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+<a href="_optimized_network_tests_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;</div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_graph_8hpp.html">Graph.hpp</a>&gt;</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_network_8hpp.html">Network.hpp</a>&gt;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_ref_workload_factory_8hpp.html">reference/RefWorkloadFactory.hpp</a>&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;</div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;boost/test/unit_test.hpp&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;</div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<a class="code" href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(OptimizedNetwork)</div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;</div><div class="line"><a name="l00016"></a><span class="lineno"><a class="line" href="_optimized_network_tests_8cpp.html#a4b3a7b26ef63f589e9e090bd050c1ab7">   16</a></span>&#160;<a class="code" href="_optimized_network_tests_8cpp.html#a4b3a7b26ef63f589e9e090bd050c1ab7">BOOST_AUTO_TEST_CASE</a>(SerializeToDot)</div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;{</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;    <a class="code" href="classarmnn_1_1_network.html">armnn::Network</a> net;</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="comment">//Defines layers.</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;    <span class="keyword">auto</span> input = net.<a class="code" href="classarmnn_1_1_network.html#a90d8841cfbbc82ab02328f33fed24ac6">AddInputLayer</a>(0);</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;    <span class="keyword">auto</span> add = net.<a class="code" href="classarmnn_1_1_network.html#adb60c75544796e23d7abc1ce0476f6d9">AddAdditionLayer</a>();</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;    <span class="keyword">auto</span> output = net.<a class="code" href="classarmnn_1_1_network.html#ad55ff20f4c7e60c18b849e61f28f0e2e">AddOutputLayer</a>(0);</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;    <span class="comment">// Connects layers.</span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(add-&gt;GetInputSlot(0));</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;    input-&gt;GetOutputSlot(0).Connect(add-&gt;GetInputSlot(1));</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;    add-&gt;GetOutputSlot(0).Connect(output-&gt;GetInputSlot(0));</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> shape({4});</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> info(shape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    input-&gt;GetOutputSlot(0).SetTensorInfo(info);</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;    add-&gt;GetOutputSlot(0).SetTensorInfo(info);</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.html">armnn::IRuntime::CreationOptions</a> <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a>;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    <a class="code" href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    std::vector&lt;armnn::BackendId&gt; backends = {<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a>};</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optimizedNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(net, backends, runtime-&gt;GetDeviceSpec());</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    std::ostringstream ss;</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    optimizedNet-&gt;SerializeToDot(ss);</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    <span class="keyword">auto</span> inputId = input-&gt;GetGuid();</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    <span class="keyword">auto</span> addId = add-&gt;GetGuid();</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    <span class="keyword">auto</span> outputId = output-&gt;GetGuid();</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;    std::stringstream expected;</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;    expected &lt;&lt;</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;        <span class="stringliteral">&quot;digraph Optimized {\n&quot;</span></div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;        <span class="stringliteral">&quot;    node [shape=\&quot;record\&quot;];\n&quot;</span></div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;        <span class="stringliteral">&quot;    edge [fontsize=8 fontcolor=\&quot;blue\&quot; fontname=\&quot;arial-bold\&quot;];\n&quot;</span></div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;        <span class="stringliteral">&quot;    &quot;</span> &lt;&lt; inputId &lt;&lt; <span class="stringliteral">&quot; [label=\&quot;{Input|LayerType : Input\\lBackendID : CpuRef\\l}\&quot;];\n&quot;</span></div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;        <span class="stringliteral">&quot;    &quot;</span> &lt;&lt; addId &lt;&lt; <span class="stringliteral">&quot; [label=\&quot;{Addition|LayerType : Addition\\lBackendID : CpuRef\\l}\&quot;];\n&quot;</span></div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;        <span class="stringliteral">&quot;    &quot;</span> &lt;&lt; outputId &lt;&lt; <span class="stringliteral">&quot; [label=\&quot;{Output|LayerType : Output\\lBackendID : CpuRef\\l}\&quot;];\n&quot;</span></div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;        <span class="stringliteral">&quot;    &quot;</span> &lt;&lt; inputId &lt;&lt; <span class="stringliteral">&quot; -&gt; &quot;</span> &lt;&lt; addId &lt;&lt; <span class="stringliteral">&quot; [label=&lt; [4] &gt;];\n&quot;</span></div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;        <span class="stringliteral">&quot;    &quot;</span> &lt;&lt; inputId &lt;&lt; <span class="stringliteral">&quot; -&gt; &quot;</span> &lt;&lt; addId &lt;&lt; <span class="stringliteral">&quot; [label=&lt; [4] &gt;];\n&quot;</span></div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;        <span class="stringliteral">&quot;    &quot;</span> &lt;&lt; addId &lt;&lt; <span class="stringliteral">&quot; -&gt; &quot;</span> &lt;&lt; outputId &lt;&lt; <span class="stringliteral">&quot; [label=&lt; [4] &gt;];\n&quot;</span></div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;        <span class="stringliteral">&quot;}\n&quot;</span>;</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    