></div><div class="line"><a name="l00793"></a><span class="lineno">  793</span>&#160;<span class="keyword">        </span>{</div><div class="line"><a name="l00794"></a><span class="lineno">  794</span>&#160;            <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a>(constants, <span class="keywordtype">id</span>);</div><div class="line"><a name="l00795"></a><span class="lineno">  795</span>&#160;            <span class="keywordflow">switch</span> (layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">GetType</a>())</div><div class="line"><a name="l00796"></a><span class="lineno">  796</span>&#160;            {</div><div class="line"><a name="l00797"></a><span class="lineno">  797</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l00798"></a><span class="lineno">  798</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l00799"></a><span class="lineno">  799</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l00800"></a><span class="lineno">  800</span>&#160;                <span class="keywordflow">default</span>:</div><div class="line"><a name="l00801"></a><span class="lineno">  801</span>&#160;                {</div><div class="line"><a name="l00802"></a><span class="lineno">  802</span>&#160;                    VerifyNameAndConnections(layer, name);</div><div class="line"><a name="l00803"></a><span class="lineno">  803</span>&#160;                    <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">GatherDescriptor</a>&amp; layerDescriptor = <span class="keyword">static_cast&lt;</span><span class="keyword">const </span><a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">GatherDescriptor</a>&amp;<span class="keyword">&gt;</span>(descriptor);</div><div class="line"><a name="l00804"></a><span class="lineno">  804</span>&#160;                    BOOST_CHECK(layerDescriptor.<a class="code" href="structarmnn_1_1_gather_descriptor.xhtml#a35d11c7d509d1adbae1ae01c58394a7f">m_Axis</a> == m_Descriptor.m_Axis);</div><div class="line"><a name="l00805"></a><span class="lineno">  805</span>&#160;                }</div><div class="line"><a name="l00806"></a><span class="lineno">  806</span>&#160;            }</div><div class="line"><a name="l00807"></a><span class="lineno">  807</span>&#160;        }</div><div class="line"><a name="l00808"></a><span class="lineno">  808</span>&#160;    };</div><div class="line"><a name="l00809"></a><span class="lineno">  809</span>&#160;</div><div class="line"><a name="l00810"></a><span class="lineno">  810</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;gather&quot;</span>);</div><div class="line"><a name="l00811"></a><span class="lineno">  811</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> paramsInfo({ 8 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>);</div><div class="line"><a name="l00812"></a><span class="lineno">  812</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({ 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>);</div><div class="line"><a name="l00813"></a><span class="lineno">  813</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> indicesInfo({ 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>);</div><div class="line"><a name="l00814"></a><span class="lineno">  814</span>&#160;    <a class="code" href="structarmnn_1_1_gather_descriptor.xhtml">GatherDescriptor</a> descriptor;</div><div class="line"><a name="l00815"></a><span class="lineno">  815</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_gather_descriptor.xhtml#a35d11c7d509d1adbae1ae01c58394a7f">m_Axis</a> = 1;</div><div class="line"><a name="l00816"></a><span class="lineno">  816</span>&#160;</div><div class="line"><a name="l00817"></a><span class="lineno">  817</span>&#160; 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   gatherLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00834"></a><span class="lineno">  834</span>&#160;</div><div class="line"><a name="l00835"></a><span class="lineno">  835</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(paramsInfo);</div><div class="line"><a name="l00836"></a><span class="lineno">  836</span>&#160;    constantLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(indicesInfo);</div><div class="line"><a name="l00837"></a><span class="lineno">  837</span>&#160;    gatherLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l00838"></a><span class="lineno">  838</span>&#160;</div><div class="line"><a name="l00839"></a><span class="lineno">  839</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00840"></a><span class="lineno">  840</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00841"></a><span class="lineno">  841</span>&#160;</div><div class="line"><a name="l00842"></a><span class="lineno">  842</span>&#160;    GatherLayerVerifier verifier(layerName, {paramsInfo, indicesInfo}, {outputInfo}, descriptor);</div><div class="line"><a name="l00843"></a><span class="lineno">  843</span>&#160;    deserializedNetwork-&gt;ExecuteStrategy(verifier);</div><div class="line"><a name="l00844"></a><span class="lineno">  844</span>&#160;}</div><div class="line"><a name="l00845"></a><span class="lineno">  845</span>&#160;</div><div class="line"><a name="l00846"></a><span class="lineno">  846</span>&#160;</div><div class="line"><a name="l00847"></a><span class="lineno">  847</span>&#160;<span class="comment">// NOTE: Until the deprecated AddGreaterLayer disappears this test checks that calling</span></div><div class="line"><a name="l00848"></a><span class="lineno">  848</span>&#160;<span class="comment">//       AddGreaterLayer places a ComparisonLayer into the serialized format and that</span></div><div class="line"><a name="l00849"></a><span class="lineno">  849</span>&#160;<span class="comment">//       when this deserialises we have a ComparisonLayer</span></div><div class="line"><a name="l00850"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#ae3e1ad8acde8d817d7d93ed3dcd39ae9">  850</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeGreaterDeprecated)</div><div class="line"><a name="l00851"></a><span class="lineno">  851</span>&#160;{</div><div class="line"><a name="l00852"></a><span class="lineno">  852</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;greater&quot;</span>);</div><div class="line"><a name="l00853"></a><span class="lineno">  853</span>&#160;</div><div class="line"><a name="l00854"></a><span class="lineno">  854</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> shape{2, 1, 2, 4};</div><div class="line"><a name="l00855"></a><span class="lineno">  855</span>&#160;</div><div class="line"><a name="l00856"></a><span class="lineno">  856</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo  = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00857"></a><span class="lineno">  857</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a>);</div><div class="line"><a name="l00858"></a><span class="lineno">  858</span>&#160;</div><div class="line"><a name="l00859"></a><span class="lineno">  859</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00860"></a><span class="lineno">  860</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer0 = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00861"></a><span class="lineno">  861</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1 = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l00862"></a><span class="lineno">  862</span>&#160;    <a class="code" href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l00863"></a><span class="lineno">  863</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> equalLayer = network-&gt;AddGreaterLayer(layerName.c_str());</div><div class="line"><a name="l00864"></a><span class="lineno">  864</span>&#160;    <a class="code" href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="line"><a name="l00865"></a><span class="lineno">  865</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00866"></a><span class="lineno">  866</span>&#160;</div><div class="line"><a name="l00867"></a><span class="lineno">  867</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(equalLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00868"></a><span class="lineno">  868</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(equalLayer-&gt;GetInputSlot(1));</div><div class="line"><a name="l00869"></a><span class="lineno">  869</span>&#160;    equalLayer-&gt;GetOutputSlot(0).Connect(outputLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00870"></a><span class="lineno">  870</span>&#160;</div><div class="line"><a name="l00871"></a><span class="lineno">  871</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00872"></a><span class="lineno">  872</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l00873"></a><span class="lineno">  873</span>&#160;    equalLayer-&gt;GetOutputSlot(0).SetTensorInfo(outputInfo);</div><div class="line"><a name="l00874"></a><span class="lineno">  874</span>&#160;</div><div class="line"><a name="l00875"></a><span class="lineno">  875</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l00876"></a><span class="lineno">  876</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l00877"></a><span class="lineno">  877</span>&#160;</div><div class="line"><a name="l00878"></a><span class="lineno">  878</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, { inputInfo, inputInfo }, { outputInfo });</div><div class="line"><a name="l00879"></a><span class="lineno">  879</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l00880"></a><span class="lineno">  880</span>&#160;}</div><div class="line"><a name="l00881"></a><span class="lineno">  881</span>&#160;</div><div class="line"><a name="l00882"></a><span class="lineno">  882</span>&#160;</div><div class="line"><a name="l00883"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a49a39142f8899f9220b03c20ee3fe7db">  883</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeInstanceNormalization)</div><div class="line"><a name="l00884"></a><span class="lineno">  884</span>&#160;{</div><div class="line"><a name="l00885"></a><span class="lineno">  885</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;instanceNormalization&quot;</span>);</div><div class="line"><a name="l00886"></a><span class="lineno">  886</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 2, 1, 5 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00887"></a><span class="lineno">  887</span>&#160;</div><div class="line"><a name="l00888"></a><span class="lineno">  888</span>&#160;    <a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml">armnn::InstanceNormalizationDescriptor</a> descriptor;</div><div class="line"><a name="l00889"></a><span class="lineno">  889</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a5e078fd505aef7bccaa05c8058e096cc">m_Gamma</a>      = 1.1f;</div><div class="line"><a name="l00890"></a><span class="lineno">  890</span>&#160;    descriptor.m_Beta       = 0.1f;</div><div class="line"><a name="l00891"></a><span class="lineno">  891</span>&#160;    descriptor.m_Eps        = 0.0001f;</div><div class="line"><a name="l00892"></a><span class="lineno">  892</span>&#160;    descriptor.m_DataLayout = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l00893"></a><span class="lineno">  893</span>&#160;</div><div class="line"><a name="l00894"></a><span class="lineno">  894</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l00895"></a><span class="lineno">  895</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer        = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l00896"></a><span class="lineno">  896</span>&#160; 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   instanceNormLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00902"></a><span class="lineno">  902</span>&#160;</div><div class="line"><a name="l00903"></a><span class="lineno">  903</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l00904"></a><span class="lineno">  904</span>&#160; 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   <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;logicalBinaryAnd&quot;</span>);</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>&#160;</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a> shape{2, 1, 2, 2};</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>&#160;</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo  = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(shape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</a>);</div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>&#160; 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   deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>&#160;}</div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>&#160;</div><div class="line"><a name="l01032"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a7491d2a9c23204f9c2b05723810d6acd"> 1032</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeLogicalUnary)</div><div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>&#160;{</div><div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;elementwiseUnaryLogicalNot&quot;</span>);</div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>&#160;</div><div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>&#160; 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   deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>&#160;}</div><div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>&#160;</div><div class="line"><a name="l01065"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a6f57bfeb8cd67cdf480f23030b374331"> 1065</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeLogSoftmax)</div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>&#160;{</div><div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;log_softmax&quot;</span>);</div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({1, 10}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>&#160;</div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>&#160;    <a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml">armnn::LogSoftmaxDescriptor</a> descriptor;</div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = 1.0f;</div><div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>&#160;    descriptor.m_Axis = -1;</div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>&#160;</div><div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer      = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> logSoftmaxLayer = network-&gt;AddLogSoftmaxLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer     = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>&#160;</div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(logSoftmaxLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>&#160;    logSoftmaxLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>&#160;</div><div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>&#160;    logSoftmaxLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>&#160;</div><div class="line"><a name="l01085"></a><span class="lineno"> 1085</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>&#160;</div><div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::LogSoftmaxDescriptor&gt;</a> verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, descriptor);</div><div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>&#160;}</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>&#160;</div><div class="line"><a name="l01092"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#aeedeb69141be5280c53e327a2ac76320"> 1092</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeMaximum)</div><div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>&#160;{</div><div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;maximum&quot;</span>);</div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 2, 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>&#160;</div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer0 = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1 = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> maximumLayer = network-&gt;AddMaximumLayer(layerName.c_str());</div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>&#160;</div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(maximumLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(maximumLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>&#160;    maximumLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>&#160;</div><div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>&#160;    maximumLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>&#160;</div><div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>&#160;</div><div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {info});</div><div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>&#160;}</div><div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>&#160;</div><div class="line"><a name="l01118"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a4da2b73764b4e976afb82b8864b99be8"> 1118</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeMean)</div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>&#160;{</div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;mean&quot;</span>);</div><div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({1, 1, 3, 2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({1, 1, 1, 2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>&#160;</div><div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>&#160;    <a class="code" href="structarmnn_1_1_mean_descriptor.xhtml">armnn::MeanDescriptor</a> descriptor;</div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">m_Axis</a> = { 2 };</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>&#160;    descriptor.m_KeepDims = <span class="keyword">true</span>;</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>&#160;</div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer   = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> meanLayer = network-&gt;AddMeanLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer  = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>&#160;</div><div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(meanLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>&#160;    meanLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>&#160;</div><div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>&#160;    meanLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>&#160;</div><div class="line"><a name="l01139"></a><span class="lineno"> 1139</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>&#160;</div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::MeanDescriptor&gt;</a> verifier(layerName, {inputInfo}, {outputInfo}, descriptor);</div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>&#160;}</div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>&#160;</div><div class="line"><a name="l01146"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#aa5b91e9c6d7ba20294ff5416969a85cf"> 1146</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeMerge)</div><div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>&#160;{</div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;merge&quot;</span>);</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 2, 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>&#160;</div><div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer0 = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1 = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> mergeLayer = network-&gt;AddMergeLayer(layerName.c_str());</div><div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>&#160;</div><div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(mergeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(mergeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>&#160;    mergeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>&#160;</div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>&#160;    mergeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>&#160;</div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>&#160;</div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {info});</div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>&#160;}</div><div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>&#160;</div><div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>&#160;<span class="keyword">class </span>MergerLayerVerifier : <span class="keyword">public</span> <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor</a>&lt;armnn::OriginsDescriptor&gt;</div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>&#160;{</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>&#160;    MergerLayerVerifier(<span class="keyword">const</span> std::string&amp; layerName,</div><div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>&#160;                        <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; inputInfos,</div><div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>&#160;                        <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; outputInfos,</div><div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>&#160;                        <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_origins_descriptor.xhtml">armnn::OriginsDescriptor</a>&amp; descriptor)</div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>&#160;        : <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::OriginsDescriptor&gt;</a>(layerName, inputInfos, outputInfos, descriptor) {}</div><div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>&#160;</div><div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>&#160;    <span class="keywordtype">void</span> ExecuteStrategy(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer,</div><div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>&#160;                         <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_base_descriptor.xhtml">armnn::BaseDescriptor</a>&amp; descriptor,</div><div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>&#160;                         <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants,</div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>&#160;                         <span class="keyword">const</span> <span class="keywordtype">char</span>* name,</div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>&#160;                         <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> <span class="keywordtype">id</span> = 0)<span class="keyword"> override</span></div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>&#160;<span class="keyword">    </span>{</div><div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>&#160;        <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a>(descriptor, constants, <span class="keywordtype">id</span>);</div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>&#160;        <span class="keywordflow">switch</span> (layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">GetType</a>())</div><div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>&#160;        {</div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>&#160;            <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>&#160;            <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>&#160;            <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a68be4837f6c739877233e527a996dd00">armnn::LayerType::Merge</a>:</div><div class="line"><a name="l01193"></a><span class="lineno"> 1193</span>&#160;            {</div><div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>&#160;                <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>(<span class="stringliteral">&quot;MergerLayer should have translated to ConcatLayer&quot;</span>);</div><div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>&#160;                <span class="keywordflow">break</span>;</div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>&#160;            }</div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>&#160;            <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ae20f0f2826a6549809f050b86274567f">armnn::LayerType::Concat</a>:</div><div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>&#160;            {</div><div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>&#160;                VerifyNameAndConnections(layer, name);</div><div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>&#160;                <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_origins_descriptor.xhtml">armnn::MergerDescriptor</a>&amp; layerDescriptor =</div><div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>&#160;                        <span class="keyword">static_cast&lt;</span><span class="keyword">const </span><a class="code" href="structarmnn_1_1_origins_descriptor.xhtml">armnn::MergerDescriptor</a>&amp;<span class="keyword">&gt;</span>(descriptor);</div><div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>&#160;                VerifyDescriptor(layerDescriptor);</div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>&#160;                <span class="keywordflow">break</span>;</div><div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>&#160;            }</div><div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>&#160;            <span class="keywordflow">default</span>:</div><div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>&#160;            {</div><div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>&#160;                <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>(<span class="stringliteral">&quot;Unexpected layer type in Merge test model&quot;</span>);</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>&#160;            }</div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>&#160;        }</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>&#160;    }</div><div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>&#160;};</div><div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>&#160;</div><div class="line"><a name="l01213"></a><span class="lineno"> 1213</span>&#160;<span class="comment">// NOTE: Until the deprecated AddMergerLayer disappears this test checks that calling</span></div><div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>&#160;<span class="comment">//       AddMergerLayer places a ConcatLayer into the serialized format and that</span></div><div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>&#160;<span class="comment">//       when this deserialises we have a ConcatLayer</span></div><div class="line"><a name="l01216"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#ac5c00e890d80662b6fe3fea6c898b66f"> 1216</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeMerger)</div><div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>&#160;{</div><div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;merger&quot;</span>);</div><div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({2, 3, 2, 2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({4, 3, 2, 2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>&#160;</div><div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>&#160; 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   inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01371"></a><span class="lineno"> 1371</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01372"></a><span class="lineno"> 1372</span>&#160;    minimumLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01373"></a><span class="lineno"> 1373</span>&#160;</div><div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01375"></a><span class="lineno"> 1375</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01376"></a><span class="lineno"> 1376</span>&#160;</div><div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {info});</div><div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01379"></a><span class="lineno"> 1379</span>&#160;}</div><div class="line"><a name="l01380"></a><span class="lineno"> 1380</span>&#160;</div><div class="line"><a name="l01381"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a64531a96adf17b0fda1da04c5233a6b0"> 1381</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeMultiplication)</div><div class="line"><a name="l01382"></a><span class="lineno"> 1382</span>&#160;{</div><div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;multiplication&quot;</span>);</div><div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 5, 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>&#160;</div><div class="line"><a name="l01386"></a><span class="lineno"> 1386</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer0 = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01388"></a><span class="lineno"> 1388</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1 = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l01389"></a><span class="lineno"> 1389</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> multiplicationLayer = network-&gt;AddMultiplicationLayer(layerName.c_str());</div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>&#160;</div><div class="line"><a name="l01392"></a><span class="lineno"> 1392</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(multiplicationLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(multiplicationLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l01394"></a><span class="lineno"> 1394</span>&#160;    multiplicationLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>&#160;</div><div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>&#160;    multiplicationLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>&#160;</div><div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>&#160;</div><div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {info});</div><div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>&#160;}</div><div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>&#160;</div><div class="line"><a name="l01407"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a2bb05baf0128ccdc37d28da84f8d5986"> 1407</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializePrelu)</div><div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>&#160;{</div><div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;prelu&quot;</span>);</div><div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>&#160;</div><div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo ({ 4, 1, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01412"></a><span class="lineno"> 1412</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> alphaTensorInfo ({ 5, 4, 3, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>&#160;</div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> alphaLayer = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> preluLayer = network-&gt;AddPreluLayer(layerName.c_str());</div><div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>&#160;</div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(preluLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>&#160;    alphaLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(preluLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>&#160;    preluLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>&#160;</div><div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputTensorInfo);</div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>&#160;    alphaLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(alphaTensorInfo);</div><div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>&#160;    preluLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>&#160;</div><div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01430"></a><span class="lineno"> 1430</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>&#160;</div><div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {inputTensorInfo, alphaTensorInfo}, {outputTensorInfo});</div><div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01434"></a><span class="lineno"> 1434</span>&#160;}</div><div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>&#160;</div><div class="line"><a name="l01436"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#afa5c407820579e1e5c0c21a5e189fc15"> 1436</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeNormalization)</div><div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>&#160;{</div><div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>&#160; 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   desc.m_StrideX             = 2;</div><div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>&#160;    desc.m_StrideY             = 2;</div><div class="line"><a name="l01595"></a><span class="lineno"> 1595</span>&#160;</div><div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01597"></a><span class="lineno"> 1597</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01598"></a><span class="lineno"> 1598</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> pooling2dLayer = network-&gt;AddPooling2dLayer(desc, layerName.c_str());</div><div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>&#160;</div><div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(pooling2dLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>&#160;    pooling2dLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>&#160;</div><div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l01605"></a><span class="lineno"> 1605</span>&#160;    pooling2dLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>&#160;</div><div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>&#160;</div><div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::Pooling2dDescriptor&gt;</a> verifier(</div><div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>&#160;            layerName, {inputInfo}, {outputInfo}, desc);</div><div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01613"></a><span class="lineno"> 1613</span>&#160;}</div><div class="line"><a name="l01614"></a><span class="lineno"> 1614</span>&#160;</div><div class="line"><a name="l01615"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#aba0c861593907248e1d293a588383bb1"> 1615</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeQuantize)</div><div class="line"><a name="l01616"></a><span class="lineno"> 1616</span>&#160;{</div><div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;quantize&quot;</span>);</div><div class="line"><a name="l01618"></a><span class="lineno"> 1618</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 2, 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01619"></a><span class="lineno"> 1619</span>&#160;</div><div class="line"><a name="l01620"></a><span class="lineno"> 1620</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01621"></a><span class="lineno"> 1621</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> quantizeLayer = network-&gt;AddQuantizeLayer(layerName.c_str());</div><div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>&#160;</div><div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(quantizeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>&#160;    quantizeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>&#160;</div><div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01629"></a><span class="lineno"> 1629</span>&#160;    quantizeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01630"></a><span class="lineno"> 1630</span>&#160;</div><div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01632"></a><span class="lineno"> 1632</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>&#160;</div><div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>});</div><div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01636"></a><span class="lineno"> 1636</span>&#160;}</div><div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>&#160;</div><div class="line"><a name="l01638"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#acfbf67786378562c5d2bb9591a17e0d0"> 1638</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeRank)</div><div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>&#160;{</div><div class="line"><a name="l01640"></a><span class="lineno"> 1640</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;rank&quot;</span>);</div><div class="line"><a name="l01641"></a><span class="lineno"> 1641</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({1, 9}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01642"></a><span class="lineno"> 1642</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</a>);</div><div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>&#160;</div><div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> rankLayer = network-&gt;AddRankLayer(layerName.c_str());</div><div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>&#160;</div><div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(rankLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01650"></a><span class="lineno"> 1650</span>&#160;    rankLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>&#160;</div><div class="line"><a name="l01652"></a><span class="lineno"> 1652</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l01653"></a><span class="lineno"> 1653</span>&#160;    rankLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>&#160;</div><div class="line"><a name="l01655"></a><span class="lineno"> 1655</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01656"></a><span class="lineno"> 1656</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01657"></a><span class="lineno"> 1657</span>&#160;</div><div class="line"><a name="l01658"></a><span class="lineno"> 1658</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {inputInfo}, {outputInfo});</div><div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01660"></a><span class="lineno"> 1660</span>&#160;}</div><div class="line"><a name="l01661"></a><span class="lineno"> 1661</span>&#160;</div><div class="line"><a name="l01662"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a7cabbe04690c509789030f2df65a4f29"> 1662</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeReduceSum)</div><div class="line"><a name="l01663"></a><span class="lineno"> 1663</span>&#160;{</div><div class="line"><a name="l01664"></a><span class="lineno"> 1664</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;Reduce_Sum&quot;</span>);</div><div class="line"><a name="l01665"></a><span class="lineno"> 1665</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({1, 1, 3, 2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({1, 1, 1, 2}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>&#160;</div><div class="line"><a name="l01668"></a><span class="lineno"> 1668</span>&#160;    <a class="code" href="structarmnn_1_1_reduce_descriptor.xhtml">armnn::ReduceDescriptor</a> descriptor;</div><div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_reduce_descriptor.xhtml#aa1c6fc8c96404252f1072632fc5acb59">m_vAxis</a> = { 2 };</div><div class="line"><a name="l01670"></a><span class="lineno"> 1670</span>&#160;    descriptor.m_ReduceOperation = <a class="code" href="namespacearmnn.xhtml#abc05539fc6e7907f32ef0fb242e3b3b0aa0ec87054b5e5b7847d0d8780a01a3d5">armnn::ReduceOperation::Sum</a>;</div><div class="line"><a name="l01671"></a><span class="lineno"> 1671</span>&#160;</div><div class="line"><a name="l01672"></a><span class="lineno"> 1672</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01673"></a><span class="lineno"> 1673</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer   = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01674"></a><span class="lineno"> 1674</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> reduceSumLayer = network-&gt;AddReduceLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01675"></a><span class="lineno"> 1675</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer  = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01676"></a><span class="lineno"> 1676</span>&#160;</div><div class="line"><a name="l01677"></a><span class="lineno"> 1677</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(reduceSumLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01678"></a><span class="lineno"> 1678</span>&#160;    reduceSumLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01679"></a><span class="lineno"> 1679</span>&#160;</div><div class="line"><a name="l01680"></a><span class="lineno"> 1680</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l01681"></a><span class="lineno"> 1681</span>&#160;    reduceSumLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01682"></a><span class="lineno"> 1682</span>&#160;</div><div class="line"><a name="l01683"></a><span class="lineno"> 1683</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01684"></a><span class="lineno"> 1684</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01685"></a><span class="lineno"> 1685</span>&#160;</div><div class="line"><a name="l01686"></a><span class="lineno"> 1686</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::ReduceDescriptor&gt;</a> verifier(layerName, {inputInfo}, {outputInfo}, descriptor);</div><div class="line"><a name="l01687"></a><span class="lineno"> 1687</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01688"></a><span class="lineno"> 1688</span>&#160;}</div><div class="line"><a name="l01689"></a><span class="lineno"> 1689</span>&#160;</div><div class="line"><a name="l01690"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a6e0afb5f057cb45dbbcf7c5efad61f20"> 1690</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeReshape)</div><div class="line"><a name="l01691"></a><span