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+<a href="_convert_constants_b_float_tests_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment">// Copyright © 2020 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="preprocessor">#include &quot;../TestUtils.hpp&quot;</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;</div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_b_float16_8hpp.xhtml">BFloat16.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="_optimizer_8hpp.xhtml">Optimizer.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;boost/test/unit_test.hpp&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;</div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</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;<a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(<a class="code" href="classarmnn_1_1_optimizer.xhtml">Optimizer</a>)</div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearmnn_1_1optimizations.xhtml">armnn::optimizations</a>;</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"><a class="line" href="_convert_constants_b_float_tests_8cpp.xhtml#abd670197941421c435afaf22189735d0">   18</a></span>&#160;<a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ConvertConstantsFloatToBFloatTest)</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;    <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;</div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 1, 1, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>);</div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;</div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;    <span class="comment">// Create const tensor from fp32 data</span></div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dims[] = { 4, 2, 1, 1 };</div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;    std::vector&lt;float&gt; floatWeights{ 0.0f, -1.0f,</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;                                     3.8f, <span class="comment">// 0x40733333 Round down</span></div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;                                     3.1055E+29f, <span class="comment">// 0x707ADC3C Round up</span></div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;                                     9.149516E-10f, <span class="comment">// 0x307B7FFF Round down</span></div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;                                    -3.8f, <span class="comment">// 0xC0733333 Round down</span></div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;                                    -3.1055E+29f, <span class="comment">// 0xF07ADC3C Round up</span></div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;                                    -9.149516E-10f <span class="comment">// 0xB07B7FFF Round down</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_const_tensor.xhtml">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, dims, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>), floatWeights);</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;    <span class="comment">// Create simple test network</span></div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;    <span class="keyword">auto</span> input = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;    <span class="keyword">auto</span> fc      = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml">armnn::FullyConnectedLayer</a>&gt;(<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">armnn::FullyConnectedDescriptor</a>(), <span class="stringliteral">&quot;fc&quot;</span>);</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    fc-&gt;<a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique&lt;armnn::ScopedCpuTensorHandle&gt;(weights);</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    fc-&gt;GetOutputSlot().SetTensorInfo(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    <span class="keyword">auto</span> output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.xhtml">armnn::OutputLayer</a>&gt;(1, <span class="stringliteral">&quot;output&quot;</span>);</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;    <span class="comment">// Connect up the layers</span></div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(fc-&gt;GetInputSlot(0));</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;    fc-&gt;GetOutputSlot().Connect(output-&gt;GetInputSlot(0));</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="comment">// Check tensor data type before conversion</span></div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(fc-&gt;m_Weight-&gt;GetTensorInfo().GetDataType() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;</div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;    <span class="comment">// Run the optimizer</span></div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    <a class="code" href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a>(graph, <a class="code" href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a>(<a