BOOST_TEST(ss.str() == expected.str());</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;</div><div class="line"><a name="l00064"></a><span class="lineno"><a class="line" href="_optimized_network_tests_8cpp.html#a12dcef28bd7edb36b696eaa84b87647c">   64</a></span>&#160;<a class="code" href="_optimized_network_tests_8cpp.html#a4b3a7b26ef63f589e9e090bd050c1ab7">BOOST_AUTO_TEST_CASE</a>(OptimizeValidateDeviceNonSupportLayerNoFallback)</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;{</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <span class="comment">// build up the structure of the network</span></div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.html#a706f7345af3f18f4b16e226a672214c6">armnn::INetwork::Create</a>());</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* input = net-&gt;AddInputLayer(0);</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;    <span class="comment">// This layer configuration isn&#39;t supported by CpuAcc and isn&#39;t allowed to fall back, so Optimize will return null.</span></div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;    <a class="code" href="structarmnn_1_1_normalization_descriptor.html">armnn::NormalizationDescriptor</a> descriptor;</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* normalize = net-&gt;AddNormalizationLayer(descriptor);</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="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* output = net-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(normalize-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    normalize-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({ 1, 1, 4, 4 }, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    normalize-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({ 1, 1, 4, 4 }, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.html">armnn::IRuntime::CreationOptions</a> <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a>;</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    <a class="code" href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    std::vector&lt;armnn::BackendId&gt; backends = { <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a> };</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(*net, backends, runtime-&gt;GetDeviceSpec());</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160; 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   <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* output = net-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(normalize-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;    normalize-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({ 1, 1, 4, 4 }, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    normalize-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({ 1, 1, 4, 4 }, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</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">  110</span>&#160;    <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.html">armnn::IRuntime::CreationOptions</a> <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a>;</div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;    <a class="code" href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    std::vector&lt;armnn::BackendId&gt; backends = { <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a>, <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a> };</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;    <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(*net, backends, runtime-&gt;GetDeviceSpec());</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    BOOST_REQUIRE(optNet);</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;</div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    <span class="keywordflow">for</span> (<span class="keyword">auto</span>&amp;&amp; layer : static_cast&lt;armnn::OptimizedNetwork*&gt;(optNet.get())-&gt;GetGraph())</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    {</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;        <span class="comment">// If NEON is enabled, Input and Output layers are supported by CpuAcc,</span></div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160; 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           <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;GetBackendId() == <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a>);</div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;        }</div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;        <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer-&gt;GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f">armnn::LayerType::Normalization</a>)</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;        {</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;            <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;GetBackendId() == <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a>);</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;        }</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;<span class="preprocessor">#else</span></div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;        <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;GetBackendId() == <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a>);</div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;<span class="preprocessor">#endif</span></div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    }</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;</div><div class="line"><a name="l00137"></a><span class="lineno"><a class="line" href="_optimized_network_tests_8cpp.html#a5f53d76cfa699d6fbbfc9c2914318768">  137</a></span>&#160;<a class="code" href="_optimized_network_tests_8cpp.html#a4b3a7b26ef63f589e9e090bd050c1ab7">BOOST_AUTO_TEST_CASE</a>(OptimizeValidateWorkloadsUndefinedComputeDevice)</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;{</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> desc({3, 5}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    <a class="code" href="classarmnn_1_1_network.html">armnn::Network</a>  net;</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;    <a class="code" href="structarmnn_1_1_normalization_descriptor.html">armnn::NormalizationDescriptor</a> nmDesc;</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    <a