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<a href="_log_softmax_end_to_end_test_impl_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 © 2019 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> <span class="preprocessor">#include "<a class="code" href="_end_to_end_test_impl_8hpp.html">EndToEndTestImpl.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_log_softmax_end_to_end_test_impl_8hpp.html">LogSoftmaxEndToEndTestImpl.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_i_network_8hpp.html">armnn/INetwork.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_test_utils_8hpp.html">test/TestUtils.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <boost/test/unit_test.hpp></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="keyword">namespace </span>{</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="keyword">template</span> <<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a> CreateLogSoftmaxNetwork(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a>& inputShape,</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a>& outputShape,</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> beta,</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> axis,</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keyword">const</span> int32_t qOffset = 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="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="comment">// Builds up the structure of the network.</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <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="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_info.html">TensorInfo</a> inputTensorInfo(inputShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>, qScale, qOffset);</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  <a class="code" href="structarmnn_1_1_softmax_descriptor.html">LogSoftmaxDescriptor</a> logSoftmaxDesc;</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  logSoftmaxDesc.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">m_Beta</a> = beta;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  logSoftmaxDesc.<a class="code" href="structarmnn_1_1_softmax_descriptor.html#a214c3636fdf0ea5bac8edb42d0e6c7f0">m_Axis</a> = axis;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* logSoftmax = net->AddLogSoftmaxLayer(logSoftmaxDesc, <span class="stringliteral">"Log_Softmax"</span>);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* input = net->AddInputLayer(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, logSoftmax, inputTensorInfo, 0, 0);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputTensorInfo(outputShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>, qScale, qOffset);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* output = net->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(logSoftmax, output, outputTensorInfo, 0, 0);</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="keywordflow">return</span> net;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> }</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="keywordtype">void</span> LogSoftmaxEndToEnd(<span class="keyword">const</span> std::vector<armnn::BackendId>& backends,</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& inputTensorInfo,</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>& outputTensorInfo,</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  std::vector<float>& inputData,</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  std::vector<float>& expectedOutputData,</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> beta,</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> axis)</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> {</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// Builds up the structure of the network</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net = CreateLogSoftmaxNetwork<DataType::Float32>(inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>(),</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  beta,</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  axis);</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>  BOOST_TEST_CHECKPOINT(<span class="stringliteral">"Create a network"</span>);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  std::map<int, std::vector<float>> inputTensorData = { {0, inputData} };</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  std::map<int, std::vector<float>> expectedOutputTensorData = { {0, expectedOutputData} };</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> </div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  EndToEndLayerTestImpl<DataType::Float32, DataType::Float32>(move(net),</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  inputTensorData,</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  expectedOutputTensorData,</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  backends);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> }</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> } <span class="comment">// anonymous namespace</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"><a class="line" href="_log_softmax_end_to_end_test_impl_8cpp.html#ae25266b3210c32d9e1a665b6d59a4c78"> 76</a></span> <span class="keywordtype">void</span> <a class="code" href="_log_softmax_end_to_end_test_impl_8cpp.html#ae25266b3210c32d9e1a665b6d59a4c78">LogSoftmaxEndToEndTest</a>(<span class="keyword">const</span> std::vector<armnn::BackendId>& <a class="code" href="_cl_end_to_end_tests_8cpp.html#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a>)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</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>  <span class="keyword">const</span> <span class="keywordtype">float</span> beta = 10.0f; <span class="comment">// non-default beta</span></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> axis = 3; <span class="comment">// positive axis</span></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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> inputShape{1, 1, 2, 4};</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> inputTensorInfo(inputShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</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>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a> outputShape{1, 1, 2, 4};</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a> outputTensorInfo(outputShape, <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  std::vector<float> inputData = std::vector<float>({</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  0.0f, -0.6f, 0.2f, 0.4f,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  0.3f, -0.2f, 1.0f, 0.1f</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> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  std::vector<float> expectedOutputData = std::vector<float>({</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  -4.14297f, -10.14297f, -2.14297f, -0.14297f,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  -7.00104f, -12.00104f, -0.00104087f, -9.00104f</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> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  LogSoftmaxEndToEnd(defaultBackends,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  inputTensorInfo,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  outputTensorInfo,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  inputData,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  expectedOutputData,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  beta,</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  axis);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> }</div><div class="ttc" id="_end_to_end_test_impl_8hpp_html"><div class="ttname"><a href="_end_to_end_test_impl_8hpp.html">EndToEndTestImpl.hpp</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="_log_softmax_end_to_end_test_impl_8cpp_html_ae25266b3210c32d9e1a665b6d59a4c78"><div class="ttname"><a href="_log_softmax_end_to_end_test_impl_8cpp.html#ae25266b3210c32d9e1a665b6d59a4c78">LogSoftmaxEndToEndTest</a></div><div class="ttdeci">void LogSoftmaxEndToEndTest(const std::vector< armnn::BackendId > &defaultBackends)</div><div class="ttdef"><b>Definition:</b> <a href="_log_softmax_end_to_end_test_impl_8cpp_source.html#l00076">LogSoftmaxEndToEndTestImpl.cpp:76</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="structarmnn_1_1_softmax_descriptor_html_a8275d51ef9a584feb95726ea0522f6e5"><div class="ttname"><a href="structarmnn_1_1_softmax_descriptor.html#a8275d51ef9a584feb95726ea0522f6e5">armnn::SoftmaxDescriptor::m_Beta</a></div><div class="ttdeci">float m_Beta</div><div class="ttdoc">Exponentiation value. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00136">Descriptors.hpp:136</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="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></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>
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<div class="ttc" id="_test_utils_8cpp_html_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.html#l00012">TestUtils.cpp:12</a></div></div>
<div class="ttc" id="namespacearmnn_html_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.html#l00032">Types.hpp:32</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>
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<div class="ttc" id="_log_softmax_end_to_end_test_impl_8hpp_html"><div class="ttname"><a href="_log_softmax_end_to_end_test_impl_8hpp.html">LogSoftmaxEndToEndTestImpl.hpp</a></div></div>
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<div class="ttc" id="structarmnn_1_1_softmax_descriptor_html_a214c3636fdf0ea5bac8edb42d0e6c7f0"><div class="ttname"><a href="structarmnn_1_1_softmax_descriptor.html#a214c3636fdf0ea5bac8edb42d0e6c7f0">armnn::SoftmaxDescriptor::m_Axis</a></div><div class="ttdeci">int m_Axis</div><div class="ttdoc">Scalar, defaulted to the last index (-1), specifying the dimension the activation will be performed o...</div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.html#l00138">Descriptors.hpp:138</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00088">Tensor.hpp:88</a></div></div>
<div class="ttc" id="_cl_end_to_end_tests_8cpp_html_ab59caffe2ee6be46c08766c055420f17"><div class="ttname"><a href="_cl_end_to_end_tests_8cpp.html#ab59caffe2ee6be46c08766c055420f17">defaultBackends</a></div><div class="ttdeci">std::vector< armnn::BackendId > defaultBackends</div><div class="ttdef"><b>Definition:</b> <a href="_cl_end_to_end_tests_8cpp_source.html#l00025">ClEndToEndTests.cpp:25</a></div></div>
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