class="lineno"> 1691</span>&#160;{</div><div class="line"><a name="l01692"></a><span class="lineno"> 1692</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;reshape&quot;</span>);</div><div class="line"><a name="l01693"></a><span class="lineno"> 1693</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({1, 9}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01694"></a><span class="lineno"> 1694</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({3, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01695"></a><span class="lineno"> 1695</span>&#160;</div><div class="line"><a name="l01696"></a><span class="lineno"> 1696</span>&#160;    <a class="code" href="structarmnn_1_1_reshape_descriptor.xhtml">armnn::ReshapeDescriptor</a> descriptor({3, 3});</div><div class="line"><a name="l01697"></a><span class="lineno"> 1697</span>&#160;</div><div class="line"><a name="l01698"></a><span class="lineno"> 1698</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01699"></a><span class="lineno"> 1699</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01700"></a><span class="lineno"> 1700</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> reshapeLayer = network-&gt;AddReshapeLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01701"></a><span class="lineno"> 1701</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01702"></a><span class="lineno"> 1702</span>&#160;</div><div class="line"><a name="l01703"></a><span class="lineno"> 1703</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(reshapeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01704"></a><span class="lineno"> 1704</span>&#160;    reshapeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01705"></a><span class="lineno"> 1705</span>&#160;</div><div class="line"><a name="l01706"></a><span class="lineno"> 1706</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l01707"></a><span class="lineno"> 1707</span>&#160;    reshapeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01708"></a><span class="lineno"> 1708</span>&#160;</div><div class="line"><a name="l01709"></a><span class="lineno"> 1709</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01710"></a><span class="lineno"> 1710</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01711"></a><span class="lineno"> 1711</span>&#160;</div><div class="line"><a name="l01712"></a><span class="lineno"> 1712</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::ReshapeDescriptor&gt;</a> verifier(</div><div class="line"><a name="l01713"></a><span class="lineno"> 1713</span>&#160;            layerName, {inputInfo}, {outputInfo}, descriptor);</div><div class="line"><a name="l01714"></a><span class="lineno"> 1714</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01715"></a><span class="lineno"> 1715</span>&#160;}</div><div class="line"><a name="l01716"></a><span class="lineno"> 1716</span>&#160;</div><div class="line"><a name="l01717"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a66859a4301a19650149508458d36d5d6"> 1717</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeResize)</div><div class="line"><a name="l01718"></a><span class="lineno"> 1718</span>&#160;{</div><div class="line"><a name="l01719"></a><span class="lineno"> 1719</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;resize&quot;</span>);</div><div class="line"><a name="l01720"></a><span class="lineno"> 1720</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo  = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({1, 3, 5, 5}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01721"></a><span class="lineno"> 1721</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({1, 3, 2, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01722"></a><span class="lineno"> 1722</span>&#160;</div><div class="line"><a name="l01723"></a><span class="lineno"> 1723</span>&#160;    <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">armnn::ResizeDescriptor</a> desc;</div><div class="line"><a name="l01724"></a><span class="lineno"> 1724</span>&#160;    desc.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a>  = 4;</div><div class="line"><a name="l01725"></a><span class="lineno"> 1725</span>&#160;    desc.m_TargetHeight = 2;</div><div class="line"><a name="l01726"></a><span class="lineno"> 1726</span>&#160;    desc.m_Method       = <a class="code" href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a>;</div><div class="line"><a name="l01727"></a><span class="lineno"> 1727</span>&#160;    desc.m_AlignCorners = <span class="keyword">true</span>;</div><div class="line"><a name="l01728"></a><span class="lineno"> 1728</span>&#160;    desc.m_HalfPixelCenters = <span class="keyword">true</span>;</div><div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>&#160;</div><div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>&#160; 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   inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(resizeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01736"></a><span class="lineno"> 1736</span>&#160;    resizeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01737"></a><span class="lineno"> 1737</span>&#160;</div><div class="line"><a name="l01738"></a><span class="lineno"> 1738</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l01739"></a><span class="lineno"> 1739</span>&#160;    resizeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01740"></a><span class="lineno"> 1740</span>&#160;</div><div class="line"><a name="l01741"></a><span class="lineno"> 1741</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01742"></a><span class="lineno"> 1742</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01743"></a><span class="lineno"> 1743</span>&#160;</div><div class="line"><a name="l01744"></a><span class="lineno"> 1744</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::ResizeDescriptor&gt;</a> verifier(layerName, {inputInfo}, {outputInfo}, desc);</div><div class="line"><a name="l01745"></a><span class="lineno"> 1745</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01746"></a><span class="lineno"> 1746</span>&#160;}</div><div class="line"><a name="l01747"></a><span class="lineno"> 1747</span>&#160;</div><div class="line"><a name="l01748"></a><span class="lineno"> 1748</span>&#160;<span class="keyword">class </span>ResizeBilinearLayerVerifier : <span class="keyword">public</span> <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor</a>&lt;armnn::ResizeBilinearDescriptor&gt;</div><div class="line"><a name="l01749"></a><span class="lineno"> 1749</span>&#160;{</div><div class="line"><a name="l01750"></a><span class="lineno"> 1750</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l01751"></a><span class="lineno"> 1751</span>&#160;    ResizeBilinearLayerVerifier(<span class="keyword">const</span> std::string&amp; layerName,</div><div class="line"><a name="l01752"></a><span class="lineno"> 1752</span>&#160;                                <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; inputInfos,</div><div class="line"><a name="l01753"></a><span class="lineno"> 1753</span>&#160;                                <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; outputInfos,</div><div class="line"><a name="l01754"></a><span class="lineno"> 1754</span>&#160;                                <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml">armnn::ResizeBilinearDescriptor</a>&amp; descriptor)</div><div class="line"><a name="l01755"></a><span class="lineno"> 1755</span>&#160;        : <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::ResizeBilinearDescriptor&gt;</a>(</div><div class="line"><a name="l01756"></a><span class="lineno"> 1756</span>&#160;            layerName, inputInfos, outputInfos, descriptor) {}</div><div class="line"><a name="l01757"></a><span class="lineno"> 1757</span>&#160;</div><div class="line"><a name="l01758"></a><span class="lineno"> 1758</span>&#160;    <span class="keywordtype">void</span> ExecuteStrategy(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer,</div><div class="line"><a name="l01759"></a><span class="lineno"> 1759</span>&#160;                         <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_base_descriptor.xhtml">armnn::BaseDescriptor</a>&amp; descriptor,</div><div class="line"><a name="l01760"></a><span class="lineno"> 1760</span>&#160;                         <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants,</div><div class="line"><a name="l01761"></a><span class="lineno"> 1761</span>&#160;                         <span class="keyword">const</span> <span class="keywordtype">char</span>* name,</div><div class="line"><a name="l01762"></a><span class="lineno"> 1762</span>&#160;                         <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> <span class="keywordtype">id</span> = 0)<span class="keyword"> override</span></div><div class="line"><a name="l01763"></a><span class="lineno"> 1763</span>&#160;<span class="keyword">    </span>{</div><div class="line"><a name="l01764"></a><span class="lineno"> 1764</span>&#160;        <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a>(descriptor, constants, <span class="keywordtype">id</span>);</div><div class="line"><a name="l01765"></a><span class="lineno"> 1765</span>&#160;        <span class="keywordflow">switch</span> (layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">GetType</a>())</div><div class="line"><a name="l01766"></a><span class="lineno"> 1766</span>&#160;        {</div><div class="line"><a name="l01767"></a><span class="lineno"> 1767</span>&#160;            <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l01768"></a><span class="lineno"> 1768</span>&#160;            <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l01769"></a><span class="lineno"> 1769</span>&#160;            <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a9d723d04c40bfd81835c0766a698cf63">armnn::LayerType::Resize</a>:</div><div class="line"><a name="l01770"></a><span class="lineno"> 1770</span>&#160;            {</div><div class="line"><a name="l01771"></a><span class="lineno"> 1771</span>&#160;                VerifyNameAndConnections(layer, name);</div><div class="line"><a name="l01772"></a><span class="lineno"> 1772</span>&#160;                <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">armnn::ResizeDescriptor</a>&amp; layerDescriptor =</div><div class="line"><a name="l01773"></a><span class="lineno"> 1773</span>&#160;                        <span class="keyword">static_cast&lt;</span><span class="keyword">const </span><a class="code" href="structarmnn_1_1_resize_descriptor.xhtml">armnn::ResizeDescriptor</a>&amp;<span class="keyword">&gt;</span>(descriptor);</div><div class="line"><a name="l01774"></a><span class="lineno"> 1774</span>&#160;                BOOST_CHECK(layerDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a869254cb56968986a78a79e1d6d4a86b">m_Method</a>             == <a class="code" href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a>);</div><div class="line"><a name="l01775"></a><span class="lineno"> 1775</span>&#160;                BOOST_CHECK(layerDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a>        == m_Descriptor.m_TargetWidth);</div><div class="line"><a name="l01776"></a><span class="lineno"> 1776</span>&#160;                BOOST_CHECK(layerDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">m_TargetHeight</a>       == m_Descriptor.m_TargetHeight);</div><div class="line"><a name="l01777"></a><span class="lineno"> 1777</span>&#160;                BOOST_CHECK(layerDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>         == m_Descriptor.m_DataLayout);</div><div class="line"><a name="l01778"></a><span class="lineno"> 1778</span>&#160;                BOOST_CHECK(layerDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#ae1a4b3b6c60552509b89747cebb900a2">m_AlignCorners</a>       == m_Descriptor.m_AlignCorners);</div><div class="line"><a name="l01779"></a><span class="lineno"> 1779</span>&#160;                BOOST_CHECK(layerDescriptor.<a class="code" href="structarmnn_1_1_resize_descriptor.xhtml#a4022d5107338aaf5eb7abebf78a1360b">m_HalfPixelCenters</a>   == m_Descriptor.m_HalfPixelCenters);</div><div class="line"><a name="l01780"></a><span class="lineno"> 1780</span>&#160;                <span class="keywordflow">break</span>;</div><div class="line"><a name="l01781"></a><span class="lineno"> 1781</span>&#160;            }</div><div class="line"><a name="l01782"></a><span class="lineno"> 1782</span>&#160;            <span class="keywordflow">default</span>:</div><div class="line"><a name="l01783"></a><span class="lineno"> 1783</span>&#160;            {</div><div class="line"><a name="l01784"></a><span class="lineno"> 1784</span>&#160;                <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>(<span class="stringliteral">&quot;Unexpected layer type in test model. ResizeBiliniar &quot;</span></div><div class="line"><a name="l01785"></a><span class="lineno"> 1785</span>&#160;                                       <span class="stringliteral">&quot;should have translated to Resize&quot;</span>);</div><div class="line"><a name="l01786"></a><span class="lineno"> 1786</span>&#160;            }</div><div class="line"><a name="l01787"></a><span class="lineno"> 1787</span>&#160;        }</div><div class="line"><a name="l01788"></a><span class="lineno"> 1788</span>&#160;    }</div><div class="line"><a name="l01789"></a><span class="lineno"> 1789</span>&#160;};</div><div class="line"><a name="l01790"></a><span class="lineno"> 1790</span>&#160;</div><div class="line"><a name="l01791"></a><span class="lineno"> 1791</span>&#160;<span class="comment">// NOTE: Until the deprecated AddResizeBilinearLayer disappears this test checks that</span></div><div class="line"><a name="l01792"></a><span class="lineno"> 1792</span>&#160;<span class="comment">//       calling AddResizeBilinearLayer places a ResizeLayer into the serialized format</span></div><div class="line"><a name="l01793"></a><span class="lineno"> 1793</span>&#160;<span class="comment">//       and that when this deserialises we have a ResizeLayer</span></div><div class="line"><a name="l01794"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a245e67bfc92e7d3ebc671f58b01ef9a7"> 1794</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeResizeBilinear)</div><div class="line"><a name="l01795"></a><span class="lineno"> 1795</span>&#160;{</div><div class="line"><a name="l01796"></a><span class="lineno"> 1796</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;resizeBilinear&quot;</span>);</div><div class="line"><a name="l01797"></a><span class="lineno"> 1797</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo  = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({1, 3, 5, 5}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01798"></a><span class="lineno"> 1798</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({1, 3, 2, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01799"></a><span class="lineno"> 1799</span>&#160;</div><div class="line"><a name="l01800"></a><span class="lineno"> 1800</span>&#160;    <a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml">armnn::ResizeBilinearDescriptor</a> desc;</div><div class="line"><a name="l01801"></a><span class="lineno"> 1801</span>&#160;    desc.<a class="code" href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">m_TargetWidth</a>  = 4u;</div><div class="line"><a name="l01802"></a><span class="lineno"> 1802</span>&#160;    desc.m_TargetHeight = 2u;</div><div class="line"><a name="l01803"></a><span class="lineno"> 1803</span>&#160;    desc.m_AlignCorners = <span class="keyword">true</span>;</div><div class="line"><a name="l01804"></a><span class="lineno"> 1804</span>&#160;    desc.m_HalfPixelCenters = <span class="keyword">true</span>;</div><div class="line"><a name="l01805"></a><span class="lineno"> 1805</span>&#160;</div><div class="line"><a name="l01806"></a><span class="lineno"> 1806</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01807"></a><span class="lineno"> 1807</span>&#160; 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   inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(resizeLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l01814"></a><span class="lineno"> 1814</span>&#160;    resizeLayer-&gt;GetOutputSlot(0).Connect(outputLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l01815"></a><span class="lineno"> 1815</span>&#160;</div><div class="line"><a name="l01816"></a><span class="lineno"> 1816</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l01817"></a><span class="lineno"> 1817</span>&#160;    resizeLayer-&gt;GetOutputSlot(0).SetTensorInfo(outputInfo);</div><div class="line"><a name="l01818"></a><span class="lineno"> 1818</span>&#160;</div><div class="line"><a name="l01819"></a><span class="lineno"> 1819</span>&#160; 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   <span class="comment">// The hex data below is a flat buffer containing a simple network with an input,</span></div><div class="line"><a name="l01829"></a><span class="lineno"> 1829</span>&#160;    <span class="comment">// a ResizeBilinearLayer (now deprecated) and an output</span></div><div class="line"><a name="l01830"></a><span class="lineno"> 1830</span>&#160;    <span class="comment">//</span></div><div class="line"><a name="l01831"></a><span class="lineno"> 1831</span>&#160;    <span class="comment">// This test verifies that we can still deserialize this old-style model by replacing</span></div><div class="line"><a name="l01832"></a><span class="lineno"> 1832</span>&#160;    <span class="comment">// the ResizeBilinearLayer with an equivalent ResizeLayer</span></div><div class="line"><a name="l01833"></a><span class="lineno"> 1833</span>&#160;    <span class="keyword">const</span> std::vector&lt;uint8_t&gt; resizeBilinearModel =</div><div class="line"><a name="l01834"></a><span class="lineno"> 1834</span>&#160; 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   <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;softmax&quot;</span>);</div><div class="line"><a name="l01913"></a><span class="lineno"> 1913</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({1, 10}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01914"></a><span class="lineno"> 1914</span>&#160;</div><div class="line"><a name="l01915"></a><span class="lineno"> 1915</span>&#160;    <a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml">armnn::SoftmaxDescriptor</a> descriptor;</div><div class="line"><a name="l01916"></a><span class="lineno"> 1916</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_softmax_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = 1.0f;</div><div class="line"><a name="l01917"></a><span class="lineno"> 1917</span>&#160;</div><div class="line"><a name="l01918"></a><span class="lineno"> 1918</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01919"></a><span class="lineno"> 1919</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer   = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01920"></a><span class="lineno"> 1920</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> softmaxLayer = network-&gt;AddSoftmaxLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l01921"></a><span class="lineno"> 1921</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer  = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01922"></a><span class="lineno"> 1922</span>&#160;</div><div class="line"><a name="l01923"></a><span class="lineno"> 1923</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(softmaxLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01924"></a><span class="lineno"> 1924</span>&#160;    softmaxLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01925"></a><span class="lineno"> 1925</span>&#160;</div><div class="line"><a name="l01926"></a><span class="lineno"> 1926</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01927"></a><span class="lineno"> 1927</span>&#160;    softmaxLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l01928"></a><span class="lineno"> 1928</span>&#160;</div><div class="line"><a name="l01929"></a><span class="lineno"> 1929</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01930"></a><span class="lineno"> 1930</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01931"></a><span class="lineno"> 1931</span>&#160;</div><div class="line"><a name="l01932"></a><span class="lineno"> 1932</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::SoftmaxDescriptor&gt;</a> verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, descriptor);</div><div class="line"><a name="l01933"></a><span class="lineno"> 1933</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01934"></a><span class="lineno"> 1934</span>&#160;}</div><div class="line"><a name="l01935"></a><span class="lineno"> 1935</span>&#160;</div><div class="line"><a name="l01936"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a798088dcd410d5c4e70e619986a19fa1"> 1936</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeSpaceToBatchNd)</div><div class="line"><a name="l01937"></a><span class="lineno"> 1937</span>&#160;{</div><div class="line"><a name="l01938"></a><span class="lineno"> 1938</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;spaceToBatchNd&quot;</span>);</div><div class="line"><a name="l01939"></a><span class="lineno"> 1939</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({2, 1, 2, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01940"></a><span class="lineno"> 1940</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({8, 1, 1, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01941"></a><span class="lineno"> 1941</span>&#160;</div><div class="line"><a name="l01942"></a><span class="lineno"> 1942</span>&#160;    <a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml">armnn::SpaceToBatchNdDescriptor</a> desc;</div><div class="line"><a name="l01943"></a><span class="lineno"> 1943</span>&#160;    desc.