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<div class="title">ActivationTestImpl.cpp</div> </div>
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<a href="_activation_test_impl_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> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd and Contributors. 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="_activation_test_impl_8hpp.xhtml">ActivationTestImpl.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_quantize_helper_8hpp.xhtml">QuantizeHelper.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_resolve_type_8hpp.xhtml">ResolveType.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="_activation_fixture_8hpp.xhtml">backendsCommon/test/ActivationFixture.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_tensor_copy_utils_8hpp.xhtml">backendsCommon/test/TensorCopyUtils.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_workload_test_utils_8hpp.xhtml">backendsCommon/test/WorkloadTestUtils.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_ref_workload_factory_helper_8hpp.xhtml">reference/test/RefWorkloadFactoryHelper.hpp</a>></span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <<a class="code" href="_numeric_cast_8hpp.xhtml">armnn/utility/NumericCast.hpp</a>></span></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> <span class="preprocessor">#include <<a class="code" href="_tensor_helpers_8hpp.xhtml">test/TensorHelpers.hpp</a>></span></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="preprocessor">#include <boost/multi_array.hpp></span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> </div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="preprocessor">#include <algorithm></span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> </div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00025"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a17ab0fa28201a48e6ed1f45eba2aa901"> 25</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a17ab0fa28201a48e6ed1f45eba2aa901">BoundedReLuTestCommon</a>(</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keywordtype">float</span> upperBound,</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <span class="keywordtype">float</span> lowerBound,</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <span class="keywordtype">float</span> inputScale,</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  int32_t inputOffset,</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keywordtype">float</span> outputScale,</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  int32_t outputOffset,</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <span class="keyword">const</span> std::vector<T>& inputData,</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">const</span> std::vector<T>& outputExpectedData,</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels,</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize)</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = inputWidth;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = inputHeight;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = inputChannels;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputBatchSize = inputBatchSize;</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>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, ArmnnType);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, ArmnnType);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> </div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">if</span>(armnn::IsQuantizedType<T>())</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  {</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(inputScale);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  inputTensorInfo.SetQuantizationOffset(inputOffset);</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>  outputTensorInfo.SetQuantizationScale(outputScale);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  outputTensorInfo.SetQuantizationOffset(outputOffset);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</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>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> result(inputTensorInfo);</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>  <span class="keyword">auto</span> input = MakeTensor<T, 4>(inputTensorInfo, inputData);</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::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</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>  <span class="comment">// Setup bounded ReLu.</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="structarmnn_1_1_activation_queue_descriptor.xhtml">armnn::ActivationQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get());</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>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a>;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a017b2990003a014234f13e999dc7c689">m_A</a> = upperBound;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a28c4c9cb15f6be3499abbc46b356060b">m_B</a> = lowerBound;</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>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5">CreateActivation</a>(descriptor, workloadInfo);</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>  inputHandle->Allocate();</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  outputHandle->Allocate();</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="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &input[0][0][0][0]);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  workload->Execute();</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&result.<a class="code" href="struct_layer_test_result.xhtml#ac9d44d346bb7c89f7a7aa31d2bee947f">output</a>[0][0][0][0], outputHandle.get());</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>  result.<a class="code" href="struct_layer_test_result.xhtml#a73610ea6c776cc66e5a78dd842a39b8b">outputExpected</a> = MakeTensor<T, 4>(outputTensorInfo, outputExpectedData);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordflow">return</span> result;</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"><a class="line" href="_activation_test_impl_8hpp.xhtml#ab265bbfc98785482a41bb9780b6858d0"> 94</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#ab265bbfc98785482a41bb9780b6858d0">BoundedReLuUpperAndLowerBoundTest</a>(</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 4u;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 5u;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 1u;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize = 1;</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>  std::vector<float> input = std::vector<float>{</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  -2.0f, 0.1f, 0.5f, 1.25f,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  0.786f, 0.9875f, -1.5f, 0.384f,</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  1.0001f, 3.5f, 7.5f, 0.896f,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  2.126f, 2.0f, 0.3f, 0.15f,</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  0.999f, 1.2f, 0.89f, 6.1f,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  };</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="comment">// Calculated manually.</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  std::vector<float> output = std::vector<float>{</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  -1.0f, 0.1f, 0.5f, 1.0f,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  0.786f, 0.9875f, -1.0f, 0.384f,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  1.0f, 1.0f, 1.0f, 0.896f,</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  1.0f, 1.0f, 0.3f, 0.15f,</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  0.999f, 1.0f, 0.89f, 1.0f,</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  };</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keywordflow">return</span> BoundedReLuTestCommon<armnn::DataType::Float32>(</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  workloadFactory, memoryManager, tensorHandleFactory, 1.0f, -1.0f, 1.0f, 0, 1.0f, 0, input, output,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  inputWidth, inputHeight, inputChannels, inputBatchSize);</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> </div><div class="line"><a name="l00126"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a73da7517b63c3a8ea6046124c258e158"> 126</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a73da7517b63c3a8ea6046124c258e158">BoundedReLuUpperBoundOnlyTest</a>(</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 4u;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 5u;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 1u;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize = 1;</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>  std::vector<float> input = std::vector<float>{</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  -1.0f, 0.1f, 0.5f, 6.25f,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  0.786f, 5.9875f, -0.5f, 0.384f,</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  6.0001f, 3.5f, 7.5f, 0.896f,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  2.126f, 12.0f, 0.3f, 0.15f,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  0.999f, 1.2f, 0.89f, 6.1f,</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> </div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="comment">// Calculated manually.</span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  std::vector<float> output = std::vector<float>{</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  0.0f, 0.1f, 0.5f, 6.0f,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  0.786f, 5.9875f, 0.0f, 0.384f,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  6.0f, 3.5f, 6.0f, 0.896f,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  2.126f, 6.0f, 0.3f, 0.15f,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  0.999f, 1.2f, 0.89f, 6.0f,</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  };</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> </div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keywordflow">return</span> BoundedReLuTestCommon<armnn::DataType::Float32>(</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  workloadFactory, memoryManager, tensorHandleFactory, 6.0f, 0.0f, 1.0f, 0, 1.0f, 0, input, output,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  inputWidth, inputHeight, inputChannels, inputBatchSize);</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> }</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div><div class="line"><a name="l00158"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a50acd207f416e7df36c17d333b9a0801"> 158</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a50acd207f416e7df36c17d333b9a0801">BoundedReLuUint8UpperBoundOnlyTest</a>(</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> {</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 3u;</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 2u;</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 1u;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize = 1;</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> </div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  std::vector<uint8_t> input = std::vector<uint8_t>{</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  51, 124, 28,</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  251, 8, 92</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</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>  <span class="comment">// Calculated manually.</span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  std::vector<uint8_t> output = std::vector<uint8_t>{</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  0, 122, 0,</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  255, 0, 58</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  };</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <span class="keywordtype">float</span> inputScale = 12.0f / 255.0f;</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  int32_t inputOffset = 63;</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keywordtype">float</span> outputScale = 6.0f / 255.0f;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  int32_t outputOffset = 0;</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>  <span class="keywordflow">return</span> BoundedReLuTestCommon<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  workloadFactory, memoryManager, tensorHandleFactory, 6.0f, 0.0f,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  inputScale, inputOffset, outputScale, outputOffset,</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  input, output, inputWidth, inputHeight, inputChannels, inputBatchSize);</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> </div><div class="line"><a name="l00190"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#adc989d81c996f8c88a872e9de94274c8"> 190</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a6e6556796cdc26d6c2d55eab69cf6945">BoundedReLuUint8UpperAndLowerBoundTest</a>(</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> {</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 3u;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 2u;</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 1u;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize = 1;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  std::vector<uint8_t> input = std::vector<uint8_t>{</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  51, 230, 28,</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  251, 8, 92</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  };</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>  <span class="comment">// Calculated manually.</span></div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  std::vector<uint8_t> output = std::vector<uint8_t>{</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  51, 192, 32,</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  192, 32, 92</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  };</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> </div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  int32_t inputOffset = 112;</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="keywordtype">float</span> inputScale = 0.0125f;</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> </div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="keywordflow">return</span> BoundedReLuTestCommon<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  workloadFactory, memoryManager, tensorHandleFactory, 1.0f, -1.0f,</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  inputScale, inputOffset, inputScale, inputOffset, <span class="comment">// Input/output scale & offset same.</span></div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  input, output, inputWidth, inputHeight, inputChannels, inputBatchSize);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> }</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span> </div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> <span class="keyword">namespace</span></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> </div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="keyword">struct </span>BoundedReLuRandomInputTestTraits</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> {</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 31u;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 19u;</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 4u;</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize = 2;</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> </div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = inputHeight;</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = inputWidth;</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = inputChannels;</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputBatchSize = inputBatchSize;</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>  <span class="keyword">static</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> <a class="code" href="namespacearmnn.xhtml#adb77d7a922e1a8dee8490f50a5ae4bac">GetInputTensorInfo</a>()</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  {</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({ inputBatchSize, inputChannels, inputHeight, inputWidth },</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  }</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keyword">static</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> GetOutputTensorInfo()</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>  <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>({ outputBatchSize, outputChannels, outputHeight, outputWidth },</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</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> };</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> </div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> boost::multi_array<float, 4> BoundedReLuRandomInputTest(</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordtype">float</span> lowerBound,</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keywordtype">float</span> upperBound,</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keyword">const</span> <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a>& activationDescriptor)</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.