class="code" href="namespacearmnn_1_1optimizations.xhtml#aee1a3b292f726335f0a3998b51101aef">ConvertConstantsFloatToBFloat</a>()));</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <span class="comment">// Check tensor data type after conversion</span></div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(fc-&gt;m_Weight-&gt;GetTensorInfo().GetDataType() == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>);</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    <span class="comment">// Check whether data matches expected Bf16 data</span></div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>* data = fc-&gt;m_Weight-&gt;GetTensor&lt;<a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>&gt;();</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[0] == <a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>(0.0f));</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[1] == <a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>(-1.0f));</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[2] == <a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>(3.796875f)); <span class="comment">// 0x4073</span></div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[3] == <a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>(3.1072295E29f)); <span class="comment">// 0x707B</span></div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[4] == <a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>(9.131327E-10f)); <span class="comment">// 0x307B</span></div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[5] == <a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>(-3.796875f)); <span class="comment">// 0xC073</span></div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[6] == <a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>(-3.1072295E29f)); <span class="comment">// 0xF07B</span></div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[7] == <a class="code" href="classarmnn_1_1_b_float16.xhtml">BFloat16</a>(-9.131327E-10f)); <span class="comment">// 0xB07B</span></div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;}</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno"><a class="line" href="_convert_constants_b_float_tests_8cpp.xhtml#a3118a734ad26d2585544508a2c3c7418">   71</a></span>&#160;<a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(ConvertConstantsBFloatToFloatTest)</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;    <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>({ 1, 1, 1, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</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">// Create the BFloat16 precision input data</span></div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;    <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dims[] = { 4, 2, 1, 1 };</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;    std::vector&lt;float&gt; convWeightsData{ 0.f, -1.f,</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;                                        3.796875f, <span class="comment">// 0x4073</span></div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;                                        3.1072295E29f, <span class="comment">// 0x707B</span></div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;                                        9.131327E-10f, <span class="comment">// 0x307B</span></div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;                                       -3.796875f, <span class="comment">// 0xC073</span></div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;                                       -3.1072295E29f, <span class="comment">// 0xF07B</span></div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;                                       -9.131327E-10f <span class="comment">// 0xB07B</span></div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;                                       };</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    std::vector&lt;uint16_t&gt; bfWeights(8);</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    <a class="code" href="classarmnn_utils_1_1_floating_point_converter.xhtml#ac7add3b3d40fbaab5e514c756a953d78">armnnUtils::FloatingPointConverter::ConvertFloat32ToBFloat16</a>(convWeightsData.data(), convWeightsData.size(),</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;                                                                 bfWeights.data());</div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;    <a class="code" href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a> weights(<a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, dims, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6acdb56b2d2f73c26480207524f2dbe0af">armnn::DataType::BFloat16</a>), bfWeights);</div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;</div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;    <span class="comment">//Create the simple test network</span></div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    <span