<a class="code" href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a> = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div><div class="line"><a name="l01944"></a><span class="lineno"> 1944</span>&#160;    desc.m_BlockShape = {2, 2};</div><div class="line"><a name="l01945"></a><span class="lineno"> 1945</span>&#160;    desc.m_PadList = {{0, 0}, {2, 0}};</div><div class="line"><a name="l01946"></a><span class="lineno"> 1946</span>&#160;</div><div class="line"><a name="l01947"></a><span class="lineno"> 1947</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01948"></a><span class="lineno"> 1948</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01949"></a><span class="lineno"> 1949</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> spaceToBatchNdLayer = network-&gt;AddSpaceToBatchNdLayer(desc, layerName.c_str());</div><div class="line"><a name="l01950"></a><span class="lineno"> 1950</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01951"></a><span class="lineno"> 1951</span>&#160;</div><div class="line"><a name="l01952"></a><span class="lineno"> 1952</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(spaceToBatchNdLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01953"></a><span class="lineno"> 1953</span>&#160;    spaceToBatchNdLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01954"></a><span class="lineno"> 1954</span>&#160;</div><div class="line"><a name="l01955"></a><span class="lineno"> 1955</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l01956"></a><span class="lineno"> 1956</span>&#160;    spaceToBatchNdLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01957"></a><span class="lineno"> 1957</span>&#160;</div><div class="line"><a name="l01958"></a><span class="lineno"> 1958</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01959"></a><span class="lineno"> 1959</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01960"></a><span class="lineno"> 1960</span>&#160;</div><div class="line"><a name="l01961"></a><span class="lineno"> 1961</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::SpaceToBatchNdDescriptor&gt;</a> verifier(</div><div class="line"><a name="l01962"></a><span class="lineno"> 1962</span>&#160;            layerName, {inputInfo}, {outputInfo}, desc);</div><div class="line"><a name="l01963"></a><span class="lineno"> 1963</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01964"></a><span class="lineno"> 1964</span>&#160;}</div><div class="line"><a name="l01965"></a><span class="lineno"> 1965</span>&#160;</div><div class="line"><a name="l01966"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a46f46381910339f4154d071b074df35e"> 1966</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeSpaceToDepth)</div><div class="line"><a name="l01967"></a><span class="lineno"> 1967</span>&#160;{</div><div class="line"><a name="l01968"></a><span class="lineno"> 1968</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;spaceToDepth&quot;</span>);</div><div class="line"><a name="l01969"></a><span class="lineno"> 1969</span>&#160;</div><div class="line"><a name="l01970"></a><span class="lineno"> 1970</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo ({ 1, 16, 8,  3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01971"></a><span class="lineno"> 1971</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({ 1,  8, 4, 12 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01972"></a><span class="lineno"> 1972</span>&#160;</div><div class="line"><a name="l01973"></a><span class="lineno"> 1973</span>&#160;    <a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml">armnn::SpaceToDepthDescriptor</a> desc;</div><div class="line"><a name="l01974"></a><span class="lineno"> 1974</span>&#160;    desc.<a class="code" href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">m_BlockSize</a>  = 2;</div><div class="line"><a name="l01975"></a><span class="lineno"> 1975</span>&#160;    desc.m_DataLayout = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l01976"></a><span class="lineno"> 1976</span>&#160;</div><div class="line"><a name="l01977"></a><span class="lineno"> 1977</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l01978"></a><span class="lineno"> 1978</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer        = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l01979"></a><span class="lineno"> 1979</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> spaceToDepthLayer = network-&gt;AddSpaceToDepthLayer(desc, layerName.c_str());</div><div class="line"><a name="l01980"></a><span class="lineno"> 1980</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer       = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l01981"></a><span class="lineno"> 1981</span>&#160;</div><div class="line"><a name="l01982"></a><span class="lineno"> 1982</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(spaceToDepthLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01983"></a><span class="lineno"> 1983</span>&#160;    spaceToDepthLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l01984"></a><span class="lineno"> 1984</span>&#160;</div><div class="line"><a name="l01985"></a><span class="lineno"> 1985</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l01986"></a><span class="lineno"> 1986</span>&#160;    spaceToDepthLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l01987"></a><span class="lineno"> 1987</span>&#160;</div><div class="line"><a name="l01988"></a><span class="lineno"> 1988</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l01989"></a><span class="lineno"> 1989</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l01990"></a><span class="lineno"> 1990</span>&#160;</div><div class="line"><a name="l01991"></a><span class="lineno"> 1991</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::SpaceToDepthDescriptor&gt;</a> verifier(</div><div class="line"><a name="l01992"></a><span class="lineno"> 1992</span>&#160;            layerName, {inputInfo}, {outputInfo}, desc);</div><div class="line"><a name="l01993"></a><span class="lineno"> 1993</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l01994"></a><span class="lineno"> 1994</span>&#160;}</div><div class="line"><a name="l01995"></a><span class="lineno"> 1995</span>&#160;</div><div class="line"><a name="l01996"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#aad7569c190fcdb4901e8665c80df013b"> 1996</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeSplitter)</div><div class="line"><a name="l01997"></a><span class="lineno"> 1997</span>&#160;{</div><div class="line"><a name="l01998"></a><span class="lineno"> 1998</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numViews = 3;</div><div class="line"><a name="l01999"></a><span class="lineno"> 1999</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numDimensions = 4;</div><div class="line"><a name="l02000"></a><span class="lineno"> 2000</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = {1, 18, 4, 4};</div><div class="line"><a name="l02001"></a><span class="lineno"> 2001</span>&#160;    <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = {1, 6, 4, 4};</div><div class="line"><a name="l02002"></a><span class="lineno"> 2002</span>&#160;</div><div class="line"><a name="l02003"></a><span class="lineno"> 2003</span>&#160;    <span class="comment">// This is modelled on how the caffe parser sets up a splitter layer to partition an input along dimension one.</span></div><div class="line"><a name="l02004"></a><span class="lineno"> 2004</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> splitterDimSizes[4] = {<span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(inputShape[0]),</div><div class="line"><a name="l02005"></a><span class="lineno"> 2005</span>&#160;                                        static_cast&lt;unsigned int&gt;(inputShape[1]),</div><div class="line"><a name="l02006"></a><span class="lineno"> 2006</span>&#160;                                        <span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span>(inputShape[2]),</div><div class="line"><a name="l02007"></a><span class="lineno"> 2007</span>&#160;                                        static_cast&lt;unsigned int&gt;(inputShape[3])};</div><div class="line"><a name="l02008"></a><span class="lineno"> 2008</span>&#160;    splitterDimSizes[1] /= numViews;</div><div class="line"><a name="l02009"></a><span class="lineno"> 2009</span>&#160;    <a class="code" href="structarmnn_1_1_views_descriptor.xhtml">armnn::ViewsDescriptor</a> desc(numViews, numDimensions);</div><div class="line"><a name="l02010"></a><span class="lineno"> 2010</span>&#160;</div><div class="line"><a name="l02011"></a><span class="lineno"> 2011</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> g = 0; g &lt; numViews; ++g)</div><div class="line"><a name="l02012"></a><span class="lineno"> 2012</span>&#160;    {</div><div class="line"><a name="l02013"></a><span class="lineno"> 2013</span>&#160;        desc.<a class="code" href="structarmnn_1_1_views_descriptor.xhtml#a2b125117aa61f9baf3a9cb8658aa61a2">SetViewOriginCoord</a>(g, 1, splitterDimSizes[1] * g);</div><div class="line"><a name="l02014"></a><span class="lineno"> 2014</span>&#160;</div><div class="line"><a name="l02015"></a><span class="lineno"> 2015</span>&#160;        <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimIdx=0; dimIdx &lt; 4; dimIdx++)</div><div class="line"><a name="l02016"></a><span class="lineno"> 2016</span>&#160;        {</div><div class="line"><a name="l02017"></a><span class="lineno"> 2017</span>&#160;            desc.<a class="code" href="structarmnn_1_1_views_descriptor.xhtml#aae0893695f5803a3517985c7cb1ccb2e">SetViewSize</a>(g, dimIdx, splitterDimSizes[dimIdx]);</div><div class="line"><a name="l02018"></a><span class="lineno"> 2018</span>&#160;        }</div><div class="line"><a name="l02019"></a><span class="lineno"> 2019</span>&#160;    }</div><div class="line"><a name="l02020"></a><span class="lineno"> 2020</span>&#160;</div><div class="line"><a name="l02021"></a><span class="lineno"> 2021</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;splitter&quot;</span>);</div><div class="line"><a name="l02022"></a><span class="lineno"> 2022</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo(numDimensions, inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02023"></a><span class="lineno"> 2023</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo(numDimensions, outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02024"></a><span class="lineno"> 2024</span>&#160;</div><div class="line"><a name="l02025"></a><span class="lineno"> 2025</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l02026"></a><span class="lineno"> 2026</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l02027"></a><span class="lineno"> 2027</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> splitterLayer = network-&gt;AddSplitterLayer(desc, layerName.c_str());</div><div class="line"><a name="l02028"></a><span class="lineno"> 2028</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer0 = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l02029"></a><span class="lineno"> 2029</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer1 = network-&gt;AddOutputLayer(1);</div><div class="line"><a name="l02030"></a><span class="lineno"> 2030</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer2 = network-&gt;AddOutputLayer(2);</div><div class="line"><a name="l02031"></a><span class="lineno"> 2031</span>&#160;</div><div class="line"><a name="l02032"></a><span class="lineno"> 2032</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(splitterLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02033"></a><span class="lineno"> 2033</span>&#160;    splitterLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02034"></a><span class="lineno"> 2034</span>&#160;    splitterLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02035"></a><span class="lineno"> 2035</span>&#160;    splitterLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer2-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02036"></a><span class="lineno"> 2036</span>&#160;</div><div class="line"><a name="l02037"></a><span class="lineno"> 2037</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l02038"></a><span class="lineno"> 2038</span>&#160;    splitterLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l02039"></a><span class="lineno"> 2039</span>&#160;    splitterLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l02040"></a><span class="lineno"> 2040</span>&#160;    splitterLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(2).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l02041"></a><span class="lineno"> 2041</span>&#160;</div><div class="line"><a name="l02042"></a><span class="lineno"> 2042</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l02043"></a><span class="lineno"> 2043</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l02044"></a><span class="lineno"> 2044</span>&#160;</div><div class="line"><a name="l02045"></a><span class="lineno"> 2045</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::ViewsDescriptor&gt;</a> verifier(</div><div class="line"><a name="l02046"></a><span class="lineno"> 2046</span>&#160;            layerName, {inputInfo}, {outputInfo, outputInfo, outputInfo}, desc);</div><div class="line"><a name="l02047"></a><span class="lineno"> 2047</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l02048"></a><span class="lineno"> 2048</span>&#160;}</div><div class="line"><a name="l02049"></a><span class="lineno"> 2049</span>&#160;</div><div class="line"><a name="l02050"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a9e3547d945fb7ee85e09cfd3423780a9"> 2050</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeStack)</div><div class="line"><a name="l02051"></a><span class="lineno"> 2051</span>&#160;{</div><div class="line"><a name="l02052"></a><span class="lineno"> 2052</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;stack&quot;</span>);</div><div class="line"><a name="l02053"></a><span class="lineno"> 2053</span>&#160;</div><div class="line"><a name="l02054"></a><span class="lineno"> 2054</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo ({4, 3, 5}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02055"></a><span class="lineno"> 2055</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({4, 3, 2, 5}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02056"></a><span class="lineno"> 2056</span>&#160;</div><div class="line"><a name="l02057"></a><span class="lineno"> 2057</span>&#160;    <a class="code" href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a> descriptor(2, 2, {4, 3, 5});</div><div class="line"><a name="l02058"></a><span class="lineno"> 2058</span>&#160;</div><div class="line"><a name="l02059"></a><span class="lineno"> 2059</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l02060"></a><span class="lineno"> 2060</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1 = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l02061"></a><span class="lineno"> 2061</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer2 = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l02062"></a><span class="lineno"> 2062</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> stackLayer = network-&gt;AddStackLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02063"></a><span class="lineno"> 2063</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l02064"></a><span class="lineno"> 2064</span>&#160;</div><div class="line"><a name="l02065"></a><span class="lineno"> 2065</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(stackLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02066"></a><span class="lineno"> 2066</span>&#160;    inputLayer2-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(stackLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l02067"></a><span class="lineno"> 2067</span>&#160;    stackLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02068"></a><span class="lineno"> 2068</span>&#160;</div><div class="line"><a name="l02069"></a><span class="lineno"> 2069</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputTensorInfo);</div><div class="line"><a name="l02070"></a><span class="lineno"> 2070</span>&#160;    inputLayer2-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputTensorInfo);</div><div class="line"><a name="l02071"></a><span class="lineno"> 2071</span>&#160;    stackLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02072"></a><span class="lineno"> 2072</span>&#160;</div><div class="line"><a name="l02073"></a><span class="lineno"> 2073</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l02074"></a><span class="lineno"> 2074</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l02075"></a><span class="lineno"> 2075</span>&#160;</div><div class="line"><a name="l02076"></a><span class="lineno"> 2076</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::StackDescriptor&gt;</a> verifier(</div><div class="line"><a name="l02077"></a><span class="lineno"> 2077</span>&#160;            layerName, {inputTensorInfo, inputTensorInfo}, {outputTensorInfo}, descriptor);</div><div class="line"><a name="l02078"></a><span class="lineno"> 2078</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l02079"></a><span class="lineno"> 2079</span>&#160;}</div><div class="line"><a name="l02080"></a><span class="lineno"> 2080</span>&#160;</div><div class="line"><a name="l02081"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a865de239f4cf854e65f8b61ebbbb7fbd"> 2081</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeStandIn)</div><div class="line"><a name="l02082"></a><span class="lineno"> 2082</span>&#160;{</div><div class="line"><a name="l02083"></a><span class="lineno"> 2083</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;standIn&quot;</span>);</div><div class="line"><a name="l02084"></a><span class="lineno"> 2084</span>&#160;</div><div class="line"><a name="l02085"></a><span class="lineno"> 2085</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo({ 1u }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02086"></a><span class="lineno"> 2086</span>&#160;    <a class="code" href="structarmnn_1_1_stand_in_descriptor.xhtml">armnn::StandInDescriptor</a> descriptor(2u, 2u);</div><div class="line"><a name="l02087"></a><span class="lineno"> 2087</span>&#160;</div><div class="line"><a name="l02088"></a><span class="lineno"> 2088</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l02089"></a><span class="lineno"> 2089</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer0  = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l02090"></a><span class="lineno"> 2090</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1  = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l02091"></a><span class="lineno"> 2091</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> standInLayer = network-&gt;AddStandInLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02092"></a><span class="lineno"> 2092</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer0 = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l02093"></a><span class="lineno"> 2093</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer1 = network-&gt;AddOutputLayer(1);</div><div class="line"><a name="l02094"></a><span class="lineno"> 2094</span>&#160;</div><div class="line"><a name="l02095"></a><span class="lineno"> 