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo = <a class="code" href="namespacearmnn.xhtml#adb77d7a922e1a8dee8490f50a5ae4bac">BoundedReLuRandomInputTestTraits::GetInputTensorInfo</a>();</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo = BoundedReLuRandomInputTestTraits::GetOutputTensorInfo();</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> </div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  boost::multi_array<float, 4> output(GetTensorShapeAsArray<4>(outputTensorInfo));</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> </div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="comment">// Min/max random values passed to MakeRandomTensor are purposely outside of the ReLu</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="comment">// range [lowerBound, upperBound].</span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keyword">auto</span> input = MakeRandomTensor<float, 4>(inputTensorInfo, 4605828, lowerBound - 5.0f, upperBound * 2.0f);</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> </div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> </div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="comment">// Set up bounded ReLu.</span></div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <a class="code" href="structarmnn_1_1_activation_queue_descriptor.xhtml">armnn::ActivationQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a> = activationDescriptor;</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>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5">CreateActivation</a>(descriptor, workloadInfo);</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> </div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  inputHandle->Allocate();</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  outputHandle->Allocate();</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> </div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &input[0][0][0][0]);</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> </div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  workload->Execute();</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>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keywordflow">return</span> output;</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> }</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> </div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> } <span class="comment">// namespace</span></div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> </div><div class="line"><a name="l00292"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#afabbbadee3467a572cac32e1253b073b"> 292</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#afabbbadee3467a572cac32e1253b073b">CompareBoundedReLuTest</a>(</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& refWorkloadFactory,</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& refTensorHandleFactory,</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordtype">float</span> upperBound,</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordtype">float</span> lowerBound)</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> {</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> result(BoundedReLuRandomInputTestTraits::GetOutputTensorInfo());</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> </div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <a class="code" href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a> activationDescriptor;</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  activationDescriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a>;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  activationDescriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a017b2990003a014234f13e999dc7c689">m_A</a> = upperBound;</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  activationDescriptor.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a28c4c9cb15f6be3499abbc46b356060b">m_B</a> = lowerBound;</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>  result.<a class="code" href="struct_layer_test_result.xhtml#ac9d44d346bb7c89f7a7aa31d2bee947f">output</a> = BoundedReLuRandomInputTest(</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  workloadFactory, memoryManager, tensorHandleFactory, 0.0f, upperBound, activationDescriptor);</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  result.<a class="code" href="struct_layer_test_result.xhtml#a73610ea6c776cc66e5a78dd842a39b8b">outputExpected</a> = BoundedReLuRandomInputTest(</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  refWorkloadFactory, <span class="keyword">nullptr</span>, refTensorHandleFactory, 0.0f, upperBound, activationDescriptor);</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> </div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> }</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> </div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00317"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#afc6867f503e2bdbe9d42eee7361d1f91"> 317</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T,4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#afc6867f503e2bdbe9d42eee7361d1f91">ConstantLinearActivationTestCommon</a>(</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keywordtype">float</span> qScale = 0.0f,</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  int32_t qOffset = 0)</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span> {</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 20;</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 17;</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 3;</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 5;</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> </div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = {batchSize, inputChannels, inputHeight, inputWidth};</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> </div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, shape, ArmnnType);</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, shape, ArmnnType);</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> </div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordflow">if</span>(armnn::IsQuantizedType<T>())</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  {</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  }</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span> </div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> ret(outputTensorInfo);</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span> </div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="comment">// Do linear activation that should leave the tensor unchanged.</span></div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <a class="code" href="structarmnn_1_1_activation_queue_descriptor.xhtml">armnn::ActivationQueueDescriptor</a> data;</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> info;</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a017b2990003a014234f13e999dc7c689">m_A</a> = 1.0f;</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a28c4c9cb15f6be3499abbc46b356060b">m_B</a> = 0.0f;</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b">armnn::ActivationFunction::Linear</a>;</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span> </div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5">CreateActivation</a>(data, info);</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span> </div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  inputHandle->Allocate();</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  outputHandle->Allocate();</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span> </div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  boost::multi_array<T, 4> input = MakeRandomTensor<T, 4>(inputTensorInfo, 7123561);</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &input[0][0][0][0]);</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span> </div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  workload->Execute();</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span> </div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret.<a class="code" href="struct_layer_test_result.xhtml#ac9d44d346bb7c89f7a7aa31d2bee947f">output</a>[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span> </div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="comment">// Ensure output equals input.</span></div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  ret.<a class="code" href="struct_layer_test_result.xhtml#a73610ea6c776cc66e5a78dd842a39b8b">outputExpected</a> = input;</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span> </div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span> }</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div><div class="line"><a name="l00378"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a6c39ee38ff9ba4a4d2a773cc59d874d5"> 378</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a6c39ee38ff9ba4a4d2a773cc59d874d5">ConstantLinearActivationTest</a>(</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> {</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keywordflow">return</span> ConstantLinearActivationTestCommon<armnn::DataType::Float32>(workloadFactory,</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  memoryManager,</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  tensorHandleFactory);</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span> }</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> </div><div class="line"><a name="l00388"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#ae67353055c8f500c9cf58f686b78a2e0"> 388</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#ae67353055c8f500c9cf58f686b78a2e0">ConstantLinearActivationUint8Test</a>(</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span> {</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="keywordflow">return</span> ConstantLinearActivationTestCommon<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  workloadFactory, memoryManager, tensorHandleFactory, 4.0f, 3);</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> }</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span> </div><div class="line"><a name="l00397"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a1ff5e9c94a9862b4e10cfd407edd1144"> 397</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a1ff5e9c94a9862b4e10cfd407edd1144">ConstantLinearActivationInt16Test</a>(</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> {</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keywordflow">return</span> ConstantLinearActivationTestCommon<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> }</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span> </div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00407"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a7f39f3c0b73cbfc50b914bc92f9b28aa"> 407</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a7f39f3c0b73cbfc50b914bc92f9b28aa">SimpleActivationTest</a>(</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a> activationFunction,</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <span class="keywordtype">float</span> activationParameterA,</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <span class="keywordtype">float</span> activationParameterB,</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <span class="keywordtype">float</span> scale,</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  int32_t offset,</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <span class="keyword">const</span> std::vector<float>& inputData,</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="keywordtype">float</span> outScale,</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  int32_t outOffset,</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <span class="keyword">const</span> std::vector<float>& outputExpectedData)</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span> {</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputWidth = 16u;</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputHeight = 1u;</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputChannels = 1u;</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputBatchSize = 1u;</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> </div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputWidth = inputWidth;</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputHeight = inputHeight;</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputChannels = inputChannels;</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  constexpr <span class="keyword">static</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputBatchSize = inputBatchSize;</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span> </div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({ inputBatchSize, inputChannels, inputHeight, inputWidth }, ArmnnType);</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ outputBatchSize, outputChannels, outputHeight, outputWidth }, ArmnnType);</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span> </div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <span class="keywordflow">if</span>(armnn::IsQuantizedType<T>())</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  {</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(scale);</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  inputTensorInfo.SetQuantizationOffset(offset);</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  outputTensorInfo.SetQuantizationScale(outScale);</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  outputTensorInfo.SetQuantizationOffset(outOffset);</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  }</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span> </div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> result(inputTensorInfo);</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span> </div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <span class="keyword">auto</span> input = MakeTensor<T, 4>(inputTensorInfo, armnnUtils::QuantizedVector<T>(inputData, scale, offset));</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span> </div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span> </div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <span class="comment">// Setup bounded ReLu.