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+<a href="_fp16_support_test_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_descriptors_8hpp.html">armnn/Descriptors.hpp</a>&gt;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_i_runtime_8hpp.html">armnn/IRuntime.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="_i_network_8hpp.html">armnn/INetwork.hpp</a>&gt;</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_half_8hpp.html">Half.hpp</a>&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;</div><div class="line"><a name="l00011"></a><span class="lineno">   11</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="l00012"></a><span class="lineno">   12</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_optimizer_8hpp.html">Optimizer.hpp</a>&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_cpu_tensor_handle_8hpp.html">backendsCommon/CpuTensorHandle.hpp</a>&gt;</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;</div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="preprocessor">#include &lt;boost/core/ignore_unused.hpp&gt;</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="preprocessor">#include &lt;boost/test/unit_test.hpp&gt;</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;</div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="preprocessor">#include &lt;set&gt;</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;</div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<a class="code" href="_output_shape_of_squeeze_8cpp.html#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(Fp16Support)</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;</div><div class="line"><a name="l00024"></a><span class="lineno"><a class="line" href="_fp16_support_test_8cpp.html#a6aab4e0ffa70a022cce19a8e50fca1b5">   24</a></span>&#160;<a class="code" href="namespacearmnn.html#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(Fp16DataTypeSupport)</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;{</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;    <a class="code" href="classarmnn_1_1_graph.html">Graph</a> graph;</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;</div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> inputLayer1 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(1, <span class="stringliteral">&quot;input1&quot;</span>);</div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> inputLayer2 = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.html">InputLayer</a>&gt;(2, <span class="stringliteral">&quot;input2&quot;</span>);</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;</div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> additionLayer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_addition_layer.html">AdditionLayer</a>&gt;(<span class="stringliteral">&quot;addition&quot;</span>);</div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;    <a class="code" href="classarmnn_1_1_layer.html">Layer</a>* <span class="keyword">const</span> outputLayer = graph.<a class="code" href="classarmnn_1_1_graph.html#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.html">armnn::OutputLayer</a>&gt;(0, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;    <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> fp16TensorInfo({1, 2, 3, 5}, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">Connect</a>(additionLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    inputLayer2-&gt;GetOutputSlot(0).Connect(additionLayer-&gt;GetInputSlot(1));</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    additionLayer-&gt;GetOutputSlot(0).Connect(outputLayer-&gt;GetInputSlot(0));</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    inputLayer1-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.html#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(fp16TensorInfo);</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    inputLayer2-&gt;GetOutputSlot().SetTensorInfo(fp16TensorInfo);</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    additionLayer-&gt;GetOutputSlot().SetTensorInfo(fp16TensorInfo);</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(inputLayer1-&gt;<a class="code" href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(inputLayer2-&gt;GetOutputSlot(0).GetTensorInfo().GetDataType() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(additionLayer-&gt;GetOutputSlot(0).GetTensorInfo().GetDataType() == <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;}</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"><a class="line" href="_fp16_support_test_8cpp.html#a9cd77c53f585802ea8f9c1afedb641bf">   48</a></span>&#160;<a class="code" href="namespacearmnn.html#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(Fp16AdditionTest)</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;{</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;   <span class="keyword">using namespace </span>half_float::literal;</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;   <span class="comment">// Create runtime in which test will run</span></div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;   <a class="code" href="structarmnn_1_1_i_runtime_1_1_creation_options.html">IRuntime::CreationOptions</a> <a class="code" href="_file_only_profiling_decorator_tests_8cpp.html#a6560146509197f3e197d8d36f76c1347">options</a>;</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;   <a class="code" href="namespacearmnn.html#a150468a02bd7b2d2d061c4aaaee939f0">IRuntimePtr</a> runtime(<a class="code" href="classarmnn_1_1_i_runtime.html#ad44ecd3700748dc30dc4bbe34ba5bde7">IRuntime::Create</a>(options));</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;   <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;   <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.html#a706f7345af3f18f4b16e226a672214c6">INetwork::Create</a>());</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;   <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* inputLayer1 = net-&gt;AddInputLayer(0);</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;   <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* inputLayer2 = net-&gt;AddInputLayer(1);</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;   <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* additionLayer = net-&gt;AddAdditionLayer();</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;   <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* outputLayer = net-&gt;AddOutputLayer(0);</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;   inputLayer1-&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>(additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;   inputLayer2-&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>(additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(1));</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;   additionLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a80ac4eda2e7f2757ec9dd96fc96dbd16">GetOutputSlot</a>(0).