2095</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(standInLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02096"></a><span class="lineno"> 2096</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(tensorInfo);</div><div class="line"><a name="l02097"></a><span class="lineno"> 2097</span>&#160;</div><div class="line"><a name="l02098"></a><span class="lineno"> 2098</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(standInLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l02099"></a><span class="lineno"> 2099</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(tensorInfo);</div><div class="line"><a name="l02100"></a><span class="lineno"> 2100</span>&#160;</div><div class="line"><a name="l02101"></a><span class="lineno"> 2101</span>&#160;    standInLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02102"></a><span class="lineno"> 2102</span>&#160;    standInLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(tensorInfo);</div><div class="line"><a name="l02103"></a><span class="lineno"> 2103</span>&#160;</div><div class="line"><a name="l02104"></a><span class="lineno"> 2104</span>&#160;    standInLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02105"></a><span class="lineno"> 2105</span>&#160;    standInLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(tensorInfo);</div><div class="line"><a name="l02106"></a><span class="lineno"> 2106</span>&#160;</div><div class="line"><a name="l02107"></a><span class="lineno"> 2107</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l02108"></a><span class="lineno"> 2108</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l02109"></a><span class="lineno"> 2109</span>&#160;</div><div class="line"><a name="l02110"></a><span class="lineno"> 2110</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::StandInDescriptor&gt;</a> verifier(</div><div class="line"><a name="l02111"></a><span class="lineno"> 2111</span>&#160;            layerName, { tensorInfo, tensorInfo }, { tensorInfo, tensorInfo }, descriptor);</div><div class="line"><a name="l02112"></a><span class="lineno"> 2112</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l02113"></a><span class="lineno"> 2113</span>&#160;}</div><div class="line"><a name="l02114"></a><span class="lineno"> 2114</span>&#160;</div><div class="line"><a name="l02115"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a2db8caccb8225bbef2368872aa9355d1"> 2115</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeStridedSlice)</div><div class="line"><a name="l02116"></a><span class="lineno"> 2116</span>&#160;{</div><div class="line"><a name="l02117"></a><span class="lineno"> 2117</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;stridedSlice&quot;</span>);</div><div class="line"><a name="l02118"></a><span class="lineno"> 2118</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({3, 2, 3, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02119"></a><span class="lineno"> 2119</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({3, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02120"></a><span class="lineno"> 2120</span>&#160;</div><div class="line"><a name="l02121"></a><span class="lineno"> 2121</span>&#160;    <a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml">armnn::StridedSliceDescriptor</a> desc({0, 0, 1, 0}, {1, 1, 1, 1}, {1, 1, 1, 1});</div><div class="line"><a name="l02122"></a><span class="lineno"> 2122</span>&#160;    desc.<a class="code" href="structarmnn_1_1_strided_slice_descriptor.xhtml#ac37e49c0d6e6e54f9d2015d0f11f8ee7">m_EndMask</a> = (1 &lt;&lt; 4) - 1;</div><div class="line"><a name="l02123"></a><span class="lineno"> 2123</span>&#160;    desc.m_ShrinkAxisMask = (1 &lt;&lt; 1) | (1 &lt;&lt; 2);</div><div class="line"><a name="l02124"></a><span class="lineno"> 2124</span>&#160;    desc.m_DataLayout = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a>;</div><div class="line"><a name="l02125"></a><span class="lineno"> 2125</span>&#160;</div><div class="line"><a name="l02126"></a><span class="lineno"> 2126</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l02127"></a><span class="lineno"> 2127</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l02128"></a><span class="lineno"> 2128</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> stridedSliceLayer = network-&gt;AddStridedSliceLayer(desc, layerName.c_str());</div><div class="line"><a name="l02129"></a><span class="lineno"> 2129</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l02130"></a><span class="lineno"> 2130</span>&#160;</div><div class="line"><a name="l02131"></a><span class="lineno"> 2131</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(stridedSliceLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02132"></a><span class="lineno"> 2132</span>&#160;    stridedSliceLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02133"></a><span class="lineno"> 2133</span>&#160;</div><div class="line"><a name="l02134"></a><span class="lineno"> 2134</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l02135"></a><span class="lineno"> 2135</span>&#160;    stridedSliceLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l02136"></a><span class="lineno"> 2136</span>&#160;</div><div class="line"><a name="l02137"></a><span class="lineno"> 2137</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l02138"></a><span class="lineno"> 2138</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l02139"></a><span class="lineno"> 2139</span>&#160;</div><div class="line"><a name="l02140"></a><span class="lineno"> 2140</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::StridedSliceDescriptor&gt;</a> verifier(</div><div class="line"><a name="l02141"></a><span class="lineno"> 2141</span>&#160;            layerName, {inputInfo}, {outputInfo}, desc);</div><div class="line"><a name="l02142"></a><span class="lineno"> 2142</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l02143"></a><span class="lineno"> 2143</span>&#160;}</div><div class="line"><a name="l02144"></a><span class="lineno"> 2144</span>&#160;</div><div class="line"><a name="l02145"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a1ceee00de3ecf9d68bdebed498cd049a"> 2145</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeSubtraction)</div><div class="line"><a name="l02146"></a><span class="lineno"> 2146</span>&#160;{</div><div class="line"><a name="l02147"></a><span class="lineno"> 2147</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;subtraction&quot;</span>);</div><div class="line"><a name="l02148"></a><span class="lineno"> 2148</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02149"></a><span class="lineno"> 2149</span>&#160;</div><div class="line"><a name="l02150"></a><span class="lineno"> 2150</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l02151"></a><span class="lineno"> 2151</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer0 = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l02152"></a><span class="lineno"> 2152</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer1 = network-&gt;AddInputLayer(1);</div><div class="line"><a name="l02153"></a><span class="lineno"> 2153</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> subtractionLayer = network-&gt;AddSubtractionLayer(layerName.c_str());</div><div class="line"><a name="l02154"></a><span class="lineno"> 2154</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l02155"></a><span class="lineno"> 2155</span>&#160;</div><div class="line"><a name="l02156"></a><span class="lineno"> 2156</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(subtractionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02157"></a><span class="lineno"> 2157</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(subtractionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l02158"></a><span class="lineno"> 2158</span>&#160;    subtractionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02159"></a><span class="lineno"> 2159</span>&#160;</div><div class="line"><a name="l02160"></a><span class="lineno"> 2160</span>&#160;    inputLayer0-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l02161"></a><span class="lineno"> 2161</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l02162"></a><span class="lineno"> 2162</span>&#160;    subtractionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l02163"></a><span class="lineno"> 2163</span>&#160;</div><div class="line"><a name="l02164"></a><span class="lineno"> 2164</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l02165"></a><span class="lineno"> 2165</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l02166"></a><span class="lineno"> 2166</span>&#160;</div><div class="line"><a name="l02167"></a><span class="lineno"> 2167</span>&#160;    <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a> verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {info});</div><div class="line"><a name="l02168"></a><span class="lineno"> 2168</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l02169"></a><span class="lineno"> 2169</span>&#160;}</div><div class="line"><a name="l02170"></a><span class="lineno"> 2170</span>&#160;</div><div class="line"><a name="l02171"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a2ae604a52ed7b47ffe458eaff5675476"> 2171</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeSwitch)</div><div class="line"><a name="l02172"></a><span class="lineno"> 2172</span>&#160;{</div><div class="line"><a name="l02173"></a><span class="lineno"> 2173</span>&#160;    <span class="keyword">class </span>SwitchLayerVerifier : <span class="keyword">public</span> <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a></div><div class="line"><a name="l02174"></a><span class="lineno"> 2174</span>&#160;    {</div><div class="line"><a name="l02175"></a><span class="lineno"> 2175</span>&#160;    <span class="keyword">public</span>:</div><div class="line"><a name="l02176"></a><span class="lineno"> 2176</span>&#160;        SwitchLayerVerifier(<span class="keyword">const</span> std::string&amp; layerName,</div><div class="line"><a name="l02177"></a><span class="lineno"> 2177</span>&#160;                            <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; inputInfos,</div><div class="line"><a name="l02178"></a><span class="lineno"> 2178</span>&#160;                            <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; outputInfos)</div><div class="line"><a name="l02179"></a><span class="lineno"> 2179</span>&#160;                : <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a>(layerName, inputInfos, outputInfos) {}</div><div class="line"><a name="l02180"></a><span class="lineno"> 2180</span>&#160;</div><div class="line"><a name="l02181"></a><span class="lineno"> 2181</span>&#160;        <span class="keywordtype">void</span> ExecuteStrategy(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer,</div><div class="line"><a name="l02182"></a><span class="lineno"> 2182</span>&#160;                             <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_base_descriptor.xhtml">armnn::BaseDescriptor</a>&amp; descriptor,</div><div class="line"><a name="l02183"></a><span class="lineno"> 2183</span>&#160;                             <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants,</div><div class="line"><a name="l02184"></a><span class="lineno"> 2184</span>&#160;                             <span class="keyword">const</span> <span class="keywordtype">char</span>* name,</div><div class="line"><a name="l02185"></a><span class="lineno"> 2185</span>&#160;                             <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> <span class="keywordtype">id</span> = 0)<span class="keyword"> override</span></div><div class="line"><a name="l02186"></a><span class="lineno"> 2186</span>&#160;<span class="keyword">        </span>{</div><div class="line"><a name="l02187"></a><span class="lineno"> 2187</span>&#160;            <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a>(descriptor, constants, <span class="keywordtype">id</span>);</div><div class="line"><a name="l02188"></a><span class="lineno"> 2188</span>&#160;            <span class="keywordflow">switch</span> (layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">GetType</a>())</div><div class="line"><a name="l02189"></a><span class="lineno"> 2189</span>&#160;            {</div><div class="line"><a name="l02190"></a><span class="lineno"> 2190</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l02191"></a><span class="lineno"> 2191</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l02192"></a><span class="lineno"> 2192</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l02193"></a><span class="lineno"> 2193</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4abbc155fb2b111bf61c4f5ff892915e6b">armnn::LayerType::Switch</a>:</div><div class="line"><a name="l02194"></a><span class="lineno"> 2194</span>&#160;                {</div><div class="line"><a name="l02195"></a><span class="lineno"> 2195</span>&#160;                    VerifyNameAndConnections(layer, name);</div><div class="line"><a name="l02196"></a><span class="lineno"> 2196</span>&#160;                    <span class="keywordflow">break</span>;</div><div class="line"><a name="l02197"></a><span class="lineno"> 2197</span>&#160;                }</div><div class="line"><a name="l02198"></a><span class="lineno"> 2198</span>&#160;                <span class="keywordflow">default</span>:</div><div class="line"><a name="l02199"></a><span class="lineno"> 2199</span>&#160;                {</div><div class="line"><a name="l02200"></a><span class="lineno"> 2200</span>&#160;                    <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>(<span class="stringliteral">&quot;Unexpected layer type in Switch test model&quot;</span>);</div><div class="line"><a name="l02201"></a><span class="lineno"> 2201</span>&#160;                }</div><div class="line"><a name="l02202"></a><span class="lineno"> 2202</span>&#160;            }</div><div class="line"><a name="l02203"></a><span class="lineno"> 2203</span>&#160;        }</div><div class="line"><a name="l02204"></a><span class="lineno"> 2204</span>&#160;    };</div><div class="line"><a name="l02205"></a><span class="lineno"> 2205</span>&#160;</div><div class="line"><a name="l02206"></a><span class="lineno"> 2206</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;switch&quot;</span>);</div><div class="line"><a name="l02207"></a><span class="lineno"> 2207</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02208"></a><span class="lineno"> 2208</span>&#160;</div><div class="line"><a name="l02209"></a><span class="lineno"> 2209</span>&#160;    std::vector&lt;float&gt; constantData = GenerateRandomData&lt;float&gt;(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.GetNumElements());</div><div class="line"><a name="l02210"></a><span class="lineno"> 2210</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> constTensor(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, constantData);</div><div class="line"><a name="l02211"></a><span class="lineno"> 2211</span>&#160;</div><div class="line"><a name="l02212"></a><span class="lineno"> 2212</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l02213"></a><span class="lineno"> 2213</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l02214"></a><span class="lineno"> 2214</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> constantLayer = network-&gt;AddConstantLayer(constTensor, <span class="stringliteral">&quot;constant&quot;</span>);</div><div class="line"><a name="l02215"></a><span class="lineno"> 2215</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> switchLayer = network-&gt;AddSwitchLayer(layerName.c_str());</div><div class="line"><a name="l02216"></a><span class="lineno"> 2216</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> trueOutputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l02217"></a><span class="lineno"> 2217</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> falseOutputLayer = network-&gt;AddOutputLayer(1);</div><div class="line"><a name="l02218"></a><span class="lineno"> 2218</span>&#160;</div><div class="line"><a name="l02219"></a><span class="lineno"> 2219</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(switchLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02220"></a><span class="lineno"> 2220</span>&#160;    constantLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(switchLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l02221"></a><span class="lineno"> 2221</span>&#160;    switchLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(trueOutputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02222"></a><span class="lineno"> 2222</span>&#160;    switchLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(falseOutputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02223"></a><span class="lineno"> 2223</span>&#160;</div><div class="line"><a name="l02224"></a><span class="lineno"> 2224</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l02225"></a><span class="lineno"> 2225</span>&#160;    constantLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l02226"></a><span class="lineno"> 2226</span>&#160;    switchLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l02227"></a><span class="lineno"> 2227</span>&#160;    switchLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(1).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l02228"></a><span class="lineno"> 2228</span>&#160;</div><div class="line"><a name="l02229"></a><span class="lineno"> 2229</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l02230"></a><span class="lineno"> 2230</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l02231"></a><span class="lineno"> 2231</span>&#160;</div><div class="line"><a name="l02232"></a><span class="lineno"> 2232</span>&#160;    SwitchLayerVerifier verifier(layerName, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, {info, info});</div><div class="line"><a name="l02233"></a><span class="lineno"> 2233</span>&#160;    deserializedNetwork-&gt;ExecuteStrategy(verifier);</div><div class="line"><a name="l02234"></a><span class="lineno"> 2234</span>&#160;}</div><div class="line"><a name="l02235"></a><span class="lineno"> 2235</span>&#160;</div><div class="line"><a name="l02236"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#a11f5fe3da18636059c4d8c21e11ac3f5"> 2236</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeTranspose)</div><div class="line"><a name="l02237"></a><span class="lineno"> 2237</span>&#160;{</div><div class="line"><a name="l02238"></a><span class="lineno"> 2238</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;transpose&quot;</span>);</div><div class="line"><a name="l02239"></a><span class="lineno"> 2239</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({4, 3, 2, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02240"></a><span class="lineno"> 2240</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({1, 2, 3, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02241"></a><span class="lineno"> 2241</span>&#160;</div><div class="line"><a name="l02242"></a><span class="lineno"> 2242</span>&#160;    <a class="code" href="structarmnn_1_1_transpose_descriptor.xhtml">armnn::TransposeDescriptor</a> descriptor(<a class="code" href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a>({3, 2, 1, 0}));</div><div class="line"><a name="l02243"></a><span class="lineno"> 2243</span>&#160;</div><div class="line"><a name="l02244"></a><span class="lineno"> 2244</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l02245"></a><span class="lineno"> 2245</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l02246"></a><span class="lineno"> 2246</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> transposeLayer = network-&gt;AddTransposeLayer(descriptor, layerName.c_str());</div><div class="line"><a name="l02247"></a><span class="lineno"> 2247</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l02248"></a><span class="lineno"> 2248</span>&#160;</div><div class="line"><a name="l02249"></a><span class="lineno"> 2249</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(transposeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02250"></a><span class="lineno"> 2250</span>&#160;    transposeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02251"></a><span class="lineno"> 2251</span>&#160;</div><div class="line"><a name="l02252"></a><span class="lineno"> 2252</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputTensorInfo);</div><div class="line"><a name="l02253"></a><span class="lineno"> 2253</span>&#160;    transposeLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputTensorInfo);</div><div class="line"><a name="l02254"></a><span