</span></div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <a class="code" href="structarmnn_1_1_activation_queue_descriptor.xhtml">armnn::ActivationQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = activationFunction;</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a017b2990003a014234f13e999dc7c689">m_A</a> = activationParameterA;</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a28c4c9cb15f6be3499abbc46b356060b">m_B</a> = activationParameterB;</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span> </div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5">CreateActivation</a>(descriptor, workloadInfo);</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span> </div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  inputHandle->Allocate();</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  outputHandle->Allocate();</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span> </div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &input[0][0][0][0]);</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span> </div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  workload->Execute();</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span> </div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&result.<a class="code" href="struct_layer_test_result.xhtml#ac9d44d346bb7c89f7a7aa31d2bee947f">output</a>[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span> </div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <span class="comment">// Calculated manually.</span></div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  result.<a class="code" href="struct_layer_test_result.xhtml#a73610ea6c776cc66e5a78dd842a39b8b">outputExpected</a> =</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  MakeTensor<T, 4>(outputTensorInfo, armnnUtils::QuantizedVector<T>(outputExpectedData, outScale, outOffset));</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span> </div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span> }</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span> </div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00480"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a901a3ece796b742b948398b267299feb"> 480</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a901a3ece796b742b948398b267299feb">SimpleSigmoidTestCommon</a>(</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  int32_t qOffset)</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span> {</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  std::vector<float> inputData =</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  {</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  -0.1f, -0.2f, -0.3f, -0.4f,</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  -1.0f, -2.0f, -3.0f, -4.0f,</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  };</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span> </div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keyword">auto</span> f = [](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  {</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keywordflow">return</span> 1.0f / (1.0f + std::exp(-value));</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  };</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span> </div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  memoryManager,</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  tensorHandleFactory,</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a>,</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  0.f,</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  0.f,</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  qScale,</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  qOffset,</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  inputData,</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  1.f / 256.f,</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  0,</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  outputExpectedData);</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span> }</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span> </div><div class="line"><a name="l00517"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#acbb4401d3616df08c74c8578d7ed56bb"> 517</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#acbb4401d3616df08c74c8578d7ed56bb">SimpleSigmoidTest</a>(</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span> {</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <span class="keywordflow">return</span> SimpleSigmoidTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager,</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  tensorHandleFactory, 0.0f, 0);</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span> }</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span> </div><div class="line"><a name="l00526"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#aa56d52a539e33972bb9c9f83be6a3fae"> 526</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#aa56d52a539e33972bb9c9f83be6a3fae">SimpleSigmoidUint8Test</a>(</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span> {</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  <span class="keywordflow">return</span> SimpleSigmoidTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager,</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  tensorHandleFactory, 0.1f, 50);</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span> }</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span> </div><div class="line"><a name="l00535"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a52def8ec78955ae882f10fac3b627f58"> 535</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a52def8ec78955ae882f10fac3b627f58">SimpleSigmoidInt16Test</a>(</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span> {</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <span class="keywordflow">return</span> SimpleSigmoidTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager,</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span> }</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span> </div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00545"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a3e9280c93340ddc5271fa2bc640763ff"> 545</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a3e9280c93340ddc5271fa2bc640763ff">ReLuTestCommon</a>(</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  int32_t qOffset)</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span> {</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  std::vector<float> inputData = {</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  -0.1f, -0.2f, -0.3f, -0.4f,</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  -1.0f, -2.0f, -3.0f, -4.0f,</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  };</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span> </div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <span class="keyword">auto</span> f = [](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  {</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  <span class="keywordflow">return</span> std::fmax(0.0f, value);</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  };</div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span> </div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  memoryManager,</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  tensorHandleFactory,</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559">armnn::ActivationFunction::ReLu</a>,</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  0.f,</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  0.f,</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  qScale,</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  qOffset,</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  inputData,</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  qScale,</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  qOffset,</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  outputExpectedData);</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span> }</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span> </div><div class="line"><a name="l00581"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#ac40efab6398e5afab3383906bcea0b55"> 581</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#ac40efab6398e5afab3383906bcea0b55">ReLuInt16Test</a>(</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span> {</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <span class="keywordflow">return</span> ReLuTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span> }</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span> </div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span> </div><div class="line"><a name="l00590"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a45728e94871f867e565a9733bfe685fc"> 590</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a45728e94871f867e565a9733bfe685fc">ReLuUint8Test</a>(</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span> {</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="keywordflow">return</span> ReLuTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span> }</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span> </div><div class="line"><a name="l00598"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a8368a9f279a3480e87c693688686227a"> 598</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a8368a9f279a3480e87c693688686227a">ReLuTest</a>(</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span> {</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <span class="keywordflow">return</span> ReLuTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span> }</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span> </div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span> </div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00608"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a33fddc51aba945a41434951110208da4"> 608</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a17ab0fa28201a48e6ed1f45eba2aa901">BoundedReLuTestCommon</a>(</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  int32_t qOffset)</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span> {</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  std::vector<float> inputData = {</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  -0.1f, -0.2f, -0.3f, -0.4f,</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  -1.0f, -2.0f, -3.0f, -4.0f,</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  };</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> a = 1.0f;</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> b = -1.0f;</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <span class="keyword">auto</span> f = [a, b](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  {</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  <span class="keywordflow">return</span> std::min(a, std::max(b, value));</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  };</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span> </div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  memoryManager,</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  tensorHandleFactory,</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a>,</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  a,</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  b,</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  qScale,</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  qOffset,</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  inputData,</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  qScale,</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  qOffset,</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  outputExpectedData);</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span> }</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span> </div><div class="line"><a name="l00645"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a2f0f449bcba656f12e676c7554846626"> 645</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a2f0f449bcba656f12e676c7554846626">BoundedReLuInt16Test</a>(</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span> {</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  <span class="keywordflow">return</span> ReLuTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span> }</div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span> </div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span> </div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span> </div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00656"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#ac1ff1b47192a4ae96deca53703c97d56"> 656</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#ac1ff1b47192a4ae96deca53703c97d56">SoftReLuTestCommon</a>(</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  int32_t qOffset)</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span> {</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  std::vector<float> inputData = {</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  -0.1f, -0.2f, -0.3f, -0.4f,</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  -1.0f, -2.0f, -3.0f, -4.0f,</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  };</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span> </div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  <span class="keyword">auto</span> f = [](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  {</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  <span class="keywordflow">return</span> std::log(1.0f + std::exp(value));</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  };</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span> </div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  memoryManager,</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  tensorHandleFactory,</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa6bba7052636d1740303b1b2ef3b53fef">armnn::ActivationFunction::SoftReLu</a>,</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  0.f,</div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  0.f,</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  qScale,</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  qOffset,</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  inputData,</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  qScale,</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  qOffset,</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  outputExpectedData);</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span> }</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span> </div><div class="line"><a name="l00692"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#ae2d87b32c8fde79841bdd44e5b07b220"> 692</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#ae2d87b32c8fde79841bdd44e5b07b220">SoftReLuTest</a>(</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span> {</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  <span class="keywordflow">return</span> SoftReLuTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span> }</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span> </div><div class="line"><a name="l00700"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#abe4ce5ac4300f71f8d1e17df42b73bdf"> 700</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#abe4ce5ac4300f71f8d1e17df42b73bdf">SoftReLuUint8Test</a>(</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span> {</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  <span class="keywordflow">return</span> SoftReLuTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager,</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  tensorHandleFactory, 0.0625f, 64);</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span> }</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span> </div><div class="line"><a name="l00709"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a102ed5f3b12e4d88645c9cc60820554a"> 709</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a102ed5f3b12e4d88645c9cc60820554a">SoftReLuInt16Test</a>(</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span> {</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <span class="keywordflow">return</span> SoftReLuTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span> }</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span> </div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00718"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a4e4d43057d33c584cfb9bd3257c0a643"> 