class="code" href="structarmnn_1_1_activation_descriptor.html">armnn::ActivationDescriptor</a> acDesc;</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    <span class="comment">//    in</span></div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    <span class="comment">//     |</span></div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="comment">//    nm</span></div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    <span class="comment">//   /  |</span></div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;    <span class="comment">//  ac  |</span></div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    <span class="comment">//   \  |</span></div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    <span class="comment">//    ml</span></div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    <span class="comment">//     |</span></div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    <span class="comment">//    sm</span></div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    <span class="comment">//     |</span></div><div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;    <span class="comment">//    ot</span></div><div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer = net.AddInputLayer(0, <span class="stringliteral">&quot;in&quot;</span>);</div><div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(desc);</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; 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   layer = net.AddActivationLayer(acDesc, <span class="stringliteral">&quot;ac&quot;</span>);</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;    normLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(desc);</div><div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;</div><div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* prevLayer = layer;</div><div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;    layer = net.AddMultiplicationLayer(<span class="stringliteral">&quot;ml&quot;</span>);</div><div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;</div><div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;    prevLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;    normLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(desc);</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;    prevLayer = layer;</div><div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;    <a class="code" href="structarmnn_1_1_softmax_descriptor.html">armnn::SoftmaxDescriptor</a> softmaxDescriptor;</div><div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;    layer = net.AddSoftmaxLayer(softmaxDescriptor, <span class="stringliteral">&quot;sm&quot;</span>);</div><div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;</div><div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;    prevLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(desc);</div><div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;</div><div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;    prevLayer = layer;</div><div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;    layer = net.AddOutputLayer(0, <span class="stringliteral">&quot;ot&quot;</span>);</div><div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;</div><div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;    prevLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;</div><div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;    <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.html">armnn::IRuntime::CreationOptions</a> <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a>;</div><div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;    <a class="code" href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</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;    std::vector&lt;armnn::BackendId&gt; backends = { <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a> };</div><div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;</div><div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;    <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(net, backends, runtime-&gt;GetDeviceSpec());</div><div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(!optNet);</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;}</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"><a class="line" href="_optimized_network_tests_8cpp.html#a899bd2622a67b52d28aa502da141b92a">  199</a></span>&#160;<a class="code" href="_optimized_network_tests_8cpp.html#a4b3a7b26ef63f589e9e090bd050c1ab7">BOOST_AUTO_TEST_CASE</a>(OptimizeValidateWorkloadsUndefinedComputeDeviceWithFallback)</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;{</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> desc({3, 5}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    <a class="code" href="classarmnn_1_1_network.html">armnn::Network</a>  net;</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;    <a class="code" href="structarmnn_1_1_normalization_descriptor.html">armnn::NormalizationDescriptor</a> nmDesc;</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;    <a class="code" href="structarmnn_1_1_activation_descriptor.html">armnn::ActivationDescriptor</a> acDesc;</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;    <span class="comment">//    in</span></div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;    <span class="comment">//     |</span></div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;    <span class="comment">//    nm</span></div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    <span class="comment">//   /  |</span></div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;    <span class="comment">//  ac  |</span></div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;    <span class="comment">//   \  |</span></div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;    <span class="comment">//    ml</span></div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    <span class="comment">//     |</span></div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;    <span class="comment">//    sm</span></div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;    <span class="comment">//     |</span></div><div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;    <span class="comment">//    ot</span></div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer = net.AddInputLayer(0, <span