class="lineno"> 2254</span>&#160;</div><div class="line"><a name="l02255"></a><span class="lineno"> 2255</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l02256"></a><span class="lineno"> 2256</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l02257"></a><span class="lineno"> 2257</span>&#160;</div><div class="line"><a name="l02258"></a><span class="lineno"> 2258</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor&lt;armnn::TransposeDescriptor&gt;</a> verifier(</div><div class="line"><a name="l02259"></a><span class="lineno"> 2259</span>&#160;            layerName, {inputTensorInfo}, {outputTensorInfo}, descriptor);</div><div class="line"><a name="l02260"></a><span class="lineno"> 2260</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l02261"></a><span class="lineno"> 2261</span>&#160;}</div><div class="line"><a name="l02262"></a><span class="lineno"> 2262</span>&#160;</div><div class="line"><a name="l02263"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#acb977ca4fb62419f89117fa33c5a4d4a"> 2263</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeTransposeConvolution2d)</div><div class="line"><a name="l02264"></a><span class="lineno"> 2264</span>&#160;{</div><div class="line"><a name="l02265"></a><span class="lineno"> 2265</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;transposeConvolution2d&quot;</span>);</div><div class="line"><a name="l02266"></a><span class="lineno"> 2266</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo ({ 1, 7, 7, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02267"></a><span class="lineno"> 2267</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({ 1, 9, 9, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02268"></a><span class="lineno"> 2268</span>&#160;</div><div class="line"><a name="l02269"></a><span class="lineno"> 2269</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> weightsInfo({ 1, 3, 3, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02270"></a><span class="lineno"> 2270</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> biasesInfo ({ 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02271"></a><span class="lineno"> 2271</span>&#160;</div><div class="line"><a name="l02272"></a><span class="lineno"> 2272</span>&#160;    std::vector&lt;float&gt; weightsData = GenerateRandomData&lt;float&gt;(weightsInfo.GetNumElements());</div><div class="line"><a name="l02273"></a><span class="lineno"> 2273</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights(weightsInfo, weightsData);</div><div class="line"><a name="l02274"></a><span class="lineno"> 2274</span>&#160;</div><div class="line"><a name="l02275"></a><span class="lineno"> 2275</span>&#160;    std::vector&lt;float&gt; biasesData = GenerateRandomData&lt;float&gt;(biasesInfo.GetNumElements());</div><div class="line"><a name="l02276"></a><span class="lineno"> 2276</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> biases(biasesInfo, biasesData);</div><div class="line"><a name="l02277"></a><span class="lineno"> 2277</span>&#160;</div><div class="line"><a name="l02278"></a><span class="lineno"> 2278</span>&#160;    <a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">armnn::TransposeConvolution2dDescriptor</a> descriptor;</div><div class="line"><a name="l02279"></a><span class="lineno"> 2279</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">m_PadLeft</a>     = 1;</div><div class="line"><a name="l02280"></a><span class="lineno"> 2280</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">m_PadRight</a>    = 1;</div><div class="line"><a name="l02281"></a><span class="lineno"> 2281</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">m_PadTop</a>      = 1;</div><div class="line"><a name="l02282"></a><span class="lineno"> 2282</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">m_PadBottom</a>   = 1;</div><div class="line"><a name="l02283"></a><span class="lineno"> 2283</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">m_StrideX</a>     = 1;</div><div class="line"><a name="l02284"></a><span class="lineno"> 2284</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">m_StrideY</a>     = 1;</div><div class="line"><a name="l02285"></a><span class="lineno"> 2285</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">m_BiasEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l02286"></a><span class="lineno"> 2286</span>&#160;    descriptor.<a class="code" href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">m_DataLayout</a>  = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a>;</div><div class="line"><a name="l02287"></a><span class="lineno"> 2287</span>&#160;</div><div class="line"><a name="l02288"></a><span class="lineno"> 2288</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network = <a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>();</div><div class="line"><a name="l02289"></a><span class="lineno"> 2289</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> inputLayer  = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l02290"></a><span class="lineno"> 2290</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> convLayer   =</div><div class="line"><a name="l02291"></a><span class="lineno"> 2291</span>&#160;            network-&gt;AddTransposeConvolution2dLayer(descriptor,</div><div class="line"><a name="l02292"></a><span class="lineno"> 2292</span>&#160;                                                    weights,</div><div class="line"><a name="l02293"></a><span class="lineno"> 2293</span>&#160;                                                    <a class="code" href="classarmnn_1_1_optional.xhtml">armnn::Optional&lt;armnn::ConstTensor&gt;</a>(biases),</div><div class="line"><a name="l02294"></a><span class="lineno"> 2294</span>&#160;                                                    layerName.c_str());</div><div class="line"><a name="l02295"></a><span class="lineno"> 2295</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* <span class="keyword">const</span> outputLayer = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l02296"></a><span class="lineno"> 2296</span>&#160;</div><div class="line"><a name="l02297"></a><span class="lineno"> 2297</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(convLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02298"></a><span class="lineno"> 2298</span>&#160;    convLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02299"></a><span class="lineno"> 2299</span>&#160;</div><div class="line"><a name="l02300"></a><span class="lineno"> 2300</span>&#160;    inputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(inputInfo);</div><div class="line"><a name="l02301"></a><span class="lineno"> 2301</span>&#160;    convLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(outputInfo);</div><div class="line"><a name="l02302"></a><span class="lineno"> 2302</span>&#160;</div><div class="line"><a name="l02303"></a><span class="lineno"> 2303</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l02304"></a><span class="lineno"> 2304</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l02305"></a><span class="lineno"> 2305</span>&#160;</div><div class="line"><a name="l02306"></a><span class="lineno"> 2306</span>&#160;    <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt; constants {weights, biases};</div><div class="line"><a name="l02307"></a><span class="lineno"> 2307</span>&#160;    <a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml">LayerVerifierBaseWithDescriptorAndConstants&lt;armnn::TransposeConvolution2dDescriptor&gt;</a> verifier(</div><div class="line"><a name="l02308"></a><span class="lineno"> 2308</span>&#160;            layerName, {inputInfo}, {outputInfo}, descriptor, constants);</div><div class="line"><a name="l02309"></a><span class="lineno"> 2309</span>&#160;    deserializedNetwork-&gt;<a class="code" href="class_layer_verifier_base_with_descriptor_and_constants.xhtml#a49f7f1098adb86fd2197d9aee3924de2">ExecuteStrategy</a>(verifier);</div><div class="line"><a name="l02310"></a><span class="lineno"> 2310</span>&#160;}</div><div class="line"><a name="l02311"></a><span class="lineno"> 2311</span>&#160;</div><div class="line"><a name="l02312"></a><span class="lineno"><a class="line" href="_serializer_tests_8cpp.xhtml#aca4adebc92f5a0afc5969f5be06ec2b4"> 2312</a></span>&#160;<a class="code" href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a>(SerializeDeserializeNonLinearNetwork)</div><div class="line"><a name="l02313"></a><span class="lineno"> 2313</span>&#160;{</div><div class="line"><a name="l02314"></a><span class="lineno"> 2314</span>&#160;    <span class="keyword">class </span>ConstantLayerVerifier : <span class="keyword">public</span> <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a></div><div class="line"><a name="l02315"></a><span class="lineno"> 2315</span>&#160;    {</div><div class="line"><a name="l02316"></a><span class="lineno"> 2316</span>&#160;    <span class="keyword">public</span>:</div><div class="line"><a name="l02317"></a><span class="lineno"> 2317</span>&#160;        ConstantLayerVerifier(<span class="keyword">const</span> std::string&amp; layerName,</div><div class="line"><a name="l02318"></a><span class="lineno"> 2318</span>&#160;                              <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; inputInfos,</div><div class="line"><a name="l02319"></a><span class="lineno"> 2319</span>&#160;                              <span class="keyword">const</span> std::vector&lt;armnn::TensorInfo&gt;&amp; outputInfos,</div><div class="line"><a name="l02320"></a><span class="lineno"> 2320</span>&#160;                              <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a>&amp; layerInput)</div><div class="line"><a name="l02321"></a><span class="lineno"> 2321</span>&#160;            : <a class="code" href="class_layer_verifier_base.xhtml">LayerVerifierBase</a>(layerName, inputInfos, outputInfos)</div><div class="line"><a name="l02322"></a><span class="lineno"> 2322</span>&#160;            , m_LayerInput(layerInput) {}</div><div class="line"><a name="l02323"></a><span class="lineno"> 2323</span>&#160;</div><div class="line"><a name="l02324"></a><span class="lineno"> 2324</span>&#160;        <span class="keywordtype">void</span> ExecuteStrategy(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* layer,</div><div class="line"><a name="l02325"></a><span class="lineno"> 2325</span>&#160;                             <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_base_descriptor.xhtml">armnn::BaseDescriptor</a>&amp; descriptor,</div><div class="line"><a name="l02326"></a><span class="lineno"> 2326</span>&#160;                             <span class="keyword">const</span> std::vector&lt;armnn::ConstTensor&gt;&amp; constants,</div><div class="line"><a name="l02327"></a><span class="lineno"> 2327</span>&#160;                             <span class="keyword">const</span> <span class="keywordtype">char</span>* name,</div><div class="line"><a name="l02328"></a><span class="lineno"> 2328</span>&#160;                             <span class="keyword">const</span> <a class="code" href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a> <span class="keywordtype">id</span> = 0)<span class="keyword"> override</span></div><div class="line"><a name="l02329"></a><span class="lineno"> 2329</span>&#160;<span class="keyword">        </span>{</div><div class="line"><a name="l02330"></a><span class="lineno"> 2330</span>&#160;            <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a>(descriptor, constants, <span class="keywordtype">id</span>);</div><div class="line"><a name="l02331"></a><span class="lineno"> 2331</span>&#160;            <span class="keywordflow">switch</span> (layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">GetType</a>())</div><div class="line"><a name="l02332"></a><span class="lineno"> 2332</span>&#160;            {</div><div class="line"><a name="l02333"></a><span class="lineno"> 2333</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l02334"></a><span class="lineno"> 2334</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l02335"></a><span class="lineno"> 2335</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">armnn::LayerType::Addition</a>: <span class="keywordflow">break</span>;</div><div class="line"><a name="l02336"></a><span class="lineno"> 2336</span>&#160;                <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</a>:</div><div class="line"><a name="l02337"></a><span class="lineno"> 2337</span>&#160;                {</div><div class="line"><a name="l02338"></a><span class="lineno"> 2338</span>&#160;                    VerifyNameAndConnections(layer, name);</div><div class="line"><a name="l02339"></a><span class="lineno"> 2339</span>&#160;                    <a class="code" href="_serializer_test_utils_8cpp.xhtml#a104f74b01c30ad4a17d765309a9731bd">CompareConstTensor</a>(constants.at(0), m_LayerInput);</div><div class="line"><a name="l02340"></a><span class="lineno"> 2340</span>&#160;                    <span class="keywordflow">break</span>;</div><div class="line"><a name="l02341"></a><span class="lineno"> 2341</span>&#160;                }</div><div class="line"><a name="l02342"></a><span class="lineno"> 2342</span>&#160;                <span class="keywordflow">default</span>:</div><div class="line"><a name="l02343"></a><span class="lineno"> 2343</span>&#160;                {</div><div class="line"><a name="l02344"></a><span class="lineno"> 2344</span>&#160;                    <span class="keywordflow">throw</span> <a class="code" href="classarmnn_1_1_exception.xhtml">armnn::Exception</a>(<span class="stringliteral">&quot;Unexpected layer type in test model&quot;</span>);</div><div class="line"><a name="l02345"></a><span class="lineno"> 2345</span>&#160;                }</div><div class="line"><a name="l02346"></a><span class="lineno"> 2346</span>&#160;            }</div><div class="line"><a name="l02347"></a><span class="lineno"> 2347</span>&#160;        }</div><div class="line"><a name="l02348"></a><span class="lineno"> 2348</span>&#160;</div><div class="line"><a name="l02349"></a><span class="lineno"> 2349</span>&#160;    <span class="keyword">private</span>:</div><div class="line"><a name="l02350"></a><span class="lineno"> 2350</span>&#160;        <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> m_LayerInput;</div><div class="line"><a name="l02351"></a><span class="lineno"> 2351</span>&#160;    };</div><div class="line"><a name="l02352"></a><span class="lineno"> 2352</span>&#160;</div><div class="line"><a name="l02353"></a><span class="lineno"> 2353</span>&#160;    <span class="keyword">const</span> std::string layerName(<span class="stringliteral">&quot;constant&quot;</span>);</div><div class="line"><a name="l02354"></a><span class="lineno"> 2354</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 2, 3 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l02355"></a><span class="lineno"> 2355</span>&#160;</div><div class="line"><a name="l02356"></a><span class="lineno"> 2356</span>&#160;    std::vector&lt;float&gt; constantData = GenerateRandomData&lt;float&gt;(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>.GetNumElements());</div><div class="line"><a name="l02357"></a><span class="lineno"> 2357</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> constTensor(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>, constantData);</div><div class="line"><a name="l02358"></a><span class="lineno"> 2358</span>&#160;</div><div class="line"><a name="l02359"></a><span class="lineno"> 2359</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> network(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a>());</div><div class="line"><a name="l02360"></a><span class="lineno"> 2360</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* input = network-&gt;AddInputLayer(0);</div><div class="line"><a name="l02361"></a><span class="lineno"> 2361</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* add = network-&gt;AddAdditionLayer();</div><div class="line"><a name="l02362"></a><span class="lineno"> 2362</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* constant = network-&gt;AddConstantLayer(constTensor, layerName.c_str());</div><div class="line"><a name="l02363"></a><span class="lineno"> 2363</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a>* output = network-&gt;AddOutputLayer(0);</div><div class="line"><a name="l02364"></a><span class="lineno"> 2364</span>&#160;</div><div class="line"><a name="l02365"></a><span class="lineno"> 2365</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02366"></a><span class="lineno"> 2366</span>&#160;    constant-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l02367"></a><span class="lineno"> 2367</span>&#160;    add-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l02368"></a><span class="lineno"> 2368</span>&#160;</div><div class="line"><a name="l02369"></a><span class="lineno"> 2369</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l02370"></a><span class="lineno"> 2370</span>&#160;    constant-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l02371"></a><span class="lineno"> 2371</span>&#160;    add-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l02372"></a><span class="lineno"> 2372</span>&#160;</div><div class="line"><a name="l02373"></a><span class="lineno"> 2373</span>&#160;    <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> deserializedNetwork = <a class="code" href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a>(<a class="code" href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a>(*network));</div><div class="line"><a name="l02374"></a><span class="lineno"> 2374</span>&#160;    BOOST_CHECK(deserializedNetwork);</div><div class="line"><a name="l02375"></a><span class="lineno"> 2375</span>&#160;</div><div class="line"><a name="l02376"></a><span class="lineno"> 2376</span>&#160;    ConstantLayerVerifier verifier(layerName, {}, {<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>}, constTensor);</div><div class="line"><a name="l02377"></a><span class="lineno"> 2377</span>&#160;    deserializedNetwork-&gt;ExecuteStrategy(verifier);</div><div class="line"><a name="l02378"></a><span class="lineno"> 2378</span>&#160;}</div><div class="line"><a name="l02379"></a><span class="lineno"> 2379</span>&#160;</div><div class="line"><a name="l02380"></a><span class="lineno"> 2380</span>&#160;<a class="code" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</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="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="_ignore_unused_8hpp_xhtml"><div class="ttname"><a href="_ignore_unused_8hpp.xhtml">IgnoreUnused.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::Convolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00456">Descriptors.hpp:456</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4ae20f0f2826a6549809f050b86274567f"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4ae20f0f2826a6549809f050b86274567f">armnn::LayerType::Concat</a></div></div>
<div class="ttc" id="structarmnn_1_1_views_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_views_descriptor.xhtml">armnn::ViewsDescriptor</a></div><div class="ttdoc">A ViewsDescriptor for the SplitterLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00206">Descriptors.hpp:206</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00062">INetwork.hpp:62</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ab509802c659de19929f18bad14a35c58"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ab509802c659de19929f18bad14a35c58">armnn::DetectionPostProcessDescriptor::m_ScaleW</a></div><div class="ttdeci">float m_ScaleW</div><div class="ttdoc">Center size encoding scale weight. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00561">Descriptors.hpp:561</a></div></div>
<div class="ttc" id="class_layer_verifier_base_with_descriptor_xhtml"><div class="ttname"><a href="class_layer_verifier_base_with_descriptor.xhtml">LayerVerifierBaseWithDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8hpp_source.xhtml#l00051">SerializerTestUtils.hpp:51</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a27226c864bac7454a8504f8edb15d95b">armnn::DataType::Boolean</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_transpose_convolution2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml">armnn::TransposeConvolution2dDescriptor</a></div><div class="ttdoc">A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01213">Descriptors.hpp:1213</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape &amp; GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00187">Tensor.hpp:187</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_optional_xhtml"><div class="ttname"><a href="classarmnn_1_1_optional.xhtml">armnn::Optional&lt; armnn::ConstTensor &gt;</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3"><div class="ttname"><a href="namespacearmnn.xhtml#adf2e5515c4c36a3e7e46bb8b83c6754eaf3f6d0343d56ce88ce7958170ed05cb3">armnn::OutputShapeRounding::Floor</a></div></div>