class="keyword">auto</span> input = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a>&gt;(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">SetTensorInfo</a>(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;</div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    <span class="keyword">auto</span> fc      = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml">armnn::FullyConnectedLayer</a>&gt;(<a class="code" href="structarmnn_1_1_fully_connected_descriptor.xhtml">armnn::FullyConnectedDescriptor</a>(), <span class="stringliteral">&quot;fc&quot;</span>);</div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;    fc-&gt;<a class="code" href="classarmnn_1_1_fully_connected_layer.xhtml#a2664044e28e69309ea08ef385fe53903">m_Weight</a> = std::make_unique&lt;armnn::ScopedCpuTensorHandle&gt;(weights);</div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    fc-&gt;GetOutputSlot().SetTensorInfo(<a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>);</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;    <span class="keyword">auto</span> output = graph.<a class="code" href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">AddLayer</a>&lt;<a class="code" href="classarmnn_1_1_output_layer.xhtml">armnn::OutputLayer</a>&gt;(1, <span class="stringliteral">&quot;output&quot;</span>);</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;    <span class="comment">//Connect up the layers</span></div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;    input-&gt;<a class="code" href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">GetOutputSlot</a>().<a class="code" href="classarmnn_1_1_output_slot.xhtml#adcfb97035799ea4c043f9ef370714815">Connect</a>(fc-&gt;GetInputSlot(0));</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;    fc-&gt;GetOutputSlot().Connect(output-&gt;GetInputSlot(0));</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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   <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[0] == 0.0f);</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[1] == -1.0f);</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[2] == 3.796875f);</div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[3] == 3.1072295E29f);</div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    <a class="code" href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a>(data[4] == 9.131327E-10f);</div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160; 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+<div class="ttc" id="namespacearmnn_xhtml_aa7427025a851113a492de0b68b23d22a"><div class="ttname"><a href="namespacearmnn.xhtml#aa7427025a851113a492de0b68b23d22a">armnn::MakeOptimizations</a></div><div class="ttdeci">Optimizer::Optimizations MakeOptimizations(Args &amp;&amp;... args)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8hpp_source.xhtml#l00043">Optimizer.hpp:43</a></div></div>
+<div class="ttc" id="classarmnn_1_1_fully_connected_layer_xhtml_a2664044e28e69309ea08ef385fe53903"><div class="ttname"><a href="classarmnn_1_1_fully_connected_layer.xhtml#a2664044e28e69309ea08ef385fe53903">armnn::FullyConnectedLayer::m_Weight</a></div><div class="ttdeci">std::unique_ptr&lt; ScopedCpuTensorHandle &gt; m_Weight</div><div class="ttdoc">A unique pointer to store Weight values. </div><div class="ttdef"><b>Definition:</b> <a href="_fully_connected_layer_8hpp_source.xhtml#l00019">FullyConnectedLayer.hpp:19</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
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+<div class="ttc" id="classarmnn_1_1_graph_xhtml_a7563c5b899e7d0ada08fd0fdb202f205"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml#a7563c5b899e7d0ada08fd0fdb202f205">armnn::Graph::AddLayer</a></div><div class="ttdeci">LayerT * AddLayer(Args &amp;&amp;... args)</div><div class="ttdoc">Adds a new layer, of type LayerType, to the graph constructed with the arguments passed. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00398">Graph.hpp:398</a></div></div>
+<div class="ttc" id="classarmnn_1_1_b_float16_xhtml"><div class="ttname"><a href="classarmnn_1_1_b_float16.xhtml">armnn::BFloat16</a></div><div class="ttdef"><b>Definition:</b> <a href="_b_float16_8hpp_source.xhtml#l00014">BFloat16.hpp:14</a></div></div>
+<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_adcfb97035799ea4c043f9ef370714815"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#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.xhtml#l00079">Layer.cpp:79</a></div></div>
+<div class="ttc" id="classarmnn_1_1_optimizer_xhtml_a1f48ba622b76ea04d15c9b62f642bf08"><div class="ttname"><a href="classarmnn_1_1_optimizer.xhtml#a1f48ba622b76ea04d15c9b62f642bf08">armnn::Optimizer::Pass</a></div><div class="ttdeci">static void Pass(Graph &amp;graph, const Optimizations &amp;optimizations)</div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8cpp_source.xhtml#l00016">Optimizer.cpp:16</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div>