class="stringliteral">&quot;in&quot;</span>);</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(desc);</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* <span class="keyword">const</span> normLayer = net.AddNormalizationLayer(nmDesc, <span class="stringliteral">&quot;nm&quot;</span>);</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(normLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;    normLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(desc);</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;    layer = net.AddActivationLayer(acDesc, <span class="stringliteral">&quot;ac&quot;</span>);</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    normLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(desc);</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;    <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* prevLayer = layer;</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;    layer = net.AddMultiplicationLayer(<span class="stringliteral">&quot;ml&quot;</span>);</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    prevLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;    normLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(desc);</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;</div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;    prevLayer = layer;</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;    <a class="code" href="structarmnn_1_1_softmax_descriptor.html">armnn::SoftmaxDescriptor</a> softmaxDescriptor;</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;    layer = net.AddSoftmaxLayer(softmaxDescriptor, <span class="stringliteral">&quot;sm&quot;</span>);</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    prevLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;    layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(desc);</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;    prevLayer = layer;</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;    layer = net.AddOutputLayer(0, <span class="stringliteral">&quot;ot&quot;</span>);</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;    prevLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(layer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;    <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.html">armnn::IRuntime::CreationOptions</a> <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a>;</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    <a class="code" href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    std::vector&lt;armnn::BackendId&gt; backends = { <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a>, <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a> };</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;    <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(net, backends, runtime-&gt;GetDeviceSpec());</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(optNet);</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;    <span class="comment">// validate workloads</span></div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;    <a class="code" href="classarmnn_1_1_ref_workload_factory.html">armnn::RefWorkloadFactory</a> fact;</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;    <span class="keywordflow">for</span> (<span class="keyword">auto</span>&amp;&amp; layer : static_cast&lt;armnn::OptimizedNetwork*&gt;(optNet.get())-&gt;GetGraph())</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;        <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;GetBackendId() == <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a>);</div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;        BOOST_CHECK_NO_THROW(</div><div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;            layer-&gt;CreateWorkload(fact));</div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;    }</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"><a class="line" href="_optimized_network_tests_8cpp.html#a42d3dbdcea410ce0e03ecca41894f765">  269</a></span>&#160;<a class="code" href="_optimized_network_tests_8cpp.html#a4b3a7b26ef63f589e9e090bd050c1ab7">BOOST_AUTO_TEST_CASE</a>(OptimizeValidateWorkloadsDuplicateComputeDeviceWithFallback)</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;{</div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;    <span class="comment">// build up the structure of the network</span></div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;    <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.html#a706f7345af3f18f4b16e226a672214c6">armnn::INetwork::Create</a>());</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* input = net-&gt;AddInputLayer(0);</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;</div><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;    <span class="comment">// This layer configuration isn&#39;t supported by CpuAcc but it allows to fallback to CpuRef.</span></div><div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;    <a class="code" href="structarmnn_1_1_normalization_descriptor.html">armnn::NormalizationDescriptor</a> descriptor;</div><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* normalize = net-&gt;AddNormalizationLayer(descriptor);</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;</div><div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;    <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* output = net-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(normalize-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;    normalize-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(output-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#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.