<div class="ttc" id="structarmnn_1_1_reshape_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_reshape_descriptor.xhtml">armnn::ReshapeDescriptor</a></div><div class="ttdoc">A ReshapeDescriptor for the ReshapeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00832">Descriptors.hpp:832</a></div></div>
<div class="ttc" id="_serializer_test_utils_8cpp_xhtml_a59d03e40f8f051241e46091cca50d31f"><div class="ttname"><a href="_serializer_test_utils_8cpp.xhtml#a59d03e40f8f051241e46091cca50d31f">DeserializeNetwork</a></div><div class="ttdeci">armnn::INetworkPtr DeserializeNetwork(const std::string &amp;serializerString)</div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8cpp_source.xhtml#l00146">SerializerTestUtils.cpp:146</a></div></div>
<div class="ttc" id="_deprecated_8hpp_xhtml_ab66a241a0ed3ee89c866e777b035d0ed"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_BEGIN</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00033">Deprecated.hpp:33</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::DepthwiseConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00508">Descriptors.hpp:508</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="structarmnn_1_1_comparison_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_comparison_descriptor.xhtml">armnn::ComparisonDescriptor</a></div><div class="ttdoc">A ComparisonDescriptor for the ComparisonLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00078">Descriptors.hpp:78</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae64523937ea910030ad66fee6fddd51f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae64523937ea910030ad66fee6fddd51f">armnn::DetectionPostProcessDescriptor::m_ScaleX</a></div><div class="ttdeci">float m_ScaleX</div><div class="ttdoc">Center size encoding scale x. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00557">Descriptors.hpp:557</a></div></div>
<div class="ttc" id="structarmnn_1_1_resize_bilinear_descriptor_xhtml_adcf5037208faac36c0788239a073f75c"><div class="ttname"><a href="structarmnn_1_1_resize_bilinear_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">armnn::ResizeBilinearDescriptor::m_TargetWidth</a></div><div class="ttdeci">uint32_t m_TargetWidth</div><div class="ttdoc">Target width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00782">Descriptors.hpp:782</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="namespacearmnn_xhtml_a2da4db0140d1a6dc69c9c82e9ef5379ea103aa83df42877d5f9baeafdbf620b55"><div class="ttname"><a href="namespacearmnn.xhtml#a2da4db0140d1a6dc69c9c82e9ef5379ea103aa83df42877d5f9baeafdbf620b55">armnn::LogicalBinaryOperation::LogicalAnd</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="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">armnn::DataType::Signed32</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_transpose_convolution2d_descriptor_xhtml_aea202e14d8874cefd9a0f778022b7e25"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aea202e14d8874cefd9a0f778022b7e25">armnn::TransposeConvolution2dDescriptor::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#l01254">Descriptors.hpp:1254</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a></div></div>
<div class="ttc" id="_quantized_lstm_params_8hpp_xhtml"><div class="ttname"><a href="_quantized_lstm_params_8hpp.xhtml">QuantizedLstmParams.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a869254cb56968986a78a79e1d6d4a86b"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#a869254cb56968986a78a79e1d6d4a86b">armnn::ResizeDescriptor::m_Method</a></div><div class="ttdeci">ResizeMethod m_Method</div><div class="ttdoc">The Interpolation method to use (Bilinear, NearestNeighbor). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00821">Descriptors.hpp:821</a></div></div>
<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml_a5e078fd505aef7bccaa05c8058e096cc"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml#a5e078fd505aef7bccaa05c8058e096cc">armnn::InstanceNormalizationDescriptor::m_Gamma</a></div><div class="ttdeci">float m_Gamma</div><div class="ttdoc">Gamma, the scale scalar value applied for the normalized tensor. Defaults to 1.0. ...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00663">Descriptors.hpp:663</a></div></div>
<div class="ttc" id="structarmnn_1_1_softmax_descriptor_xhtml_a8275d51ef9a584feb95726ea0522f6e5"><div class="ttname"><a href="structarmnn_1_1_softmax_descriptor.xhtml#a8275d51ef9a584feb95726ea0522f6e5">armnn::SoftmaxDescriptor::m_Beta</a></div><div class="ttdeci">float m_Beta</div><div class="ttdoc">Exponentiation value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00152">Descriptors.hpp:152</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6"><div class="ttname"><a href="namespacearmnn.xhtml#a3888429b6ebc79f9a7df549e5e4d9a2fa843f2812f595e7ec7c5036e89fde02d6">armnn::PaddingMethod::Exclude</a></div><div class="ttdoc">The padding fields don&amp;#39;t count and are ignored. </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="structarmnn_1_1_arg_min_max_descriptor_xhtml_ab1ae6f520bb1a4da191a0ae907477f23"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml#ab1ae6f520bb1a4da191a0ae907477f23">armnn::ArgMinMaxDescriptor::m_Function</a></div><div class="ttdeci">ArgMinMaxFunction m_Function</div><div class="ttdoc">Specify if the function is to find Min or Max. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00070">Descriptors.hpp:70</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7e2f87544b8bc7e497e1dec8d3ca4055"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7e2f87544b8bc7e497e1dec8d3ca4055">armnn::DetectionPostProcessDescriptor::m_DetectionsPerClass</a></div><div class="ttdeci">uint32_t m_DetectionsPerClass</div><div class="ttdoc">Detections per classes, used in Regular NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00547">Descriptors.hpp:547</a></div></div>
<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_a358cb7cd3c0647b25be049fd734b8c22"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#a358cb7cd3c0647b25be049fd734b8c22">anchorsInfo</a></div><div class="ttdeci">armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32)</div></div>
<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::BatchToSpaceNdDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00700">Descriptors.hpp:700</a></div></div>
<div class="ttc" id="structarmnn_1_1_logical_binary_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_logical_binary_descriptor.xhtml">armnn::LogicalBinaryDescriptor</a></div><div class="ttdoc">A LogicalBinaryDescriptor for the LogicalBinaryLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01284">Descriptors.hpp:1284</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="class_layer_verifier_base_with_descriptor_xhtml_a49f7f1098adb86fd2197d9aee3924de2"><div class="ttname"><a href="class_layer_verifier_base_with_descriptor.xhtml#a49f7f1098adb86fd2197d9aee3924de2">LayerVerifierBaseWithDescriptor::ExecuteStrategy</a></div><div class="ttdeci">void ExecuteStrategy(const armnn::IConnectableLayer *layer, const armnn::BaseDescriptor &amp;descriptor, const std::vector&lt; armnn::ConstTensor &gt; &amp;constants, const char *name, const armnn::LayerBindingId id=0) override</div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8hpp_source.xhtml#l00061">SerializerTestUtils.hpp:61</a></div></div>
<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::NormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00603">Descriptors.hpp:603</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="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &amp;&amp;...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div>
<div class="ttc" id="_lstm_params_8hpp_xhtml"><div class="ttname"><a href="_lstm_params_8hpp.xhtml">LstmParams.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_aa9e49717ebdb741e8c767741647fc618"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#aa9e49717ebdb741e8c767741647fc618">armnn::TransposeConvolution2dDescriptor::m_PadBottom</a></div><div class="ttdeci">uint32_t m_PadBottom</div><div class="ttdoc">Padding bottom value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01248">Descriptors.hpp:1248</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::Convolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation along y axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00452">Descriptors.hpp:452</a></div></div>
<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml_ac37e49c0d6e6e54f9d2015d0f11f8ee7"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml#ac37e49c0d6e6e54f9d2015d0f11f8ee7">armnn::StridedSliceDescriptor::m_EndMask</a></div><div class="ttdeci">int32_t m_EndMask</div><div class="ttdoc">End mask value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01126">Descriptors.hpp:1126</a></div></div>
<div class="ttc" id="structarmnn_1_1_space_to_depth_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml">armnn::SpaceToDepthDescriptor</a></div><div class="ttdoc">A SpaceToDepthDescriptor for the SpaceToDepthLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00884">Descriptors.hpp:884</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a68be4837f6c739877233e527a996dd00"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a68be4837f6c739877233e527a996dd00">armnn::LayerType::Merge</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a302b688d88dd73cde0fb1faef6679907"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a302b688d88dd73cde0fb1faef6679907">armnn::DepthwiseConvolution2dDescriptor::m_DilationY</a></div><div class="ttdeci">uint32_t m_DilationY</div><div class="ttdoc">Dilation factor value for height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00504">Descriptors.hpp:504</a></div></div>
<div class="ttc" id="structarmnn_1_1_batch_to_space_nd_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_to_space_nd_descriptor.xhtml">armnn::BatchToSpaceNdDescriptor</a></div><div class="ttdoc">A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00673">Descriptors.hpp:673</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ab8cf8f9fb6792e654c2d8d8382f6f01b"><div class="ttname"><a href="namespacearmnn.xhtml#ab8cf8f9fb6792e654c2d8d8382f6f01b">armnn::LayerBindingId</a></div><div class="ttdeci">int LayerBindingId</div><div class="ttdoc">Type of identifiers for bindable layers (inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00210">Types.hpp:210</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a1cfaa710db2a54673b21d2ea2da757c8a2a25ebd8c909241e3f7818389b804ecc"><div class="ttname"><a href="namespacearmnn.xhtml#a1cfaa710db2a54673b21d2ea2da757c8a2a25ebd8c909241e3f7818389b804ecc">armnn::UnaryOperation::LogicalNot</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &amp;tensorInfo)=0</div></div>
<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml">armnn::ResizeDescriptor</a></div><div class="ttdoc">A ResizeDescriptor for the ResizeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00794">Descriptors.hpp:794</a></div></div>
<div class="ttc" id="structarmnn_1_1_l2_normalization_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::L2NormalizationDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00622">Descriptors.hpp:622</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a9ae2c9796692ebeafe19a4d3f09c8ea8"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a9ae2c9796692ebeafe19a4d3f09c8ea8">armnn::DetectionPostProcessDescriptor::m_MaxClassesPerDetection</a></div><div class="ttdeci">uint32_t m_MaxClassesPerDetection</div><div class="ttdoc">Maximum numbers of classes per detection, used in Fast NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00545">Descriptors.hpp:545</a></div></div>
<div class="ttc" id="structarmnn_1_1_base_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_base_descriptor.xhtml">armnn::BaseDescriptor</a></div><div class="ttdoc">Base class for all descriptors. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00022">Descriptors.hpp:22</a></div></div>
<div class="ttc" id="structarmnn_1_1_mean_descriptor_xhtml_a1f0d67b087c491248bd1cde3ff995a95"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml#a1f0d67b087c491248bd1cde3ff995a95">armnn::MeanDescriptor::m_Axis</a></div><div class="ttdeci">std::vector&lt; unsigned int &gt; m_Axis</div><div class="ttdoc">Values for the dimensions to reduce. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00969">Descriptors.hpp:969</a></div></div>
<div class="ttc" id="structarmnn_1_1_stack_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stack_descriptor.xhtml">armnn::StackDescriptor</a></div><div class="ttdoc">A StackDescriptor for the StackLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01024">Descriptors.hpp:1024</a></div></div>
<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::SpaceToBatchNdDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00880">Descriptors.hpp:880</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="structarmnn_1_1_detection_post_process_descriptor_xhtml_ae72089bcab60ac175557f4241b16a014"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#ae72089bcab60ac175557f4241b16a014">armnn::DetectionPostProcessDescriptor::m_MaxDetections</a></div><div class="ttdeci">uint32_t m_MaxDetections</div><div class="ttdoc">Maximum numbers of detections. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00543">Descriptors.hpp:543</a></div></div>
<div class="ttc" id="structarmnn_1_1_pad_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pad_descriptor.xhtml">armnn::PadDescriptor</a></div><div class="ttdoc">A PadDescriptor for the PadLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00975">Descriptors.hpp:975</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="_types_utils_8hpp_xhtml"><div class="ttname"><a href="_types_utils_8hpp.xhtml">TypesUtils.hpp</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="structarmnn_1_1_detection_post_process_descriptor_xhtml_a53c8a7f33a40e1e240256bcfcf41b101"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a53c8a7f33a40e1e240256bcfcf41b101">armnn::DetectionPostProcessDescriptor::m_NmsIouThreshold</a></div><div class="ttdeci">float m_NmsIouThreshold</div><div class="ttdoc">Intersection over union threshold. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00551">Descriptors.hpp:551</a></div></div>
<div class="ttc" id="_deprecated_8hpp_xhtml_ad762b11b48e5c1d1c1743f529485728a"><div class="ttname"><a href="_deprecated_8hpp.xhtml#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="ttdeci">#define ARMNN_NO_DEPRECATE_WARN_END</div><div class="ttdef"><b>Definition:</b> <a href="_deprecated_8hpp_source.xhtml#l00034">Deprecated.hpp:34</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::DepthwiseConvolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation factor value for width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00502">Descriptors.hpp:502</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::DepthwiseConvolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00494">Descriptors.hpp:494</a></div></div>
<div class="ttc" id="structarmnn_1_1_views_descriptor_xhtml_aae0893695f5803a3517985c7cb1ccb2e"><div class="ttname"><a href="structarmnn_1_1_views_descriptor.xhtml#aae0893695f5803a3517985c7cb1ccb2e">armnn::ViewsDescriptor::SetViewSize</a></div><div class="ttdeci">Status SetViewSize(uint32_t view, uint32_t coord, uint32_t value)</div><div class="ttdoc">Set the size of the views. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.xhtml#l00315">Descriptors.cpp:315</a></div></div>
<div class="ttc" id="class_layer_verifier_base_with_descriptor_and_constants_xhtml_a49f7f1098adb86fd2197d9aee3924de2"><div class="ttname"><a href="class_layer_verifier_base_with_descriptor_and_constants.xhtml#a49f7f1098adb86fd2197d9aee3924de2">LayerVerifierBaseWithDescriptorAndConstants::ExecuteStrategy</a></div><div class="ttdeci">void ExecuteStrategy(const armnn::IConnectableLayer *layer, const armnn::BaseDescriptor &amp;descriptor, const std::vector&lt; armnn::ConstTensor &gt; &amp;constants, const char *name, const armnn::LayerBindingId id=0) override</div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8hpp_source.xhtml#l00118">SerializerTestUtils.hpp:118</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233"><div class="ttname"><a href="namespacearmnn.xhtml#ae7e8cbf71db6a490789ca6dcaa8deeaea6a061313d22e51e0f25b7cd4dc065233">armnn::ArgMinMaxFunction::Max</a></div></div>
<div class="ttc" id="structarmnn_1_1_l2_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_descriptor.xhtml">armnn::L2NormalizationDescriptor</a></div><div class="ttdoc">A L2NormalizationDescriptor for the L2NormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00607">Descriptors.hpp:607</a></div></div>
<div class="ttc" id="class_layer_verifier_base_xhtml_a56e5da77beb8c601e09bf78371b95828"><div class="ttname"><a href="class_layer_verifier_base.xhtml#a56e5da77beb8c601e09bf78371b95828">LayerVerifierBase::VerifyNameAndConnections</a></div><div class="ttdeci">void VerifyNameAndConnections(const armnn::IConnectableLayer *layer, const char *name)</div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8cpp_source.xhtml#l00038">SerializerTestUtils.cpp:38</a></div></div>
<div class="ttc" id="structarmnn_1_1_arg_min_max_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_arg_min_max_descriptor.xhtml">armnn::ArgMinMaxDescriptor</a></div><div class="ttdoc">An ArgMinMaxDescriptor for ArgMinMaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00056">Descriptors.hpp:56</a></div></div>
<div class="ttc" id="structarmnn_1_1_origins_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_origins_descriptor.xhtml">armnn::OriginsDescriptor</a></div><div class="ttdoc">An OriginsDescriptor for the ConcatLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00163">Descriptors.hpp:163</a></div></div>
<div class="ttc" id="structarmnn_1_1_reduce_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_reduce_descriptor.xhtml">armnn::ReduceDescriptor</a></div><div class="ttdoc">A ReduceDescriptor for the REDUCE operators. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01304">Descriptors.hpp:1304</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="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_a56943a0946e5f15e5e58054b8e7a04a4a9d723d04c40bfd81835c0766a698cf63"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a9d723d04c40bfd81835c0766a698cf63">armnn::LayerType::Resize</a></div></div>
<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00314">Tensor.hpp:314</a></div></div>
<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_adcf5037208faac36c0788239a073f75c"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#adcf5037208faac36c0788239a073f75c">armnn::ResizeDescriptor::m_TargetWidth</a></div><div class="ttdeci">uint32_t m_TargetWidth</div><div class="ttdoc">Target width value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00816">Descriptors.hpp:816</a></div></div>
<div class="ttc" id="structarmnn_1_1_gather_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_gather_descriptor.xhtml">armnn::GatherDescriptor</a></div><div class="ttdoc">A GatherDescriptor for the GatherLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00742">Descriptors.hpp:742</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a3a04b0ccee4bb2f21721ee5045e83df4"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a3a04b0ccee4bb2f21721ee5045e83df4">armnn::DetectionPostProcessDescriptor::m_NumClasses</a></div><div class="ttdeci">uint32_t m_NumClasses</div><div class="ttdoc">Number of classes. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00553">Descriptors.hpp:553</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021"><div class="ttname"><a href="namespacearmnn.xhtml#a961bbfe1db71a848eff5a1f0ab775718ab1897515d548a960afe49ecf66a29021">armnn::PoolingAlgorithm::Average</a></div></div>
<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a4022d5107338aaf5eb7abebf78a1360b"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#a4022d5107338aaf5eb7abebf78a1360b">armnn::ResizeDescriptor::m_HalfPixelCenters</a></div><div class="ttdeci">bool m_HalfPixelCenters</div><div class="ttdoc">Half Pixel Centers. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00827">Descriptors.hpp:827</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a2d299363c9fc33334c571fa29ca4f58ca19bb0af2c3c530538cb41aff7f235b96"><div class="ttname"><a href="namespacearmnn.xhtml#a2d299363c9fc33334c571fa29ca4f58ca19bb0af2c3c530538cb41aff7f235b96">armnn::ComparisonOperation::NotEqual</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a56b51f56cef50cdfa554258eecdab046"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a56b51f56cef50cdfa554258eecdab046">armnn::TransposeConvolution2dDescriptor::m_PadTop</a></div><div class="ttdeci">uint32_t m_PadTop</div><div class="ttdoc">Padding top value in the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01246">Descriptors.hpp:1246</a></div></div>