718</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a4e4d43057d33c584cfb9bd3257c0a643">LeakyReLuTestCommon</a>(</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  int32_t qOffset)</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span> {</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  std::vector<float> inputData = {</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  -0.1f, -0.2f, -0.3f, -0.4f,</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  -1.0f, -2.0f, -3.0f, -4.0f,</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  };</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span> </div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> a = 0.01f;</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  <span class="keyword">auto</span> f = [a](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  {</div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  <span class="keywordflow">return</span> value > 0.0f ? value : (value * a);</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  };</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span> </div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  memoryManager,</div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  tensorHandleFactory,</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaacb7667f5ec2f6e8a5943b781ba6c2735">armnn::ActivationFunction::LeakyReLu</a>,</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  a,</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  0.f,</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  qScale,</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  qOffset,</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  inputData,</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  qScale,</div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  qOffset,</div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  outputExpectedData);</div><div class="line"><a name="l00753"></a><span class="lineno"> 753</span> }</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span> </div><div class="line"><a name="l00755"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#af787d7e79d1e8c23c97267a116e934ee"> 755</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#af787d7e79d1e8c23c97267a116e934ee">LeakyReLuTest</a>(</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span> {</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  <span class="keywordflow">return</span> LeakyReLuTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span> }</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span> </div><div class="line"><a name="l00763"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a99549cc0465b1493900164f87912f093"> 763</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a99549cc0465b1493900164f87912f093">LeakyReLuUint8Test</a>(</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span> {</div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  <span class="keywordflow">return</span> LeakyReLuTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager,</div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  tensorHandleFactory, 0.0625f, 64);</div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span> }</div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span> </div><div class="line"><a name="l00772"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a130f4fb9c8db249c9e1053f0725d9db2"> 772</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a130f4fb9c8db249c9e1053f0725d9db2">LeakyReLuInt16Test</a>(</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span> {</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <span class="keywordflow">return</span> LeakyReLuTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span> }</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span> </div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00781"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a3987d62d2efea44da3ca8e9b1dc3be21"> 781</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a3987d62d2efea44da3ca8e9b1dc3be21">AbsTestCommon</a>(</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  int32_t qOffset)</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span> {</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  std::vector<float> inputData = {</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  -0.1f, -0.2f, -0.3f, -0.4f,</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  -1.0f, -2.0f, -3.0f, -4.0f,</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  };</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span> </div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  <span class="keyword">auto</span> f = [](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  {</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  <span class="keywordflow">return</span> std::abs(value);</div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  };</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span> </div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  memoryManager,</div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  tensorHandleFactory,</div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">armnn::ActivationFunction::Abs</a>,</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  0.f,</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  0.f,</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  qScale,</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  qOffset,</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  inputData,</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  qScale,</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  qOffset,</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  outputExpectedData);</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span> }</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span> </div><div class="line"><a name="l00817"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#afa1af28f33ae8978b6df0b170561f787"> 817</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#afa1af28f33ae8978b6df0b170561f787">AbsTest</a>(</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span> {</div><div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  <span class="keywordflow">return</span> AbsTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span> }</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span> </div><div class="line"><a name="l00825"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a60f58fb3975d3fdfb64dfb3279e1e518"> 825</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a60f58fb3975d3fdfb64dfb3279e1e518">AbsUint8Test</a>(</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span> {</div><div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  <span class="keywordflow">return</span> AbsTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, tensorHandleFactory, 0.0625f, 64);</div><div class="line"><a name="l00831"></a><span class="lineno"> 831</span> }</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span> </div><div class="line"><a name="l00833"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#aa21484e44ff8ce2a751654d123fc9d0a"> 833</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#aa21484e44ff8ce2a751654d123fc9d0a">AbsInt16Test</a>(</div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span> {</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  <span class="keywordflow">return</span> AbsTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span> }</div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span> </div><div class="line"><a name="l00841"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a71ae12f61c946554c49aaa709c81ffa9"> 841</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 5></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a71ae12f61c946554c49aaa709c81ffa9">SqrtNNTest</a>(</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span> {</div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> inputDataSize = 120;</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  std::vector<float> inputData(inputDataSize);</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span> </div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0u; i < inputDataSize; ++i)</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  {</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  inputData[i] = <span class="keyword">static_cast<</span><span class="keywordtype">float</span><span class="keyword">></span>(i) / 10;</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  }</div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span> </div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  <span class="keyword">auto</span> f = [](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  {</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  <span class="keywordflow">return</span> std::sqrt(value);</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  };</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  std::vector<float> outputExpectedData(inputDataSize);</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span> </div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo(</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  { 1u, 2u, 3u, 4u, 5u }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo(</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  { 1u, 2u, 3u, 4u, 5u }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span> </div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 5></a> result(inputTensorInfo);</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span> </div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  <span class="keyword">auto</span> input = MakeTensor<float, 5>(inputTensorInfo, inputData);</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span> </div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span> </div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  <a class="code" href="structarmnn_1_1_activation_queue_descriptor.xhtml">armnn::ActivationQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> workloadInfo;</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  AddOutputToWorkload(descriptor, workloadInfo, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span> </div><div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  descriptor.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">armnn::ActivationFunction::Sqrt</a>;</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span> </div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5">CreateActivation</a>(descriptor, workloadInfo);</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span> </div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  inputHandle->Allocate();</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  outputHandle->Allocate();</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span> </div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &input[0][0][0][0][0]);</div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span> </div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  workload->Execute();</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span> </div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&result.output[0][0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span> </div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  <span class="comment">// Calculated manually.</span></div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  result.outputExpected = MakeTensor<float, 5>(outputTensorInfo, outputExpectedData);</div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span> </div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span> };</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span> </div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00899"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a6612d7fa4a0b57c9495bc4e1f3a274f3"> 899</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a6612d7fa4a0b57c9495bc4e1f3a274f3">SqrtTestCommon</a>(</div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  int32_t qOffset)</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span> {</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  std::vector<float> inputData = {</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  1.0f, 2.0f, 3.0f, 4.0f,</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  };</div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span> </div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  <span class="keyword">auto</span> f = [](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  {</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  <span class="keywordflow">return</span> std::sqrt(value);</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  };</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span> </div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  memoryManager,</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  tensorHandleFactory,</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">armnn::ActivationFunction::Sqrt</a>,</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  0.f,</div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  0.f,</div><div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  qScale,</div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  qOffset,</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  inputData,</div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  qScale,</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  qOffset,</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  outputExpectedData);</div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span> }</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span> </div><div class="line"><a name="l00935"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#ac9907063df1d7bba86f9f086ecd96810"> 935</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#ac9907063df1d7bba86f9f086ecd96810">SqrtTest</a>(</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span> {</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <span class="keywordflow">return</span> SqrtTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span> }</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span> </div><div class="line"><a name="l00943"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a95c71d4f833302b14790ce0755cb1103"> 943</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a95c71d4f833302b14790ce0755cb1103">SqrtUint8Test</a>(</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span> {</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  <span class="keywordflow">return</span> SqrtTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, tensorHandleFactory, 0.0625f, 64);</div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span> }</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span> </div><div class="line"><a name="l00951"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#ae38ea3540b33a68254857f9031352e71"> 951</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#ae38ea3540b33a68254857f9031352e71">SqrtInt16Test</a>(</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span> {</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  <span class="keywordflow">return</span> SqrtTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l00957"></a><span class="lineno"> 957</span> }</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span> </div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00960"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a89e93214e6dc3c5616b2351467b0abf9"> 960</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a89e93214e6dc3c5616b2351467b0abf9">SquareTestCommon</a>(</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  int32_t qOffset)</div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span> {</div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  std::vector<float> inputData = {</div><div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  -0.1f, -0.2f, -0.3f, -0.4f,</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  -1.0f, -2.0f, -3.0f, -4.0f,</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  };</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span> </div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  <span class="keyword">auto</span> f = [](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  {</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  <span class="keywordflow">return</span> std::pow(value,2);</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  };</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span> </div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  memoryManager,</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  tensorHandleFactory,</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaceb46ca115d05c51aa5a16a8867c3304">armnn::ActivationFunction::Square</a>,</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  0.f,</div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  0.f,</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  qScale,</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  qOffset,</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  inputData,</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  qScale,</div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  qOffset,</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span>  outputExpectedData);</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span> }</div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span> </div><div class="line"><a name="l00996"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a587b1550cc5479deb48bbe14c7eded17"> 996</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a587b1550cc5479deb48bbe14c7eded17">SquareTest</a>(</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span> {</div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>  <span class="keywordflow">return</span> SquareTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span> }</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span> </div><div class="line"><a name="l01004"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a1199022cc4acee1c6fa906b1ec62d4dc"> 1004</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a1199022cc4acee1c6fa906b1ec62d4dc">SquareUint8Test</a>(</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span> {</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  <span class="keywordflow">return</span> SquareTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager,</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>  tensorHandleFactory, 0.0625f, 64);</div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span> }</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span> </div><div class="line"><a name="l01013"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#acac16f9bf4a34a7a07b011a22271668a"> 1013</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#acac16f9bf4a34a7a07b011a22271668a">SquareInt16Test</a>(</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span> {</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  <span class="keywordflow">return</span> SquareTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span> }</div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span> </div><div class="line"><a name="l01021"></a><span class="lineno"> 1021</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l01022"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a33f55d819a0bf16122b458f34c82c259"> 1022</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a33f55d819a0bf16122b458f34c82c259">TanhTestCommon</a>(</div><div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  int32_t qOffset)</div><div class="line"><a name="l01028"></a><span class="lineno"> 1028</span> {</div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>  std::vector<float> inputData = {</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>  -0.1f, -0.2f, -0.3f, -0.4f,</div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  -1.0f, -2.0f, -3.0f, -4.0f,</div><div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>  };</div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span> </div><div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> a = 2.0f;</div><div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> b = 3.0f;</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  <span class="keyword">auto</span> f = [a, b](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>  {</div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>  <span class="keywordflow">return</span> a * tanhf(b * value);</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  };</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l01045"></a><span class="lineno"> 1045</span> </div><div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  memoryManager,</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  tensorHandleFactory,</div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e">armnn::ActivationFunction::TanH</a>,</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>  a,</div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>  b,</div><div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>  qScale,</div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  qOffset,</div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>  inputData,</div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>  qScale,</div><div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>  qOffset,</div><div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  outputExpectedData);</div><div class="line"><a name="l01058"></a><span class="lineno"> 1058</span> }</div><div class="line"><a name="l01059"></a><span class="lineno"> 1059</span> </div><div class="line"><a name="l01060"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#ab06eef1a3385ff1aa8914372a9e9c3a4"> 1060</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#ab06eef1a3385ff1aa8914372a9e9c3a4">TanhTest</a>(</div><div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01064"></a><span class="lineno"> 1064</span> {</div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  <span class="keywordflow">return</span> TanhTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span> }</div><div class="line"><a name="l01067"></a><span class="lineno"> 1067</span> </div><div class="line"><a name="l01068"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a7e6da1965d217931a350ad5f4f3dd772"> 1068</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a7e6da1965d217931a350ad5f4f3dd772">TanhUint8Test</a>(</div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01072"></a><span class="lineno"> 1072</span> {</div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>  <span class="keywordflow">return</span> TanhTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 64);</div><div class="line"><a name="l01074"></a><span class="lineno"> 1074</span> }</div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span> </div><div class="line"><a name="l01076"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#af67ae99fbcbf479f21bf9a6a5b20a41c"> 1076</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#af67ae99fbcbf479f21bf9a6a5b20a41c">TanhInt16Test</a>(</div><div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01080"></a><span class="lineno"> 1080</span> {</div><div class="line"><a name="l01081"></a><span class="lineno"> 1081</span>  <span class="keywordflow">return</span> TanhTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l01082"></a><span class="lineno"> 1082</span> }</div><div class="line"><a name="l01083"></a><span class="lineno"> 1083</span> </div><div class="line"><a name="l01084"></a><span class="lineno"> 1084</span> </div><div class="line"><a name="l01085"></a><span class="lineno"> 1085</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l01086"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a1b9b0fb59a485e33724a59b2c1282d91"> 1086</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a1b9b0fb59a485e33724a59b2c1282d91">EluTestCommon</a>(</div><div class="line"><a name="l01087"></a><span class="lineno"> 1087</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span>  int32_t qOffset)</div><div class="line"><a name="l01092"></a><span class="lineno"> 1092</span> {</div><div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>  std::vector<float> inputData = {</div><div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>  -0.1f, -0.2f, -0.3f, -0.4f,</div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span>  -1.0f, -2.0f, -3.0f, -4.0f,</div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  };</div><div class="line"><a name="l01099"></a><span class="lineno"> 1099</span> </div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span> </div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> a = 0.01f;</div><div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  <span class="keyword">auto</span> f = [a](<span class="keywordtype">float</span> value)</div><div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>  {</div><div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>  <span class="keywordflow">return</span> (value >= 0) ? value : a * (expf(value) - 1);</div><div class="line"><a name="l01106"></a><span class="lineno"> 1106</span>  };</div><div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l01109"></a><span class="lineno"> 1109</span> </div><div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  memoryManager,</div><div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  tensorHandleFactory,</div><div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaed67cf7d54c570e4c4891800f085f41d">armnn::ActivationFunction::Elu</a>,</div><div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  a,</div><div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>  0.0f,</div><div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>  qScale,</div><div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>  qOffset,</div><div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>  inputData,</div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span>  qScale,</div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  qOffset,</div><div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>  outputExpectedData);</div><div class="line"><a name="l01122"></a><span class="lineno"> 1122</span> }</div><div class="line"><a name="l01123"></a><span class="lineno"> 1123</span> </div><div class="line"><a name="l01124"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#aa6dccc291eaf62b56655c7ae392f0d25"> 1124</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#aa6dccc291eaf62b56655c7ae392f0d25">EluTest</a>(</div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span> {</div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>  <span class="keywordflow">return</span> EluTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span> }</div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span> </div><div class="line"><a name="l01132"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a54c12a6c177195bb8a20876f60db0286"> 1132</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a54c12a6c177195bb8a20876f60db0286">EluUint8Test</a>(</div><div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01136"></a><span class="lineno"> 1136</span> {</div><div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>  <span class="keywordflow">return</span> EluTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 64);</div><div class="line"><a name="l01138"></a><span class="lineno"> 1138</span> }</div><div class="line"><a name="l01139"></a><span class="lineno"> 1139</span> </div><div class="line"><a name="l01140"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a5f6946f1aa4624ea5c7a707d318586dc"> 1140</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a5f6946f1aa4624ea5c7a707d318586dc">EluInt16Test</a>(</div><div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span> {</div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>  <span class="keywordflow">return</span> EluTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l01146"></a><span class="lineno"> 1146</span> }</div><div class="line"><a name="l01147"></a><span class="lineno"> 1147</span> </div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span> </div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l01150"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a4decbf4064f28b31d9e3c14fabc3a56e"> 1150</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a4decbf4064f28b31d9e3c14fabc3a56e">HardSwishTestCommon</a>(</div><div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>  <span class="keywordtype">float</span> qScale,</div><div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>  int32_t qOffset)</div><div class="line"><a name="l01156"></a><span class="lineno"> 1156</span> {</div><div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>  std::vector<float> inputData = {</div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>  -0.1f, -0.2f, -0.3f, -0.4f,</div><div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>  0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>  -1.0f, -2.0f, -3.0f, -4.0f,</div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  1.0f, 2.0f, 3.0f, 4.0f</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>  };</div><div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>  <span class="comment">// Calculate output values for input.</span></div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>  <span class="keyword">auto</span> f = [](<span class="keywordtype">float</span> x)</div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  {</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  <span class="comment">// Break down the calculation to help with verification.</span></div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>  <span class="comment">// hard_swish(x) = x * relu6(x+3) / 6</span></div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span>  <span class="comment">// relu6(x) = min(max(x,0),6)</span></div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>  <span class="keywordtype">float</span> reLu6_step1 = std::max((x + 3),0.0f);</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>  <span class="keywordtype">float</span> reLu6Complete = std::min(reLu6_step1, 6.0f);</div><div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>  <span class="keywordtype">float</span> hardSwish_step1 = x * reLu6Complete;</div><div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>  <span class="keywordtype">float</span> result = hardSwish_step1 / 6;</div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>  <span class="keywordflow">return</span> result;</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  };</div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>  std::vector<float> outputExpectedData(inputData.size());</div><div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>  std::transform(inputData.begin(), inputData.end(), outputExpectedData.begin(), f);</div><div class="line"><a name="l01177"></a><span class="lineno"> 1177</span> </div><div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>  <span class="keywordflow">return</span> SimpleActivationTest<ArmnnType>(workloadFactory,</div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>  memoryManager,</div><div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  tensorHandleFactory,</div><div class="line"><a name="l01181"></a><span class="lineno"> 1181</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa0877e5b3fbe9d7569df6399609ed0186">armnn::ActivationFunction::HardSwish</a>,</div><div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>  0.f,</div><div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>  0.f,</div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>  qScale,</div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>  qOffset,</div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  inputData,</div><div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>  qScale,</div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>  qOffset,</div><div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>  outputExpectedData);</div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span> }</div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</span> </div><div