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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> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include <<a class="code" href="_graph_8hpp.html">Graph.hpp</a>></span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_network_8hpp.html">Network.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_ref_workload_factory_8hpp.html">reference/RefWorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <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> </div><div class="line"><a name="l00016"></a><span class="lineno"><a class="line" href="_optimized_network_tests_8cpp.html#a4b3a7b26ef63f589e9e090bd050c1ab7"> 16</a></span> <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> {</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <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> </div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="comment">//Defines layers.</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <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>  <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>  <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> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <span class="comment">// Connects layers.</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  input-><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->GetInputSlot(0));</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  input->GetOutputSlot(0).Connect(add->GetInputSlot(1));</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  add->GetOutputSlot(0).Connect(output->GetInputSlot(0));</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a> shape({4});</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <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>  input->GetOutputSlot(0).SetTensorInfo(info);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  add->GetOutputSlot(0).SetTensorInfo(info);</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <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>  <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> </div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  std::vector<armnn::BackendId> 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>  <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optimizedNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(net, backends, runtime->GetDeviceSpec());</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  std::ostringstream ss;</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  optimizedNet->SerializeToDot(ss);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keyword">auto</span> inputId = input->GetGuid();</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keyword">auto</span> addId = add->GetGuid();</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keyword">auto</span> outputId = output->GetGuid();</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> </div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  std::stringstream expected;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  expected <<</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="stringliteral">"digraph Optimized {\n"</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="stringliteral">" node [shape=\"record\"];\n"</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="stringliteral">" edge [fontsize=8 fontcolor=\"blue\" fontname=\"arial-bold\"];\n"</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="stringliteral">" "</span> << inputId << <span class="stringliteral">" [label=\"{Input|LayerType : Input\\lBackendID : CpuRef\\l}\"];\n"</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="stringliteral">" "</span> << addId << <span class="stringliteral">" [label=\"{Addition|LayerType : Addition\\lBackendID : CpuRef\\l}\"];\n"</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="stringliteral">" "</span> << outputId << <span class="stringliteral">" [label=\"{Output|LayerType : Output\\lBackendID : CpuRef\\l}\"];\n"</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="stringliteral">" "</span> << inputId << <span class="stringliteral">" -> "</span> << addId << <span class="stringliteral">" [label=< [4] >];\n"</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="stringliteral">" "</span> << inputId << <span class="stringliteral">" -> "</span> << addId << <span class="stringliteral">" [label=< [4] >];\n"</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="stringliteral">" "</span> << addId << <span class="stringliteral">" -> "</span> << outputId << <span class="stringliteral">" [label=< [4] >];\n"</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="stringliteral">"}\n"</span>;</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  BOOST_TEST(ss.str() == expected.str());</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> }</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div><div class="line"><a name="l00064"></a><span class="lineno"><a class="line" href="_optimized_network_tests_8cpp.html#a12dcef28bd7edb36b696eaa84b87647c"> 64</a></span> <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> {</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="comment">// build up the structure of the network</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <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> </div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* input = net->AddInputLayer(0);</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="comment">// This layer configuration isn't supported by CpuAcc and isn't allowed to fall back, so Optimize will return null.</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <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>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* normalize = net->AddNormalizationLayer(descriptor);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> </div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* output = net->AddOutputLayer(0);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  input-><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-><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>  normalize-><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-><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> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  input-><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>  normalize-><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> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <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>  <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> </div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  std::vector<armnn::BackendId> 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>  <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(*net, backends, runtime->GetDeviceSpec());</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(!optNet);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span> }</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00091"></a><span class="lineno"><a class="line" href="_optimized_network_tests_8cpp.html#aa1ec7c26f3e16232e3da4ae42fe7bc12"> 91</a></span> <a class="code" href="_optimized_network_tests_8cpp.html#a4b3a7b26ef63f589e9e090bd050c1ab7">BOOST_AUTO_TEST_CASE</a>(OptimizeValidateDeviceNonSupportLayerWithFallback)</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> {</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="comment">// build up the structure of the network</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <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="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* input = net->AddInputLayer(0);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> </div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="comment">// This layer configuration isn't supported by CpuAcc but it allows to fallback to CpuRef.</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="structarmnn_1_1_normalization_descriptor.html">armnn::NormalizationDescriptor</a> descriptor;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* normalize = net->AddNormalizationLayer(descriptor);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> </div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* output = net->AddOutputLayer(0);</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> </div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  input-><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-><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>  normalize-><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-><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> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  input-><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>  normalize-><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> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <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>  <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> </div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  std::vector<armnn::BackendId> 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>  <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(*net, backends, runtime->GetDeviceSpec());</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  BOOST_REQUIRE(optNet);</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : static_cast<armnn::OptimizedNetwork*>(optNet.get())->GetGraph())</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  {</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <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>  <span class="comment">// the other layers are supported by CpuRef.