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({ 1, 1, 4, 4 }, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;    normalize-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">SetTensorInfo</a>(<a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>({ 1, 1, 4, 4 }, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>));</div><div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;</div><div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;    <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.html">armnn::IRuntime::CreationOptions</a> <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a>;</div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;    <a class="code" href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a>(options));</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;</div><div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;    std::vector&lt;armnn::BackendId&gt; backends = { <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a>,</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;                                             <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a>,</div><div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;                                             <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a> };</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;    <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(*net, backends, runtime-&gt;GetDeviceSpec());</div><div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;    BOOST_REQUIRE(optNet);</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="keywordflow">for</span> (<span class="keyword">auto</span>&amp;&amp; layer : static_cast&lt;armnn::OptimizedNetwork*&gt;(optNet.get())-&gt;GetGraph())</div><div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;    {</div><div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;        <span class="comment">// If NEON is enabled, Input and Output layers are supported by CpuAcc,</span></div><div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;        <span class="comment">// the other layers are supported by CpuRef.</span></div><div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;        <span class="comment">// If only CL is enabled, Input and Output layers are supported by GpuAcc,</span></div><div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;        <span class="comment">// the other layers are supported by CpuRef.</span></div><div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;        <span class="comment">// If neither NEON, nor CL is enabled, all layers are supported by CpuRef.</span></div><div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;<span class="preprocessor">#if defined(ARMCOMPUTENEON_ENABLED)</span></div><div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;        <span class="keywordflow">if</span> (layer-&gt;GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a> || layer-&gt;GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>)</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;            <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;GetBackendId() == <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a>);</div><div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;        }</div><div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;        <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer-&gt;GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f">armnn::LayerType::Normalization</a>)</div><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;        {</div><div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;            <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;GetBackendId() == <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a>);</div><div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;        }</div><div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;<span class="preprocessor">#elif defined(ARMCOMPUTECL_ENABLED)</span></div><div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;        <span class="keywordflow">if</span> (layer-&gt;GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a> || layer-&gt;GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>)</div><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;        {</div><div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;            <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer-&gt;GetBackendId() == <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a>);</div><div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160; 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+<div class="ttc" id="classarmnn_1_1_network_html_a90d8841cfbbc82ab02328f33fed24ac6"><div class="ttname"><a href="classarmnn_1_1_network.html#a90d8841cfbbc82ab02328f33fed24ac6">armnn::Network::AddInputLayer</a></div><div class="ttdeci">IConnectableLayer * AddInputLayer(LayerBindingId id, const char *name=nullptr) override</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.html#l00953">Network.cpp:953</a></div></div>
+<div class="ttc" id="namespacearmnn_html_a82e98ef05fd67036d1195ba17174d685"><div class="ttname"><a href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a></div><div class="ttdeci">IOptimizedNetworkPtr Optimize(const INetwork &amp;network, const std::vector&lt; BackendId &gt; &amp;backendPreferences, const IDeviceSpec &amp;deviceSpec, const OptimizerOptions &amp;options=OptimizerOptions(), Optional&lt; std::vector&lt; std::string &gt; &amp;&gt; messages=EmptyOptional())</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.html#l00807">Network.cpp:807</a></div></div>
+<div class="ttc" id="namespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="structarmnn_1_1_activation_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.html">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00020">Descriptors.hpp:20</a></div></div>
+<div class="ttc" id="_network_8hpp_html"><div class="ttname"><a href="_network_8hpp.html">Network.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_network_html_adb60c75544796e23d7abc1ce0476f6d9"><div class="ttname"><a href="classarmnn_1_1_network.html#adb60c75544796e23d7abc1ce0476f6d9">armnn::Network::AddAdditionLayer</a></div><div class="ttdeci">IConnectableLayer * AddAdditionLayer(const char *name=nullptr) override</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.html#l01212">Network.cpp:1212</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_output_slot_html_a5ee4a6c9a2481245487b1b1a70d20fd0"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.html#a5ee4a6c9a2481245487b1b1a70d20fd0">armnn::IOutputSlot::SetTensorInfo</a></div><div class="ttdeci">virtual void SetTensorInfo(const TensorInfo &amp;tensorInfo)=0</div></div>
+<div class="ttc" id="classarmnn_1_1_network_html"><div class="ttname"><a href="classarmnn_1_1_network.html">armnn::Network</a></div><div class="ttdoc">Private implementation of INetwork. </div><div class="ttdef"><b>Definition:</b> <a href="_network_8hpp_source.html#l00027">Network.hpp:27</a></div></div>