<div class="ttc" id="class_layer_verifier_base_with_descriptor_and_constants_xhtml"><div class="ttname"><a href="class_layer_verifier_base_with_descriptor_and_constants.xhtml">LayerVerifierBaseWithDescriptorAndConstants</a></div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8hpp_source.xhtml#l00107">SerializerTestUtils.hpp:107</a></div></div>
<div class="ttc" id="structarmnn_1_1_stand_in_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stand_in_descriptor.xhtml">armnn::StandInDescriptor</a></div><div class="ttdoc">A StandInDescriptor for the StandIn layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01054">Descriptors.hpp:1054</a></div></div>
<div class="ttc" id="class_layer_verifier_base_xhtml_a39bdf94af97d9484d02649b749da327c"><div class="ttname"><a href="class_layer_verifier_base.xhtml#a39bdf94af97d9484d02649b749da327c">LayerVerifierBase::LayerVerifierBase</a></div><div class="ttdeci">LayerVerifierBase(const std::string &amp;layerName, const std::vector&lt; armnn::TensorInfo &gt; &amp;inputInfos, const std::vector&lt; armnn::TensorInfo &gt; &amp;outputInfos)</div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8cpp_source.xhtml#l00011">SerializerTestUtils.cpp:11</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7ed9bc7c26df67d274d5dd4cd83adf0f"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7ed9bc7c26df67d274d5dd4cd83adf0f">armnn::DetectionPostProcessDescriptor::m_UseRegularNms</a></div><div class="ttdeci">bool m_UseRegularNms</div><div class="ttdoc">Use Regular NMS. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00555">Descriptors.hpp:555</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::TransposeConvolution2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01256">Descriptors.hpp:1256</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a7c5531bbefed0945814f874baf9e0e0f">armnn::LayerType::Addition</a></div></div>
<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a46c3fa15c46fb0d1dcdc24d0ea5cb5cd"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#a46c3fa15c46fb0d1dcdc24d0ea5cb5cd">armnn::ResizeDescriptor::m_TargetHeight</a></div><div class="ttdeci">uint32_t m_TargetHeight</div><div class="ttdoc">Target height value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00818">Descriptors.hpp:818</a></div></div>
<div class="ttc" id="structarmnn_1_1_slice_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_slice_descriptor.xhtml">armnn::SliceDescriptor</a></div><div class="ttdoc">A SliceDescriptor for the SliceLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01001">Descriptors.hpp:1001</a></div></div>
<div class="ttc" id="classarmnn_1_1_permutation_vector_xhtml"><div class="ttname"><a href="classarmnn_1_1_permutation_vector.xhtml">armnn::PermutationVector</a></div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00212">Types.hpp:212</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_i_connectable_layer_xhtml_adceb04ae84c524e4d01881e3754a4d59"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#adceb04ae84c524e4d01881e3754a4d59">armnn::IConnectableLayer::GetType</a></div><div class="ttdeci">virtual LayerType GetType() const =0</div><div class="ttdoc">Returns the armnn::LayerType of this layer. </div></div>
<div class="ttc" id="structarmnn_1_1_space_to_depth_descriptor_xhtml_a6c6b8957f1e176867e5fb05b1a1a1486"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_descriptor.xhtml#a6c6b8957f1e176867e5fb05b1a1a1486">armnn::SpaceToDepthDescriptor::m_BlockSize</a></div><div class="ttdeci">unsigned int m_BlockSize</div><div class="ttdoc">Scalar specifying the input block size. It must be &gt;= 1. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00901">Descriptors.hpp:901</a></div></div>
<div class="ttc" id="_i_network_8hpp_xhtml"><div class="ttname"><a href="_i_network_8hpp.xhtml">INetwork.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::Pooling2dDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00385">Descriptors.hpp:385</a></div></div>
<div class="ttc" id="structarmnn_1_1_reduce_descriptor_xhtml_aa1c6fc8c96404252f1072632fc5acb59"><div class="ttname"><a href="structarmnn_1_1_reduce_descriptor.xhtml#aa1c6fc8c96404252f1072632fc5acb59">armnn::ReduceDescriptor::m_vAxis</a></div><div class="ttdeci">std::vector&lt; uint32_t &gt; m_vAxis</div><div class="ttdoc">The indices of the dimensions to reduce. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01322">Descriptors.hpp:1322</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_aa61510cbd529870182e918ac6e8b9d72"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#aa61510cbd529870182e918ac6e8b9d72">armnn::DetectionPostProcessDescriptor::m_ScaleH</a></div><div class="ttdeci">float m_ScaleH</div><div class="ttdoc">Center size encoding scale height. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00563">Descriptors.hpp:563</a></div></div>
<div class="ttc" id="structarmnn_1_1_space_to_batch_nd_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_batch_nd_descriptor.xhtml">armnn::SpaceToBatchNdDescriptor</a></div><div class="ttdoc">A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00852">Descriptors.hpp:852</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_descriptor_xhtml_aa3c6a77a963a98ccb8ea7b8fd008a8c1"><div class="ttname"><a href="structarmnn_1_1_convolution2d_descriptor.xhtml#aa3c6a77a963a98ccb8ea7b8fd008a8c1">armnn::Convolution2dDescriptor::m_DilationX</a></div><div class="ttdeci">uint32_t m_DilationX</div><div class="ttdoc">Dilation along x axis. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00450">Descriptors.hpp:450</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4acb17869fe51048b5a5c4c6106551a255">armnn::LayerType::Constant</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_transpose_convolution2d_descriptor_xhtml_ac18546ebbebbb32fe0a03baa9bf2c600"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac18546ebbebbb32fe0a03baa9bf2c600">armnn::TransposeConvolution2dDescriptor::m_PadLeft</a></div><div class="ttdeci">uint32_t m_PadLeft</div><div class="ttdoc">Padding left value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01242">Descriptors.hpp:1242</a></div></div>
<div class="ttc" id="_serializer_test_utils_8hpp_xhtml"><div class="ttname"><a href="_serializer_test_utils_8hpp.xhtml">SerializerTestUtils.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_ae1a4b3b6c60552509b89747cebb900a2"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#ae1a4b3b6c60552509b89747cebb900a2">armnn::ResizeDescriptor::m_AlignCorners</a></div><div class="ttdeci">bool m_AlignCorners</div><div class="ttdoc">Aligned corners. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00825">Descriptors.hpp:825</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_afe6a3377c4531315354def9023c8fdda"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#afe6a3377c4531315354def9023c8fdda">armnn::TransposeConvolution2dDescriptor::m_StrideX</a></div><div class="ttdeci">uint32_t m_StrideX</div><div class="ttdoc">Stride value when proceeding through input for the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01250">Descriptors.hpp:1250</a></div></div>
<div class="ttc" id="structarmnn_1_1_gather_descriptor_xhtml_a35d11c7d509d1adbae1ae01c58394a7f"><div class="ttname"><a href="structarmnn_1_1_gather_descriptor.xhtml#a35d11c7d509d1adbae1ae01c58394a7f">armnn::GatherDescriptor::m_Axis</a></div><div class="ttdeci">int32_t m_Axis</div><div class="ttdoc">The axis in params to gather indices from. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00758">Descriptors.hpp:758</a></div></div>
<div class="ttc" id="structarmnn_1_1_elementwise_unary_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_elementwise_unary_descriptor.xhtml">armnn::ElementwiseUnaryDescriptor</a></div><div class="ttdoc">A ElementwiseUnaryDescriptor for the ElementwiseUnaryLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00098">Descriptors.hpp:98</a></div></div>
<div class="ttc" id="_i_deserializer_8hpp_xhtml"><div class="ttname"><a href="_i_deserializer_8hpp.xhtml">IDeserializer.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::DepthwiseConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00500">Descriptors.hpp:500</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4abbc155fb2b111bf61c4f5ff892915e6b"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4abbc155fb2b111bf61c4f5ff892915e6b">armnn::LayerType::Switch</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_ac1fe174bbadfb39a2b636940c2e647c8"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#ac1fe174bbadfb39a2b636940c2e647c8">armnn::TransposeConvolution2dDescriptor::m_StrideY</a></div><div class="ttdeci">uint32_t m_StrideY</div><div class="ttdoc">Stride value when proceeding through input for the height dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01252">Descriptors.hpp:1252</a></div></div>
<div class="ttc" id="classarmnn_1_1_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_exception.xhtml">armnn::Exception</a></div><div class="ttdoc">Base class for all ArmNN exceptions so that users can filter to just those. </div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00046">Exceptions.hpp:46</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="_descriptors_8hpp_xhtml"><div class="ttname"><a href="_descriptors_8hpp.xhtml">Descriptors.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f"><div class="ttname"><a href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaf17c98bbd83c27d6426d2ff3fa81d7f">armnn::ResizeMethod::Bilinear</a></div></div>
<div class="ttc" id="class_layer_verifier_base_xhtml"><div class="ttname"><a href="class_layer_verifier_base.xhtml">LayerVerifierBase</a></div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8hpp_source.xhtml#l00024">SerializerTestUtils.hpp:24</a></div></div>
<div class="ttc" id="_serializer_test_utils_8cpp_xhtml_a104f74b01c30ad4a17d765309a9731bd"><div class="ttname"><a href="_serializer_test_utils_8cpp.xhtml#a104f74b01c30ad4a17d765309a9731bd">CompareConstTensor</a></div><div class="ttdeci">void CompareConstTensor(const armnn::ConstTensor &amp;tensor1, const armnn::ConstTensor &amp;tensor2)</div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8cpp_source.xhtml#l00115">SerializerTestUtils.cpp:115</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot &amp; GetInputSlot(unsigned int index) const =0</div><div class="ttdoc">Get a const input slot handle by slot index. </div></div>
<div class="ttc" id="structarmnn_1_1_mean_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_mean_descriptor.xhtml">armnn::MeanDescriptor</a></div><div class="ttdoc">A MeanDescriptor for the MeanLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00951">Descriptors.hpp:951</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_convolution2d_descriptor_xhtml_a002bc30e590d78cbb4f4d12171055ca7"><div class="ttname"><a href="structarmnn_1_1_transpose_convolution2d_descriptor.xhtml#a002bc30e590d78cbb4f4d12171055ca7">armnn::TransposeConvolution2dDescriptor::m_PadRight</a></div><div class="ttdeci">uint32_t m_PadRight</div><div class="ttdoc">Padding right value in the width dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01244">Descriptors.hpp:1244</a></div></div>
<div class="ttc" id="structarmnn_1_1_transpose_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_transpose_descriptor.xhtml">armnn::TransposeDescriptor</a></div><div class="ttdoc">A TransposeDescriptor for the TransposeLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01263">Descriptors.hpp:1263</a></div></div>
<div class="ttc" id="structarmnn_1_1_strided_slice_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_strided_slice_descriptor.xhtml">armnn::StridedSliceDescriptor</a></div><div class="ttdoc">A StridedSliceDescriptor for the StridedSliceLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01076">Descriptors.hpp:1076</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_i_connectable_layer_xhtml_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot &amp; GetOutputSlot(unsigned int index) const =0</div><div class="ttdoc">Get the const output slot handle by slot index. </div></div>
<div class="ttc" id="namespacearmnn_xhtml_a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f"><div class="ttname"><a href="namespacearmnn.xhtml#a9a2af2f8c4af4f9efa8e79417d505ac4aaa020331bb30d2fa2ecf7c3a0777823f">armnn::ResizeMethod::NearestNeighbor</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_abc05539fc6e7907f32ef0fb242e3b3b0aa0ec87054b5e5b7847d0d8780a01a3d5"><div class="ttname"><a href="namespacearmnn.xhtml#abc05539fc6e7907f32ef0fb242e3b3b0aa0ec87054b5e5b7847d0d8780a01a3d5">armnn::ReduceOperation::Sum</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a7a2156ec7d9c012ce00bbcc6afcb9028"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a7a2156ec7d9c012ce00bbcc6afcb9028">armnn::DetectionPostProcessDescriptor::m_ScaleY</a></div><div class="ttdeci">float m_ScaleY</div><div class="ttdoc">Center size encoding scale y. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00559">Descriptors.hpp:559</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a733ae6b70d0bfa43433c3e7606992328"><div class="ttname"><a href="namespacearmnn.xhtml#a733ae6b70d0bfa43433c3e7606992328">armnn::CreateDescriptorForConcatenation</a></div><div class="ttdeci">OriginsDescriptor CreateDescriptorForConcatenation(TensorShapeIt first, TensorShapeIt last, unsigned int concatenationDimension)</div><div class="ttdoc">Convenience template to create an OriginsDescriptor to use when creating a ConcatLayer for performing...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00258">Descriptors.hpp:258</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml_a4392dd6b4862cc9cf95ae8f1001ba592"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml#a4392dd6b4862cc9cf95ae8f1001ba592">armnn::DetectionPostProcessDescriptor::m_NmsScoreThreshold</a></div><div class="ttdeci">float m_NmsScoreThreshold</div><div class="ttdoc">NMS score threshold. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00549">Descriptors.hpp:549</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr&lt; INetwork, void(*)(INetwork *network)&gt; INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="classarmnn_deserializer_1_1_i_deserializer_xhtml"><div class="ttname"><a href="classarmnn_deserializer_1_1_i_deserializer.xhtml">armnnDeserializer::IDeserializer</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_deserializer_8hpp_source.xhtml#l00027">IDeserializer.hpp:27</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_output_slot_xhtml_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.xhtml#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &amp;destination)=0</div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_descriptor.xhtml">armnn::Pooling2dDescriptor</a></div><div class="ttdoc">A Pooling2dDescriptor for the Pooling2dLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00329">Descriptors.hpp:329</a></div></div>
<div class="ttc" id="_serializer_test_utils_8cpp_xhtml_a228162aa622e2e39abb4f498c761ab5e"><div class="ttname"><a href="_serializer_test_utils_8cpp.xhtml#a228162aa622e2e39abb4f498c761ab5e">SerializeNetwork</a></div><div class="ttdeci">std::string SerializeNetwork(const armnn::INetwork &amp;network)</div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8cpp_source.xhtml#l00152">SerializerTestUtils.cpp:152</a></div></div>
<div class="ttc" id="structarmnn_1_1_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.xhtml">armnn::NormalizationDescriptor</a></div><div class="ttdoc">A NormalizationDescriptor for the NormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00567">Descriptors.hpp:567</a></div></div>
<div class="ttc" id="structarmnn_1_1_resize_descriptor_xhtml_a6089e1ca91914015777ea780a513131a"><div class="ttname"><a href="structarmnn_1_1_resize_descriptor.xhtml#a6089e1ca91914015777ea780a513131a">armnn::ResizeDescriptor::m_DataLayout</a></div><div class="ttdeci">DataLayout m_DataLayout</div><div class="ttdoc">The data layout to be used (NCHW, NHWC). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00823">Descriptors.hpp:823</a></div></div>
<div class="ttc" id="structarmnn_1_1_detection_post_process_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_detection_post_process_descriptor.xhtml">armnn::DetectionPostProcessDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00511">Descriptors.hpp:511</a></div></div>
<div class="ttc" id="structarmnn_1_1_instance_normalization_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_instance_normalization_descriptor.xhtml">armnn::InstanceNormalizationDescriptor</a></div><div class="ttdoc">An InstanceNormalizationDescriptor for InstanceNormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00645">Descriptors.hpp:645</a></div></div>
<div class="ttc" id="structarmnn_1_1_resize_bilinear_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_resize_bilinear_descriptor.xhtml">armnn::ResizeBilinearDescriptor</a></div><div class="ttdoc">A ResizeBilinearDescriptor for the ResizeBilinearLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00762">Descriptors.hpp:762</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00510">Network.cpp:510</a></div></div>
<div class="ttc" id="structarmnn_1_1_softmax_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_softmax_descriptor.xhtml">armnn::SoftmaxDescriptor</a></div><div class="ttdoc">A SoftmaxDescriptor for the SoftmaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00139">Descriptors.hpp:139</a></div></div>
<div class="ttc" id="structarmnn_1_1_views_descriptor_xhtml_a2b125117aa61f9baf3a9cb8658aa61a2"><div class="ttname"><a href="structarmnn_1_1_views_descriptor.xhtml#a2b125117aa61f9baf3a9cb8658aa61a2">armnn::ViewsDescriptor::SetViewOriginCoord</a></div><div class="ttdeci">Status SetViewOriginCoord(uint32_t view, uint32_t coord, uint32_t value)</div><div class="ttdoc">Set the view origin coordinates. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8cpp_source.xhtml#l00310">Descriptors.cpp:310</a></div></div>
<div class="ttc" id="_serializer_tests_8cpp_xhtml_a613b87da634d3ef40e416fea62da62b9"><div class="ttname"><a href="_serializer_tests_8cpp.xhtml#a613b87da634d3ef40e416fea62da62b9">BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(SerializeAbs)</div><div class="ttdef"><b>Definition:</b> <a href="_serializer_tests_8cpp_source.xhtml#l00026">SerializerTests.cpp:26</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="structarmnn_1_1_fill_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fill_descriptor.xhtml">armnn::FillDescriptor</a></div><div class="ttdoc">A FillDescriptor for the FillLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00723">Descriptors.hpp:723</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="class_layer_verifier_base_xhtml_a49f7f1098adb86fd2197d9aee3924de2"><div class="ttname"><a href="class_layer_verifier_base.xhtml#a49f7f1098adb86fd2197d9aee3924de2">LayerVerifierBase::ExecuteStrategy</a></div><div class="ttdeci">void ExecuteStrategy(const armnn::IConnectableLayer *layer, const armnn::BaseDescriptor &amp;descriptor, const std::vector&lt; armnn::ConstTensor &gt; &amp;constants, const char *name, const armnn::LayerBindingId id=0) override</div><div class="ttdef"><b>Definition:</b> <a href="_serializer_test_utils_8cpp_source.xhtml#l00019">SerializerTestUtils.cpp:19</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
<div class="ttc" id="structarmnn_1_1_permute_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_permute_descriptor.xhtml">armnn::PermuteDescriptor</a></div><div class="ttdoc">A PermuteDescriptor for the PermuteLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00118">Descriptors.hpp:118</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>
<div class="ttc" id="_neon_end_to_end_tests_8cpp_xhtml_ac0981848e4ae57729f14f72bd4caa9f8"><div class="ttname"><a href="_neon_end_to_end_tests_8cpp.xhtml#ac0981848e4ae57729f14f72bd4caa9f8">anchors</a></div><div class="ttdeci">std::vector&lt; float &gt; anchors({ 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 0.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 10.5f, 1.0f, 1.0f, 0.5f, 100.5f, 1.0f, 1.0f })</div></div>
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