</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="comment">// If NEON is not enabled, all layers are supported by CpuRef.</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="preprocessor">#if defined(ARMCOMPUTENEON_ENABLED)</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">if</span> (layer->GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a> || layer->GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a29c2c02a361c9d7028472e5d92cd4a54">armnn::LayerType::Output</a>)</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  {</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer->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>  }</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer->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>  {</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer->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>  }</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer->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> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  }</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> }</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> </div><div class="line"><a name="l00137"></a><span class="lineno"><a class="line" href="_optimized_network_tests_8cpp.html#a5f53d76cfa699d6fbbfc9c2914318768"> 137</a></span> <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> {</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <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> </div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <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> </div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <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>  <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> </div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="comment">// in</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="comment">// |</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="comment">// nm</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="comment">// / |</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="comment">// ac |</span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="comment">// \ |</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="comment">// ml</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="comment">// |</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="comment">// sm</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="comment">// |</span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="comment">// ot</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer = net.AddInputLayer(0, <span class="stringliteral">"in"</span>);</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  layer-><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> </div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <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">"nm"</span>);</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> </div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  layer-><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-><a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  normLayer-><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="l00164"></a><span class="lineno"> 164</span> </div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  layer = net.AddActivationLayer(acDesc, <span class="stringliteral">"ac"</span>);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  normLayer-><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-><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>  layer-><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> </div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <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>  layer = net.AddMultiplicationLayer(<span class="stringliteral">"ml"</span>);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  prevLayer-><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-><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>  normLayer-><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-><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>  layer-><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> </div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  prevLayer = layer;</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <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>  layer = net.AddSoftmaxLayer(softmaxDescriptor, <span class="stringliteral">"sm"</span>);</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  prevLayer-><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-><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>  layer-><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> </div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  prevLayer = layer;</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  layer = net.AddOutputLayer(0, <span class="stringliteral">"ot"</span>);</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  prevLayer-><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-><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> </div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <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>  <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> </div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  std::vector<armnn::BackendId> 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> </div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(net, backends, runtime->GetDeviceSpec());</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <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> </div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> }</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> </div><div class="line"><a name="l00199"></a><span class="lineno"><a class="line" href="_optimized_network_tests_8cpp.html#a899bd2622a67b52d28aa502da141b92a"> 199</a></span> <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> {</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <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> </div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <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> </div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <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>  <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> </div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="comment">// in</span></div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="comment">// |</span></div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="comment">// nm</span></div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="comment">// / |</span></div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="comment">// ac |</span></div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="comment">// \ |</span></div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="comment">// ml</span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <span class="comment">// |</span></div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="comment">// sm</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="comment">// |</span></div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="comment">// ot</span></div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* layer = net.AddInputLayer(0, <span class="stringliteral">"in"</span>);</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  layer-><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> </div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  <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">"nm"</span>);</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> </div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  layer-><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-><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>  normLayer-><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> </div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  layer = net.AddActivationLayer(acDesc, <span class="stringliteral">"ac"</span>);</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> </div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  normLayer-><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-><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>  layer-><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> </div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <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>  layer = net.AddMultiplicationLayer(<span class="stringliteral">"ml"</span>);</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> </div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  prevLayer-><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-><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>  normLayer-><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-><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>  layer-><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> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  