class="line"><a name="l01192"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a6c2c2872c1f72cb6ba1f947de0d1b314"> 1192</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a6c2c2872c1f72cb6ba1f947de0d1b314">HardSwishTest</a>(</div><div class="line"><a name="l01193"></a><span class="lineno"> 1193</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span> {</div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  <span class="keywordflow">return</span> HardSwishTestCommon<armnn::DataType::Float32>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l01198"></a><span class="lineno"> 1198</span> }</div><div class="line"><a name="l01199"></a><span class="lineno"> 1199</span> </div><div class="line"><a name="l01200"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a3bcc369772d1cd70007d3078a032dc03"> 1200</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a3bcc369772d1cd70007d3078a032dc03">HardSwishUint8Test</a>(</div><div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01204"></a><span class="lineno"> 1204</span> {</div><div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>  <span class="keywordflow">return</span> HardSwishTestCommon<armnn::DataType::QAsymmU8>(workloadFactory, memoryManager,</div><div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>  tensorHandleFactory, 0.1f, 64);</div><div class="line"><a name="l01207"></a><span class="lineno"> 1207</span> }</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span> </div><div class="line"><a name="l01209"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#aa3aa2cd4a74c5bbf137fe056e2161c52"> 1209</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t, 4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#aa3aa2cd4a74c5bbf137fe056e2161c52">HardSwishInt16Test</a>(</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory)</div><div class="line"><a name="l01213"></a><span class="lineno"> 1213</span> {</div><div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  <span class="keywordflow">return</span> HardSwishTestCommon<armnn::DataType::QSymmS16>(workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 0);</div><div class="line"><a name="l01215"></a><span class="lineno"> 1215</span> }</div><div class="line"><a name="l01216"></a><span class="lineno"> 1216</span> </div><div class="line"><a name="l01217"></a><span class="lineno"> 1217</span> </div><div class="line"><a name="l01218"></a><span class="lineno"> 1218</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l01219"></a><span class="lineno"><a class="line" href="_activation_test_impl_8cpp.xhtml#a0e54b6eef4277787b60869d72ed1015f"> 1219</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T,4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a0e54b6eef4277787b60869d72ed1015f">CompareActivationTestImpl</a>(</div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& refWorkloadFactory,</div><div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& refTensorHandleFactory,</div><div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a> f,</div><div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 5,</div><div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>  <span class="keywordtype">float</span> qScale = 0.0f,</div><div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  int32_t qOffset = 0)</div><div class="line"><a name="l01229"></a><span class="lineno"> 1229</span> {</div><div class="line"><a name="l01230"></a><span class="lineno"> 1230</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l01231"></a><span class="lineno"> 1231</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = 17;</div><div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 29;</div><div class="line"><a name="l01233"></a><span class="lineno"> 1233</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 2;</div><div class="line"><a name="l01234"></a><span class="lineno"> 1234</span> </div><div class="line"><a name="l01235"></a><span class="lineno"> 1235</span>  <span class="keywordtype">float</span> a = 0.234f;</div><div class="line"><a name="l01236"></a><span class="lineno"> 1236</span>  <span class="keywordtype">float</span> b = -12.345f;</div><div class="line"><a name="l01237"></a><span class="lineno"> 1237</span> </div><div class="line"><a name="l01238"></a><span class="lineno"> 1238</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l01239"></a><span class="lineno"> 1239</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</div><div class="line"><a name="l01240"></a><span class="lineno"> 1240</span> </div><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> shape[] = {batchSize, channels, height, width};</div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span> </div><div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>  inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, shape, ArmnnType);</div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>  outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, shape, ArmnnType);</div><div class="line"><a name="l01245"></a><span class="lineno"> 1245</span> </div><div class="line"><a name="l01246"></a><span class="lineno"> 1246</span>  <span class="comment">// Set quantization parameters if the requested type is a quantized type.</span></div><div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>  <span class="keywordflow">if</span>(armnn::IsQuantizedType<T>())</div><div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>  {</div><div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>  inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>  outputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l01253"></a><span class="lineno"> 1253</span>  }</div><div class="line"><a name="l01254"></a><span class="lineno"> 1254</span> </div><div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>  <span class="keywordtype">float</span> minVal = -10.f;</div><div class="line"><a name="l01256"></a><span class="lineno"> 1256</span>  <span class="keywordflow">if</span> (f == <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">armnn::ActivationFunction::Sqrt</a>)</div><div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>  {</div><div class="line"><a name="l01258"></a><span class="lineno"> 1258</span>  minVal = 0.f;</div><div class="line"><a name="l01259"></a><span class="lineno"> 1259</span>  }</div><div class="line"><a name="l01260"></a><span class="lineno"> 1260</span> </div><div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>  boost::multi_array<T, 4> input = MakeRandomTensor<T, 4>(inputTensorInfo, 21453, minVal, 10.f);</div><div class="line"><a name="l01262"></a><span class="lineno"> 1262</span> </div><div class="line"><a name="l01263"></a><span class="lineno"> 1263</span> </div><div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>  <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<T,4></a> ret(outputTensorInfo);</div><div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>  <span class="keyword">auto</span> boostArrayExtents = boost::extents</div><div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>  [<a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><boost::multi_array_types::extent_gen::index>(batchSize)]</div><div class="line"><a name="l01267"></a><span class="lineno"> 1267</span>  [armnn::numeric_cast<boost::multi_array_types::extent_gen::index>(channels)]</div><div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>  [<a class="code" href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a><boost::multi_array_types::extent_gen::index>(height)]</div><div class="line"><a name="l01269"></a><span class="lineno"> 1269</span>  [armnn::numeric_cast<boost::multi_array_types::extent_gen::index>(width)];</div><div class="line"><a name="l01270"></a><span class="lineno"> 1270</span>  ret.output.resize(boostArrayExtents);</div><div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>  ret.outputExpected.resize(boostArrayExtents);</div><div class="line"><a name="l01272"></a><span class="lineno"> 1272</span> </div><div class="line"><a name="l01273"></a><span class="lineno"> 1273</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l01274"></a><span class="lineno"> 1274</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l01275"></a><span class="lineno"> 1275</span> </div><div class="line"><a name="l01276"></a><span class="lineno"> 1276</span>  std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>  std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refTensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l01278"></a><span class="lineno"> 1278</span> </div><div class="line"><a name="l01279"></a><span class="lineno"> 1279</span>  <a class="code" href="structarmnn_1_1_activation_queue_descriptor.xhtml">armnn::ActivationQueueDescriptor</a> data;</div><div class="line"><a name="l01280"></a><span class="lineno"> 1280</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> info;</div><div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l01282"></a><span class="lineno"> 1282</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a017b2990003a014234f13e999dc7c689">m_A</a> = a;</div><div class="line"><a name="l01284"></a><span class="lineno"> 1284</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#a28c4c9cb15f6be3499abbc46b356060b">m_B</a> = b;</div><div class="line"><a name="l01285"></a><span class="lineno"> 1285</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">m_Function</a> = f;</div><div class="line"><a name="l01286"></a><span class="lineno"> 1286</span> </div><div class="line"><a name="l01287"></a><span class="lineno"> 1287</span>  <a class="code" href="structarmnn_1_1_activation_queue_descriptor.xhtml">armnn::ActivationQueueDescriptor</a> refData = data;</div><div class="line"><a name="l01288"></a><span class="lineno"> 1288</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> refInfo = info;</div><div class="line"><a name="l01289"></a><span class="lineno"> 1289</span>  SetWorkloadInput(refData, refInfo, 0, inputTensorInfo, inputHandleRef.get());</div><div class="line"><a name="l01290"></a><span class="lineno"> 1290</span>  SetWorkloadOutput(refData, refInfo, 0, outputTensorInfo, outputHandleRef.get());</div><div class="line"><a name="l01291"></a><span class="lineno"> 1291</span> </div><div class="line"><a name="l01292"></a><span class="lineno"> 1292</span>  std::unique_ptr<armnn::IWorkload> workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5">CreateActivation</a>(data, info);</div><div class="line"><a name="l01293"></a><span class="lineno"> 1293</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(workload != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l01294"></a><span class="lineno"> 1294</span>  std::unique_ptr<armnn::IWorkload> workloadRef = refWorkloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5">CreateActivation</a>(refData, refInfo);</div><div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(workloadRef != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l01296"></a><span class="lineno"> 1296</span> </div><div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>  inputHandle->Allocate();</div><div class="line"><a name="l01298"></a><span class="lineno"> 1298</span>  outputHandle->Allocate();</div><div class="line"><a name="l01299"></a><span class="lineno"> 1299</span>  inputHandleRef->Allocate();</div><div class="line"><a name="l01300"></a><span class="lineno"> 1300</span>  outputHandleRef->Allocate();</div><div class="line"><a name="l01301"></a><span class="lineno"> 1301</span> </div><div class="line"><a name="l01302"></a><span class="lineno"> 1302</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &input[0][0][0][0]);</div><div class="line"><a name="l01303"></a><span class="lineno"> 1303</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandleRef.get(), &input[0][0][0][0]);</div><div class="line"><a name="l01304"></a><span class="lineno"> 1304</span> </div><div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>  workload->Execute();</div><div class="line"><a name="l01306"></a><span class="lineno"> 1306</span>  workloadRef->Execute();</div><div class="line"><a name="l01307"></a><span class="lineno"> 1307</span> </div><div class="line"><a name="l01308"></a><span class="lineno"> 1308</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l01309"></a><span class="lineno"> 1309</span>  <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&ret.outputExpected[0][0][0][0], outputHandleRef.get());</div><div class="line"><a name="l01310"></a><span class="lineno"> 1310</span> </div><div class="line"><a name="l01311"></a><span class="lineno"> 1311</span>  <span class="keywordflow">return</span> ret;</div><div class="line"><a name="l01312"></a><span class="lineno"> 1312</span> }</div><div class="line"><a name="l01313"></a><span class="lineno"> 1313</span> </div><div class="line"><a name="l01314"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#a3fe7773804a82637c66799f5f106e31e"> 1314</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float,4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a38a8471de26d70e7bcc13861948b009a">CompareActivationTest</a>(</div><div class="line"><a name="l01315"></a><span class="lineno"> 1315</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01316"></a><span class="lineno"> 1316</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01317"></a><span class="lineno"> 1317</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& refWorkloadFactory,</div><div class="line"><a name="l01318"></a><span class="lineno"> 1318</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01319"></a><span class="lineno"> 1319</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& refTensorHandleFactory,</div><div class="line"><a name="l01320"></a><span class="lineno"> 1320</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a> f,</div><div class="line"><a name="l01321"></a><span class="lineno"> 1321</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize)</div><div class="line"><a name="l01322"></a><span class="lineno"> 1322</span> {</div><div class="line"><a name="l01323"></a><span class="lineno"> 1323</span>  <span class="keywordflow">return</span> CompareActivationTestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l01324"></a><span class="lineno"> 1324</span>  workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory,</div><div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>  refTensorHandleFactory, f, batchSize);</div><div class="line"><a name="l01326"></a><span class="lineno"> 1326</span> }</div><div class="line"><a name="l01327"></a><span class="lineno"> 1327</span> </div><div class="line"><a name="l01328"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#aba70ea96ebdef661aeb5cc77c631312c"> 1328</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<uint8_t,4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a98bbb7ff1347e911e6505cc5345b9b17">CompareActivationUint8Test</a>(</div><div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01330"></a><span class="lineno"> 1330</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& refWorkloadFactory,</div><div class="line"><a name="l01332"></a><span class="lineno"> 1332</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& refTensorHandleFactory,</div><div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a> f)</div><div class="line"><a name="l01335"></a><span class="lineno"> 1335</span> {</div><div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>  <span class="keywordflow">return</span> CompareActivationTestImpl<armnn::DataType::QAsymmU8>(</div><div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>  workloadFactory, memoryManager, refWorkloadFactory,</div><div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>  tensorHandleFactory, refTensorHandleFactory, f, 5, 0.1f, 50);</div><div class="line"><a name="l01339"></a><span class="lineno"> 1339</span> }</div><div class="line"><a name="l01340"></a><span class="lineno"> 1340</span> </div><div class="line"><a name="l01341"></a><span class="lineno"><a class="line" href="_activation_test_impl_8hpp.xhtml#af570c70b327791541f5bbf2c13e99e3f"> 1341</a></span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<int16_t,4></a> <a