+<div class="ttc" id="_file_only_profiling_decorator_tests_8cpp_xhtml_a0c262ba6f6c189a2d092d127c1b7627b"><div class="ttname"><a href="_file_only_profiling_decorator_tests_8cpp.xhtml#a0c262ba6f6c189a2d092d127c1b7627b">BOOST_CHECK</a></div><div class="ttdeci">BOOST_CHECK(profilingService.GetCurrentState()==ProfilingState::WaitingForAck)</div></div>
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+<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_aee1a3b292f726335f0a3998b51101aef"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#aee1a3b292f726335f0a3998b51101aef">armnn::optimizations::ConvertConstantsFloatToBFloat</a></div><div class="ttdeci">ConvertConstants&lt; Float32ToBFloat16, IsBFloat16Layer &gt; ConvertConstantsFloatToBFloat</div><div class="ttdef"><b>Definition:</b> <a href="_convert_constants_8hpp_source.xhtml#l00152">ConvertConstants.hpp:152</a></div></div>
+<div class="ttc" id="classarmnn_1_1_fully_connected_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_fully_connected_layer.xhtml">armnn::FullyConnectedLayer</a></div><div class="ttdoc">This layer represents a fully connected operation. </div><div class="ttdef"><b>Definition:</b> <a href="_fully_connected_layer_8hpp_source.xhtml#l00015">FullyConnectedLayer.hpp:15</a></div></div>
+<div class="ttc" id="namespacearmnn_1_1optimizations_xhtml_ae8c1ba6bb2208ba3a0e17ad9ba5791ad"><div class="ttname"><a href="namespacearmnn_1_1optimizations.xhtml#ae8c1ba6bb2208ba3a0e17ad9ba5791ad">armnn::optimizations::ConvertConstantsBFloatToFloat</a></div><div class="ttdeci">ConvertConstants&lt; BFloat16ToFloat32, IsFloat32Layer &gt; ConvertConstantsBFloatToFloat</div><div class="ttdef"><b>Definition:</b> <a href="_convert_constants_8hpp_source.xhtml#l00151">ConvertConstants.hpp:151</a></div></div>
+<div class="ttc" id="structarmnn_1_1_fully_connected_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fully_connected_descriptor.xhtml">armnn::FullyConnectedDescriptor</a></div><div class="ttdoc">A FullyConnectedDescriptor for the FullyConnectedLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00381">Descriptors.hpp:381</a></div></div>
+<div class="ttc" id="classarmnn_1_1_const_tensor_xhtml"><div class="ttname"><a href="classarmnn_1_1_const_tensor.xhtml">armnn::ConstTensor</a></div><div class="ttdoc">A tensor defined by a TensorInfo (shape and data type) and an immutable backing store. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00199">Tensor.hpp:199</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a10d15f3df1ab52b3b915a4be1dbf386b"><div class="ttname"><a href="namespacearmnn.xhtml#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.xhtml#l00268">ConstTensorLayerVisitor.cpp:268</a></div></div>
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+<div class="ttc" id="classarmnn_1_1_input_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_input_layer.xhtml">armnn::InputLayer</a></div><div class="ttdoc">A layer user-provided data can be bound to (e.g. inputs, outputs). </div><div class="ttdef"><b>Definition:</b> <a href="_input_layer_8hpp_source.xhtml#l00013">InputLayer.hpp:13</a></div></div>
+<div class="ttc" id="classarmnn_1_1_output_slot_xhtml_a7e5c5771d741dd5473989047a9314728"><div class="ttname"><a href="classarmnn_1_1_output_slot.xhtml#a7e5c5771d741dd5473989047a9314728">armnn::OutputSlot::SetTensorInfo</a></div><div class="ttdeci">void SetTensorInfo(const TensorInfo &amp;tensorInfo) override</div><div class="ttdef"><b>Definition:</b> <a href="_layer_8cpp_source.xhtml#l00058">Layer.cpp:58</a></div></div>
+<div class="ttc" id="classarmnn_1_1_layer_xhtml_a0e36688a43c35668d8db5257274c68fe"><div class="ttname"><a href="classarmnn_1_1_layer.xhtml#a0e36688a43c35668d8db5257274c68fe">armnn::Layer::GetOutputSlot</a></div><div class="ttdeci">const OutputSlot &amp; GetOutputSlot(unsigned int index=0) const override</div><div class="ttdoc">Get the const output slot handle by slot index. </div><div class="ttdef"><b>Definition:</b> <a href="_layer_8hpp_source.xhtml#l00312">Layer.hpp:312</a></div></div>
+<div class="ttc" id="_b_float16_8hpp_xhtml"><div class="ttname"><a href="_b_float16_8hpp.xhtml">BFloat16.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
+<div class="ttc" id="classarmnn_1_1_optimizer_xhtml"><div class="ttname"><a href="classarmnn_1_1_optimizer.xhtml">armnn::Optimizer</a></div><div class="ttdef"><b>Definition:</b> <a href="_optimizer_8hpp_source.xhtml#l00014">Optimizer.hpp:14</a></div></div>
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+    <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_e0a84d05c80a2ef4231141dcbbeac5c8.xhtml">armnn</a></li><li class="navelem"><a class="el" href="dir_9d86fd1fbecbedf5bdb69c7e7235fe5f.xhtml">test</a></li><li class="navelem"><a class="el" href="dir_f1cd0e6da811a659c139424442adfb5f.xhtml">optimizations</a></li><li class="navelem"><a class="el" href="_convert_constants_b_float_tests_8cpp.xhtml">ConvertConstantsBFloatTests.cpp</a></li>
+    <li class="footer">Generated on Fri May 29 2020 10:20:41 for ArmNN by
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