<a class="code" href="classarmnn_1_1_i_output_slot.html#ac1835f8756a9f03c02fcf9664e3a0fce">Connect</a>(outputLayer-&gt;<a class="code" href="classarmnn_1_1_i_connectable_layer.html#a6ec9e0eb66d7d6a01240492a0b18104c">GetInputSlot</a>(0));</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;   <span class="comment">//change to float16</span></div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;   <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> fp16TensorInfo(<a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>({4}), <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>);</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;   inputLayer1-&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>(fp16TensorInfo);</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;   inputLayer2-&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>(fp16TensorInfo);</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;   additionLayer-&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>(fp16TensorInfo);</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;   <span class="comment">// optimize the network</span></div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;   std::vector&lt;BackendId&gt; backends = {<a class="code" href="namespacearmnn.html#ae2f04a162585c0a5222a537efd5456aeafaa4524e3df19ada32643ce9a222362b">Compute::GpuAcc</a>};</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;   <a class="code" href="namespacearmnn.html#a674efcf6cbdb9e831d653ff0e821fb38">IOptimizedNetworkPtr</a> optNet = <a class="code" href="namespacearmnn.html#a82e98ef05fd67036d1195ba17174d685">Optimize</a>(*net, backends, runtime-&gt;GetDeviceSpec());</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;   <span class="comment">// Loads it into the runtime.</span></div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;   <a class="code" href="namespacearmnn.html#a83015160d8c67d5d77735eb0d4033d9a">NetworkId</a> netId;</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160; 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  std::vector&lt;Half&gt; outputData(input1Data.size());</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;   <a class="code" href="namespacearmnn.html#a8f091a512915d1cb29a4ebf13dfc53ea">OutputTensors</a> outputTensors</div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;   {</div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;       {0,<a class="code" href="classarmnn_1_1_tensor.html">Tensor</a>(runtime-&gt;GetOutputTensorInfo(netId, 0), outputData.data())}</div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;   };</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;   <span class="comment">// Does the inference.</span></div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;   runtime-&gt;EnqueueWorkload(netId, inputTensors, outputTensors);</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160; 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+<div class="ttc" id="_optimizer_8hpp_html"><div class="ttname"><a href="_optimizer_8hpp.html">Optimizer.hpp</a></div></div>
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+<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>
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+<div class="ttc" id="namespacearmnn_html_a10d15f3df1ab52b3b915a4be1dbf386b"><div class="ttname"><a href="namespacearmnn.html#a10d15f3df1ab52b3b915a4be1dbf386b">armnn::BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.html#l00170">ConstTensorLayerVisitor.cpp:170</a></div></div>
+<div class="ttc" id="_i_runtime_8hpp_html"><div class="ttname"><a href="_i_runtime_8hpp.html">IRuntime.hpp</a></div></div>
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+<div class="ttc" id="classarmnn_1_1_output_slot_html_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#adcfb97035799ea4c043f9ef370714815">armnn::OutputSlot::Connect</a></div><div class="ttdeci">int Connect(InputSlot &amp;destination)</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00079">Layer.cpp:79</a></div></div>
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+<div class="ttc" id="_descriptors_8hpp_html"><div class="ttname"><a href="_descriptors_8hpp.html">Descriptors.hpp</a></div></div>
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+<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>
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+<div class="ttc" id="_graph_8hpp_html"><div class="ttname"><a href="_graph_8hpp.html">Graph.hpp</a></div></div>
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+<div class="ttc" id="classarmnn_1_1_output_slot_html_ada2ad7d1caeeb4ef6195c8925fad6a65"><div class="ttname"><a href="classarmnn_1_1_output_slot.html#ada2ad7d1caeeb4ef6195c8925fad6a65">armnn::OutputSlot::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo &amp; GetTensorInfo() const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.html#l00063">Layer.cpp:63</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_html_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.html#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.html#l00312">Layer.hpp:312</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>
+<div class="ttc" id="_i_network_8hpp_html"><div class="ttname"><a href="_i_network_8hpp.html">INetwork.hpp</a></div></div>
+<div class="ttc" id="_half_8hpp_html"><div class="ttname"><a href="_half_8hpp.html">Half.hpp</a></div></div>
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+    <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.html">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.html">backends</a></li><li class="navelem"><a class="el" href="dir_1ad86c6d39ab715a831555571b9e98a5.html">cl</a></li><li class="navelem"><a class="el" href="dir_02bab2737bbb2fb3882a0be567244fbf.html">test</a></li><li class="navelem"><a class="el" href="_fp16_support_test_8cpp.html">Fp16SupportTest.cpp</a></li>
+    <li class="footer">Generated on Fri Mar 13 2020 16:06:57 for ArmNN by
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