class="code" href="_activation_test_impl_8cpp.xhtml#a67a7fa8c32816472fde1b4042795f789">CompareActivationInt16Test</a>(</div><div class="line"><a name="l01342"></a><span class="lineno"> 1342</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& workloadFactory,</div><div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a>& memoryManager,</div><div class="line"><a name="l01344"></a><span class="lineno"> 1344</span>  <a class="code" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a>& refWorkloadFactory,</div><div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& tensorHandleFactory,</div><div class="line"><a name="l01346"></a><span class="lineno"> 1346</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a>& refTensorHandleFactory,</div><div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>  <a class="code" href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a> f)</div><div class="line"><a name="l01348"></a><span class="lineno"> 1348</span> {</div><div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>  <span class="keywordflow">return</span> CompareActivationTestImpl<armnn::DataType::QSymmS16>(</div><div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>  workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory,</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>  refTensorHandleFactory, f, 5, 0.1f, 0);</div><div class="line"><a name="l01352"></a><span class="lineno"> 1352</span> }</div><div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa3d90c0a5ab3fcf8e6f6608cb3d3a1559">armnn::ActivationFunction::ReLu</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a901a3ece796b742b948398b267299feb"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a901a3ece796b742b948398b267299feb">SimpleSigmoidTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > SimpleSigmoidTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00480">ActivationTestImpl.cpp:480</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a98bbb7ff1347e911e6505cc5345b9b17"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a98bbb7ff1347e911e6505cc5345b9b17">CompareActivationUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > CompareActivationUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::IWorkloadFactory &refWorkloadFactory, const armnn::ITensorHandleFactory &tensorHandleFactory, const armnn::ITensorHandleFactory &refTensorHandleFactory, armnn::ActivationFunction f)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01328">ActivationTestImpl.cpp:1328</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_afc6867f503e2bdbe9d42eee7361d1f91"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#afc6867f503e2bdbe9d42eee7361d1f91">ConstantLinearActivationTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > ConstantLinearActivationTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale=0.0f, int32_t qOffset=0)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00317">ActivationTestImpl.cpp:317</a></div></div>
<div class="ttc" id="_tensor_copy_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_copy_utils_8hpp.xhtml">TensorCopyUtils.hpp</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_ac9907063df1d7bba86f9f086ecd96810"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#ac9907063df1d7bba86f9f086ecd96810">SqrtTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > SqrtTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00935">ActivationTestImpl.cpp:935</a></div></div>
<div class="ttc" id="_activation_test_impl_8hpp_xhtml"><div class="ttname"><a href="_activation_test_impl_8hpp.xhtml">ActivationTestImpl.hpp</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a1ff5e9c94a9862b4e10cfd407edd1144"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a1ff5e9c94a9862b4e10cfd407edd1144">ConstantLinearActivationInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > ConstantLinearActivationInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00397">ActivationTestImpl.cpp:397</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_acbb4401d3616df08c74c8578d7ed56bb"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#acbb4401d3616df08c74c8578d7ed56bb">SimpleSigmoidTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > SimpleSigmoidTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00517">ActivationTestImpl.cpp:517</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_ae2d87b32c8fde79841bdd44e5b07b220"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#ae2d87b32c8fde79841bdd44e5b07b220">SoftReLuTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > SoftReLuTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00692">ActivationTestImpl.cpp:692</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a0e54b6eef4277787b60869d72ed1015f"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a0e54b6eef4277787b60869d72ed1015f">CompareActivationTestImpl</a></div><div class="ttdeci">LayerTestResult< T, 4 > CompareActivationTestImpl(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::IWorkloadFactory &refWorkloadFactory, const armnn::ITensorHandleFactory &tensorHandleFactory, const armnn::ITensorHandleFactory &refTensorHandleFactory, armnn::ActivationFunction f, unsigned int batchSize=5, float qScale=0.0f, int32_t qOffset=0)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01219">ActivationTestImpl.cpp:1219</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_afabbbadee3467a572cac32e1253b073b"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#afabbbadee3467a572cac32e1253b073b">CompareBoundedReLuTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > CompareBoundedReLuTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::IWorkloadFactory &refWorkloadFactory, const armnn::ITensorHandleFactory &tensorHandleFactory, const armnn::ITensorHandleFactory &refTensorHandleFactory, float upperBound, float lowerBound)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00292">ActivationTestImpl.cpp:292</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a33f55d819a0bf16122b458f34c82c259"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a33f55d819a0bf16122b458f34c82c259">TanhTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > TanhTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01022">ActivationTestImpl.cpp:1022</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a130f4fb9c8db249c9e1053f0725d9db2"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a130f4fb9c8db249c9e1053f0725d9db2">LeakyReLuInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > LeakyReLuInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00772">ActivationTestImpl.cpp:772</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_adb77d7a922e1a8dee8490f50a5ae4bac"><div class="ttname"><a href="namespacearmnn.xhtml#adb77d7a922e1a8dee8490f50a5ae4bac">armnn::GetInputTensorInfo</a></div><div class="ttdeci">TensorInfo GetInputTensorInfo(const INetwork *network)</div><div class="ttdef"><b>Definition:</b> <a href="_quantizer_test_8cpp_source.xhtml#l00080">QuantizerTest.cpp:80</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#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="_quantize_helper_8hpp_xhtml"><div class="ttname"><a href="_quantize_helper_8hpp.xhtml">QuantizeHelper.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8hpp_source.xhtml#l00022">WorkloadFactory.hpp:22</a></div></div>
<div class="ttc" id="_workload_test_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_test_utils_8hpp.xhtml">WorkloadTestUtils.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaae77f3ad25595e35b327334d89410054">armnn::ActivationFunction::Sqrt</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a67a7fa8c32816472fde1b4042795f789"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a67a7fa8c32816472fde1b4042795f789">CompareActivationInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > CompareActivationInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::IWorkloadFactory &refWorkloadFactory, const armnn::ITensorHandleFactory &tensorHandleFactory, const armnn::ITensorHandleFactory &refTensorHandleFactory, armnn::ActivationFunction f)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01341">ActivationTestImpl.cpp:1341</a></div></div>
<div class="ttc" id="struct_layer_test_result_xhtml_a73610ea6c776cc66e5a78dd842a39b8b"><div class="ttname"><a href="struct_layer_test_result.xhtml#a73610ea6c776cc66e5a78dd842a39b8b">LayerTestResult::outputExpected</a></div><div class="ttdeci">boost::multi_array< T, n > outputExpected</div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00042">LayerTestResult.hpp:42</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaacb7667f5ec2f6e8a5943b781ba6c2735"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaacb7667f5ec2f6e8a5943b781ba6c2735">armnn::ActivationFunction::LeakyReLu</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a38a8471de26d70e7bcc13861948b009a"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a38a8471de26d70e7bcc13861948b009a">CompareActivationTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > CompareActivationTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, armnn::IWorkloadFactory &refWorkloadFactory, const armnn::ITensorHandleFactory &tensorHandleFactory, const armnn::ITensorHandleFactory &refTensorHandleFactory, armnn::ActivationFunction f, unsigned int batchSize)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01314">ActivationTestImpl.cpp:1314</a></div></div>
<div class="ttc" id="_ref_workload_factory_helper_8hpp_xhtml"><div class="ttname"><a href="_ref_workload_factory_helper_8hpp.xhtml">RefWorkloadFactoryHelper.hpp</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a6c39ee38ff9ba4a4d2a773cc59d874d5"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a6c39ee38ff9ba4a4d2a773cc59d874d5">ConstantLinearActivationTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > ConstantLinearActivationTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00378">ActivationTestImpl.cpp:378</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a52def8ec78955ae882f10fac3b627f58"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a52def8ec78955ae882f10fac3b627f58">SimpleSigmoidInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > SimpleSigmoidInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00535">ActivationTestImpl.cpp:535</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa1e34af023adeb7d5f484f8eb4b9826b6">armnn::ActivationFunction::Abs</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa21eebb164e4b8b9bcf64fdb4d8d5dff4">armnn::ActivationFunction::Sigmoid</a></div></div>
<div class="ttc" id="_resolve_type_8hpp_xhtml"><div class="ttname"><a href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a8368a9f279a3480e87c693688686227a"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a8368a9f279a3480e87c693688686227a">ReLuTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > ReLuTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00598">ActivationTestImpl.cpp:598</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a7e6da1965d217931a350ad5f4f3dd772"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a7e6da1965d217931a350ad5f4f3dd772">TanhUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > TanhUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01068">ActivationTestImpl.cpp:1068</a></div></div>
<div class="ttc" id="_activation_fixture_8hpp_xhtml"><div class="ttname"><a href="_activation_fixture_8hpp.xhtml">ActivationFixture.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_ac1ff1b47192a4ae96deca53703c97d56"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#ac1ff1b47192a4ae96deca53703c97d56">SoftReLuTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > SoftReLuTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00656">ActivationTestImpl.cpp:656</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a4458d75c0db21c6abc941cd93a6a24c5"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a4458d75c0db21c6abc941cd93a6a24c5">armnn::IWorkloadFactory::CreateActivation</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateActivation(const ActivationQueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01296">WorkloadFactory.cpp:1296</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00057">WorkloadData.hpp:57</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_abe4ce5ac4300f71f8d1e17df42b73bdf"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#abe4ce5ac4300f71f8d1e17df42b73bdf">SoftReLuUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > SoftReLuUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00700">ActivationTestImpl.cpp:700</a></div></div>
<div class="ttc" id="_numeric_cast_8hpp_xhtml"><div class="ttname"><a href="_numeric_cast_8hpp.xhtml">NumericCast.hpp</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a71ae12f61c946554c49aaa709c81ffa9"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a71ae12f61c946554c49aaa709c81ffa9">SqrtNNTest</a></div><div class="ttdeci">LayerTestResult< float, 5 > SqrtNNTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00841">ActivationTestImpl.cpp:841</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_ab06eef1a3385ff1aa8914372a9e9c3a4"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#ab06eef1a3385ff1aa8914372a9e9c3a4">TanhTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > TanhTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01060">ActivationTestImpl.cpp:1060</a></div></div>
<div class="ttc" id="_tensor_helpers_8hpp_xhtml"><div class="ttname"><a href="_tensor_helpers_8hpp.xhtml">TensorHelpers.hpp</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_af67ae99fbcbf479f21bf9a6a5b20a41c"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#af67ae99fbcbf479f21bf9a6a5b20a41c">TanhInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > TanhInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01076">ActivationTestImpl.cpp:1076</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_ae38ea3540b33a68254857f9031352e71"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#ae38ea3540b33a68254857f9031352e71">SqrtInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > SqrtInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00951">ActivationTestImpl.cpp:951</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_ab265bbfc98785482a41bb9780b6858d0"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#ab265bbfc98785482a41bb9780b6858d0">BoundedReLuUpperAndLowerBoundTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > BoundedReLuUpperAndLowerBoundTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00094">ActivationTestImpl.cpp:94</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a2f0f449bcba656f12e676c7554846626"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a2f0f449bcba656f12e676c7554846626">BoundedReLuInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > BoundedReLuInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00645">ActivationTestImpl.cpp:645</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a587b1550cc5479deb48bbe14c7eded17"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a587b1550cc5479deb48bbe14c7eded17">SquareTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > SquareTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00996">ActivationTestImpl.cpp:996</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_backend_internal_xhtml_a693b40e6b94e958836aeb0410ca186bd"><div class="ttname"><a href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a></div><div class="ttdeci">std::shared_ptr< IMemoryManager > IMemoryManagerSharedPtr</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.xhtml#l00092">IBackendInternal.hpp:92</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a73da7517b63c3a8ea6046124c258e158"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a73da7517b63c3a8ea6046124c258e158">BoundedReLuUpperBoundOnlyTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > BoundedReLuUpperBoundOnlyTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00126">ActivationTestImpl.cpp:126</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a3987d62d2efea44da3ca8e9b1dc3be21"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a3987d62d2efea44da3ca8e9b1dc3be21">AbsTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > AbsTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00781">ActivationTestImpl.cpp:781</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a54c12a6c177195bb8a20876f60db0286"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a54c12a6c177195bb8a20876f60db0286">EluUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > EluUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01132">ActivationTestImpl.cpp:1132</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa6bba7052636d1740303b1b2ef3b53fef"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa6bba7052636d1740303b1b2ef3b53fef">armnn::ActivationFunction::SoftReLu</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00464">Tensor.cpp:464</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a7f39f3c0b73cbfc50b914bc92f9b28aa"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a7f39f3c0b73cbfc50b914bc92f9b28aa">SimpleActivationTest</a></div><div class="ttdeci">LayerTestResult< T, 4 > SimpleActivationTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, armnn::ActivationFunction activationFunction, float activationParameterA, float activationParameterB, float scale, int32_t offset, const std::vector< float > &inputData, float outScale, int32_t outOffset, const std::vector< float > &outputExpectedData)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00407">ActivationTestImpl.cpp:407</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_aa6dccc291eaf62b56655c7ae392f0d25"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#aa6dccc291eaf62b56655c7ae392f0d25">EluTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > EluTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01124">ActivationTestImpl.cpp:1124</a></div></div>