+<div class="ttc" id="namespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f">armnn::LayerType::Normalization</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_network_html_a706f7345af3f18f4b16e226a672214c6"><div class="ttname"><a href="classarmnn_1_1_i_network.html#a706f7345af3f18f4b16e226a672214c6">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.html#l00048">Network.cpp:48</a></div></div>
+<div class="ttc" id="_file_only_profiling_decorator_tests_8cpp_html_a0c262ba6f6c189a2d092d127c1b7627b"><div class="ttname"><a href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a></div><div class="ttdeci">BOOST_CHECK(profilingService.GetCurrentState()==ProfilingState::WaitingForAck)</div></div>
+<div class="ttc" id="namespacearmnn_html_ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b"><div class="ttname"><a href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a></div><div class="ttdoc">GPU Execution: OpenCL: ArmCompute. </div></div>
+<div class="ttc" id="namespacearmnn_html_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.html#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.html#l00085">INetwork.hpp:85</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64"><div class="ttname"><a href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a></div><div class="ttdoc">CPU Execution: Reference C++ kernels. </div></div>
+<div class="ttc" id="classarmnn_1_1_i_runtime_html_ad44ecd3700748dc30dc4bbe34ba5bde7"><div class="ttname"><a href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">armnn::IRuntime::Create</a></div><div class="ttdeci">static IRuntimePtr Create(const CreationOptions &amp;options)</div><div class="ttdef"><b>Definition:</b> <a href="_runtime_8cpp_source.html#l00032">Runtime.cpp:32</a></div></div>
+<div class="ttc" id="_profiler_tests_8cpp_html_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div>
+<div class="ttc" id="_optimized_network_tests_8cpp_html_a4b3a7b26ef63f589e9e090bd050c1ab7"><div class="ttname"><a href="_optimized_network_tests_8cpp.html#a4b3a7b26ef63f589e9e090bd050c1ab7">BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(SerializeToDot)</div><div class="ttdef"><b>Definition:</b> <a href="_optimized_network_tests_8cpp_source.html#l00016">OptimizedNetworkTests.cpp:16</a></div></div>
+<div class="ttc" id="structarmnn_1_1_softmax_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_softmax_descriptor.html">armnn::SoftmaxDescriptor</a></div><div class="ttdoc">A SoftmaxDescriptor for the SoftmaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00123">Descriptors.hpp:123</a></div></div>
+<div class="ttc" id="namespacearmnn_html_ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1"><div class="ttname"><a href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea39f8662ca778258e9c6a14f26fec5ec1">armnn::Compute::CpuAcc</a></div><div class="ttdoc">CPU Execution: NEON: ArmCompute. </div></div>
+<div class="ttc" id="_ref_workload_factory_8hpp_html"><div class="ttname"><a href="_ref_workload_factory_8hpp.html">RefWorkloadFactory.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_connectable_layer_html"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html">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.html#l00061">INetwork.hpp:61</a></div></div>
+<div class="ttc" id="_output_shape_of_squeeze_8cpp_html_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div>
+<div class="ttc" id="namespacearmnn_html_a674efcf6cbdb9e831d653ff0e821fb38"><div class="ttname"><a href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a></div><div class="ttdeci">std::unique_ptr&lt; IOptimizedNetwork, void(*)(IOptimizedNetwork *network)&gt; IOptimizedNetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00544">INetwork.hpp:544</a></div></div>
+<div class="ttc" id="structarmnn_1_1_i_runtime_1_1_creation_options_html"><div class="ttname"><a href="structarmnn_1_1_i_runtime_1_1_creation_options.html">armnn::IRuntime::CreationOptions</a></div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00041">IRuntime.hpp:41</a></div></div>
+<div class="ttc" id="_graph_8hpp_html"><div class="ttname"><a href="_graph_8hpp.html">Graph.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_network_html_ad55ff20f4c7e60c18b849e61f28f0e2e"><div class="ttname"><a href="classarmnn_1_1_network.html#ad55ff20f4c7e60c18b849e61f28f0e2e">armnn::Network::AddOutputLayer</a></div><div class="ttdeci">IConnectableLayer * AddOutputLayer(LayerBindingId id, const char *name=nullptr) override</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.html#l01222">Network.cpp:1222</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_output_slot_html_ac1835f8756a9f03c02fcf9664e3a0fce"><div class="ttname"><a href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">armnn::IOutputSlot::Connect</a></div><div class="ttdeci">virtual int Connect(IInputSlot &amp;destination)=0</div></div>
+<div class="ttc" id="_file_only_profiling_decorator_tests_8cpp_html_a6560146509197f3e197d8d36f76c1347"><div class="ttname"><a href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a></div><div class="ttdeci">armnn::Runtime::CreationOptions::ExternalProfilingOptions options</div><div class="ttdef"><b>Definition:</b> <a href="_file_only_profiling_decorator_tests_8cpp_source.html#l00045">FileOnlyProfilingDecoratorTests.cpp:45</a></div></div>
+<div class="ttc" id="classarmnn_1_1_ref_workload_factory_html"><div class="ttname"><a href="classarmnn_1_1_ref_workload_factory.html">armnn::RefWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_factory_8hpp_source.html#l00031">RefWorkloadFactory.hpp:31</a></div></div>
+<div class="ttc" id="namespacearmnn_html_a150468a02bd7b2d2d061c4aaaee939f0"><div class="ttname"><a href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">armnn::IRuntimePtr</a></div><div class="ttdeci">std::unique_ptr&lt; IRuntime, void(*)(IRuntime *runtime)&gt; IRuntimePtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_runtime_8hpp_source.html#l00024">IRuntime.hpp:24</a></div></div>
+<div class="ttc" id="namespacearmnn_html_a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5"><div class="ttname"><a href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_connectable_layer_html_a80ac4eda2e7f2757ec9dd96fc96dbd16"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">armnn::IConnectableLayer::GetOutputSlot</a></div><div class="ttdeci">virtual const IOutputSlot &amp; GetOutputSlot(unsigned int index) const =0</div></div>
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