prevLayer = layer;</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <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>  layer = net.AddSoftmaxLayer(softmaxDescriptor, <span class="stringliteral">"sm"</span>);</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span> </div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  prevLayer-><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-><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>  layer-><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> </div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  prevLayer = layer;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  layer = net.AddOutputLayer(0, <span class="stringliteral">"ot"</span>);</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> </div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  prevLayer-><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-><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> </div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <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>  <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> </div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  std::vector<armnn::BackendId> 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> </div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(net, backends, runtime->GetDeviceSpec());</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <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> </div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="comment">// validate workloads</span></div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <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>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : static_cast<armnn::OptimizedNetwork*>(optNet.get())->GetGraph())</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  {</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer->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>  BOOST_CHECK_NO_THROW(</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  layer->CreateWorkload(fact));</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  }</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> }</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> </div><div class="line"><a name="l00269"></a><span class="lineno"><a class="line" href="_optimized_network_tests_8cpp.html#a42d3dbdcea410ce0e03ecca41894f765"> 269</a></span> <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> {</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <span class="comment">// build up the structure of the network</span></div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <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> </div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* input = net->AddInputLayer(0);</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> </div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <span class="comment">// This layer configuration isn'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>  <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>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* normalize = net->AddNormalizationLayer(descriptor);</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> </div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">armnn::IConnectableLayer</a>* output = net->AddOutputLayer(0);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> </div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  input-><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-><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>  normalize-><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-><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> </div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  input-><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>  normalize-><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> </div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <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>  <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> </div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  std::vector<armnn::BackendId> 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>  <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">armnn::Compute::GpuAcc</a>,</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a> };</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span> </div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">armnn::IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">armnn::Optimize</a>(*net, backends, runtime->GetDeviceSpec());</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  BOOST_REQUIRE(optNet);</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> </div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>&& layer : static_cast<armnn::OptimizedNetwork*>(optNet.get())->GetGraph())</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  {</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <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>  <span class="comment">// the other layers are supported by CpuRef.</span></div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <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>  <span class="comment">// the other layers are supported by CpuRef.</span></div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <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> <span class="preprocessor">#if defined(ARMCOMPUTENEON_ENABLED)</span></div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keywordflow">if</span> (layer->GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a> || layer->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>  {</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer->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>  }</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer->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>  {</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer->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>  }</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="preprocessor">#elif defined(ARMCOMPUTECL_ENABLED)</span></div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="keywordflow">if</span> (layer->GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4a324118a6721dd6b8a9b9f4e327df2bf5">armnn::LayerType::Input</a> || layer->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>  {</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer->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>  }</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (layer->GetType() == <a class="code" href="namespacearmnn.html#a56943a0946e5f15e5e58054b8e7a04a4aac61f2e17250a818dee4d12b112aa88f">armnn::LayerType::Normalization</a>)</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  {</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer->GetBackendId() == <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a>);</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  }</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(layer->GetBackendId() == <a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aea83c2c4e9b658ccafbcbe6309c5d84c64">armnn::Compute::CpuRef</a>);</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  }</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> }</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> </div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> <a class="code" href="_profiler_tests_8cpp.html#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="ttc" id="namespacearmnn_html_ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360"><div class="ttname"><a href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeaec0fc0100c4fc1ce4eea230c3dc10360">armnn::Compute::Undefined</a></div></div>
+<div class="ttc" id="classarmnn_1_1_i_connectable_layer_html_a6ec9e0eb66d7d6a01240492a0b18104c"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">armnn::IConnectableLayer::GetInputSlot</a></div><div class="ttdeci">virtual const IInputSlot & GetInputSlot(unsigned int index) const =0</div></div>
+<div class="ttc" id="structarmnn_1_1_normalization_descriptor_html"><div class="ttname"><a href="structarmnn_1_1_normalization_descriptor.html">armnn::NormalizationDescriptor</a></div><div class="ttdoc">A NormalizationDescriptor for the NormalizationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00551">Descriptors.hpp:551</a></div></div>
+<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 &network, const std::vector< BackendId > &backendPreferences, const IDeviceSpec &deviceSpec, const OptimizerOptions &options=OptimizerOptions(), Optional< std::vector< std::string > &> 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 &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< INetwork, void(*)(INetwork *network)> 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 &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< IOptimizedNetwork, void(*)(IOptimizedNetwork *network)> 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 &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< IRuntime, void(*)(IRuntime *runtime)> 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 & GetOutputSlot(unsigned int index) const =0</div></div>
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