<div class="ttc" id="_assert_8hpp_xhtml_a5698be69cbd5dfe6c28fcd9867e8cbed"><div class="ttname"><a href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a></div><div class="ttdeci">#define ARMNN_ASSERT(COND)</div><div class="ttdef"><b>Definition:</b> <a href="_assert_8hpp_source.xhtml#l00014">Assert.hpp:14</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a45728e94871f867e565a9733bfe685fc"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a45728e94871f867e565a9733bfe685fc">ReLuUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > ReLuUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00590">ActivationTestImpl.cpp:590</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a1199022cc4acee1c6fa906b1ec62d4dc"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a1199022cc4acee1c6fa906b1ec62d4dc">SquareUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > SquareUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01004">ActivationTestImpl.cpp:1004</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a50acd207f416e7df36c17d333b9a0801"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a50acd207f416e7df36c17d333b9a0801">BoundedReLuUint8UpperBoundOnlyTest</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > BoundedReLuUint8UpperBoundOnlyTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00158">ActivationTestImpl.cpp:158</a></div></div>
<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml">armnn::ActivationDescriptor</a></div><div class="ttdoc">An ActivationDescriptor for the ActivationLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00025">Descriptors.hpp:25</a></div></div>
<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaabc5a0f0d6e7cf7fca73299dcd46c0f0d">armnn::ActivationFunction::BoundedReLu</a></div><div class="ttdoc">min(a, max(b, input)) ReLu1 & ReLu6. </div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_af787d7e79d1e8c23c97267a116e934ee"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#af787d7e79d1e8c23c97267a116e934ee">LeakyReLuTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > LeakyReLuTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00755">ActivationTestImpl.cpp:755</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a6612d7fa4a0b57c9495bc4e1f3a274f3"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a6612d7fa4a0b57c9495bc4e1f3a274f3">SqrtTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > SqrtTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00899">ActivationTestImpl.cpp:899</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a102ed5f3b12e4d88645c9cc60820554a"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a102ed5f3b12e4d88645c9cc60820554a">SoftReLuInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > SoftReLuInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00709">ActivationTestImpl.cpp:709</a></div></div>
<div class="ttc" id="struct_layer_test_result_xhtml_ac9d44d346bb7c89f7a7aa31d2bee947f"><div class="ttname"><a href="struct_layer_test_result.xhtml#ac9d44d346bb7c89f7a7aa31d2bee947f">LayerTestResult::output</a></div><div class="ttdeci">boost::multi_array< T, n > output</div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00041">LayerTestResult.hpp:41</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a6e6556796cdc26d6c2d55eab69cf6945"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a6e6556796cdc26d6c2d55eab69cf6945">BoundedReLuUint8UpperAndLowerBoundTest</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > BoundedReLuUint8UpperAndLowerBoundTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00190">ActivationTestImpl.cpp:190</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaaed67cf7d54c570e4c4891800f085f41d"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaed67cf7d54c570e4c4891800f085f41d">armnn::ActivationFunction::Elu</a></div></div>
<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_a017b2990003a014234f13e999dc7c689"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#a017b2990003a014234f13e999dc7c689">armnn::ActivationDescriptor::m_A</a></div><div class="ttdeci">float m_A</div><div class="ttdoc">Alpha upper bound value used by the activation functions. (BoundedReLu, Linear, TanH, Elu). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00050">Descriptors.hpp:50</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_aa56d52a539e33972bb9c9f83be6a3fae"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#aa56d52a539e33972bb9c9f83be6a3fae">SimpleSigmoidUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > SimpleSigmoidUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00526">ActivationTestImpl.cpp:526</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a4e4d43057d33c584cfb9bd3257c0a643"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a4e4d43057d33c584cfb9bd3257c0a643">LeakyReLuTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > LeakyReLuTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00718">ActivationTestImpl.cpp:718</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a4decbf4064f28b31d9e3c14fabc3a56e"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a4decbf4064f28b31d9e3c14fabc3a56e">HardSwishTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > HardSwishTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01150">ActivationTestImpl.cpp:1150</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_i_tensor_handle_factory_8hpp_source.xhtml#l00041">ITensorHandleFactory.hpp:41</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a5f6946f1aa4624ea5c7a707d318586dc"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a5f6946f1aa4624ea5c7a707d318586dc">EluInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > EluInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01140">ActivationTestImpl.cpp:1140</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a1b9b0fb59a485e33724a59b2c1282d91"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a1b9b0fb59a485e33724a59b2c1282d91">EluTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > EluTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01086">ActivationTestImpl.cpp:1086</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a95c71d4f833302b14790ce0755cb1103"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a95c71d4f833302b14790ce0755cb1103">SqrtUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > SqrtUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00943">ActivationTestImpl.cpp:943</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_acac16f9bf4a34a7a07b011a22271668a"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#acac16f9bf4a34a7a07b011a22271668a">SquareInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > SquareInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01013">ActivationTestImpl.cpp:1013</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_ac40efab6398e5afab3383906bcea0b55"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#ac40efab6398e5afab3383906bcea0b55">ReLuInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > ReLuInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00581">ActivationTestImpl.cpp:581</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_ae67353055c8f500c9cf58f686b78a2e0"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#ae67353055c8f500c9cf58f686b78a2e0">ConstantLinearActivationUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > ConstantLinearActivationUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00388">ActivationTestImpl.cpp:388</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a375ca3cff9f1b005d1412dc5f3cf5b6e"><div class="ttname"><a href="namespacearmnn.xhtml#a375ca3cff9f1b005d1412dc5f3cf5b6e">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00035">NumericCast.hpp:35</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaaceb46ca115d05c51aa5a16a8867c3304"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaaceb46ca115d05c51aa5a16a8867c3304">armnn::ActivationFunction::Square</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a3e9280c93340ddc5271fa2bc640763ff"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a3e9280c93340ddc5271fa2bc640763ff">ReLuTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > ReLuTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00545">ActivationTestImpl.cpp:545</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="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div>
<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00030">LayerTestResult.hpp:30</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00480">Tensor.cpp:480</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_afa1af28f33ae8978b6df0b170561f787"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#afa1af28f33ae8978b6df0b170561f787">AbsTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > AbsTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00817">ActivationTestImpl.cpp:817</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a17ab0fa28201a48e6ed1f45eba2aa901"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a17ab0fa28201a48e6ed1f45eba2aa901">BoundedReLuTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > BoundedReLuTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float upperBound, float lowerBound, float inputScale, int32_t inputOffset, float outputScale, int32_t outputOffset, const std::vector< T > &inputData, const std::vector< T > &outputExpectedData, unsigned int inputWidth, unsigned int inputHeight, unsigned int inputChannels, unsigned int inputBatchSize)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00025">ActivationTestImpl.cpp:25</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a6c2c2872c1f72cb6ba1f947de0d1b314"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a6c2c2872c1f72cb6ba1f947de0d1b314">HardSwishTest</a></div><div class="ttdeci">LayerTestResult< float, 4 > HardSwishTest(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01192">ActivationTestImpl.cpp:1192</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a3bcc369772d1cd70007d3078a032dc03"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a3bcc369772d1cd70007d3078a032dc03">HardSwishUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > HardSwishUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01200">ActivationTestImpl.cpp:1200</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_aa21484e44ff8ce2a751654d123fc9d0a"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#aa21484e44ff8ce2a751654d123fc9d0a">AbsInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > AbsInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00833">ActivationTestImpl.cpp:833</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa32a843da6ea40ab3b17a3421ccdf671b">armnn::ActivationFunction::Linear</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa0877e5b3fbe9d7569df6399609ed0186"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa0877e5b3fbe9d7569df6399609ed0186">armnn::ActivationFunction::HardSwish</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a89e93214e6dc3c5616b2351467b0abf9"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a89e93214e6dc3c5616b2351467b0abf9">SquareTestCommon</a></div><div class="ttdeci">LayerTestResult< T, 4 > SquareTestCommon(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory, float qScale, int32_t qOffset)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00960">ActivationTestImpl.cpp:960</a></div></div>
<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_a28c4c9cb15f6be3499abbc46b356060b"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#a28c4c9cb15f6be3499abbc46b356060b">armnn::ActivationDescriptor::m_B</a></div><div class="ttdeci">float m_B</div><div class="ttdoc">Beta lower bound value used by the activation functions. (BoundedReLu, Linear, TanH). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00052">Descriptors.hpp:52</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div>
<div class="ttc" id="structarmnn_1_1_activation_descriptor_xhtml_af10fa7883e3579950f477bee92a64844"><div class="ttname"><a href="structarmnn_1_1_activation_descriptor.xhtml#af10fa7883e3579950f477bee92a64844">armnn::ActivationDescriptor::m_Function</a></div><div class="ttdeci">ActivationFunction m_Function</div><div class="ttdoc">The activation function to use (Sigmoid, TanH, Linear, ReLu, BoundedReLu, SoftReLu, LeakyReLu, Abs, Sqrt, Square, Elu). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l00048">Descriptors.hpp:48</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a60f58fb3975d3fdfb64dfb3279e1e518"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a60f58fb3975d3fdfb64dfb3279e1e518">AbsUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > AbsUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00825">ActivationTestImpl.cpp:825</a></div></div>
<div class="ttc" id="structarmnn_1_1_activation_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_activation_queue_descriptor.xhtml">armnn::ActivationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00148">WorkloadData.hpp:148</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9ea"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9ea">armnn::ActivationFunction</a></div><div class="ttdeci">ActivationFunction</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00056">Types.hpp:56</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_aa3aa2cd4a74c5bbf137fe056e2161c52"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#aa3aa2cd4a74c5bbf137fe056e2161c52">HardSwishInt16Test</a></div><div class="ttdeci">LayerTestResult< int16_t, 4 > HardSwishInt16Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l01209">ActivationTestImpl.cpp:1209</a></div></div>
<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div>
<div class="ttc" id="_activation_test_impl_8cpp_xhtml_a99549cc0465b1493900164f87912f093"><div class="ttname"><a href="_activation_test_impl_8cpp.xhtml#a99549cc0465b1493900164f87912f093">LeakyReLuUint8Test</a></div><div class="ttdeci">LayerTestResult< uint8_t, 4 > LeakyReLuUint8Test(armnn::IWorkloadFactory &workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager, const armnn::ITensorHandleFactory &tensorHandleFactory)</div><div class="ttdef"><b>Definition:</b> <a href="_activation_test_impl_8cpp_source.xhtml#l00763">ActivationTestImpl.cpp:763</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e"><div class="ttname"><a href="namespacearmnn.xhtml#a56297e0f7b215eea46c818cb7528d9eaa23b68da1de2b77d74da9da2635722a3e">armnn::ActivationFunction::TanH</a></div></div>
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