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<div class="title">NeonCreateWorkloadTests.cpp</div> </div>
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<a href="_neon_create_workload_tests_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <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="_neon_workload_factory_helper_8hpp.xhtml">NeonWorkloadFactoryHelper.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="_arm_compute_tensor_utils_8hpp.xhtml">aclCommon/ArmComputeTensorUtils.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_assert_8hpp.xhtml">armnn/utility/Assert.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_ignore_unused_8hpp.xhtml">armnn/utility/IgnoreUnused.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_polymorphic_downcast_8hpp.xhtml">armnn/utility/PolymorphicDowncast.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <<a class="code" href="_mem_copy_workload_8hpp.xhtml">backendsCommon/MemCopyWorkload.hpp</a>></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <<a class="code" href="_create_workload_cl_neon_8hpp.xhtml">aclCommon/test/CreateWorkloadClNeon.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="_neon_workload_factory_8hpp.xhtml">neon/NeonWorkloadFactory.hpp</a>></span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include <<a class="code" href="_neon_tensor_handle_8hpp.xhtml">neon/NeonTensorHandle.hpp</a>></span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include <<a class="code" href="_neon_workload_utils_8hpp.xhtml">neon/workloads/NeonWorkloadUtils.hpp</a>></span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include <<a class="code" href="_neon_workloads_8hpp.xhtml">neon/workloads/NeonWorkloads.hpp</a>></span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(CreateWorkloadNeon)</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> {</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> boost::test_tools::predicate_result CompareIAclTensorHandleShape(<a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* tensorHandle,</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  std::initializer_list<unsigned int> expectedDimensions)</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> {</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keywordflow">return</span> CompareTensorHandleShape<IAclTensorHandle>(tensorHandle, expectedDimensions);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> }</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keywordtype">bool</span> TestNeonTensorHandleInfo(<a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* handle, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& expectedInfo)</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> {</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn_1_1armcomputetensorutils.xhtml">armnn::armcomputetensorutils</a>;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">const</span> arm_compute::ITensorInfo* handleInfo = handle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a326e78519af5570a5921c6aa39968a20">GetTensor</a>().info();</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keyword">const</span> arm_compute::TensorInfo expectedAclInfo = BuildArmComputeTensorInfo(expectedInfo);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordflow">if</span> (handleInfo->data_type() != expectedAclInfo.data_type())</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  {</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  }</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordflow">if</span> (handleInfo->num_dimensions() != expectedAclInfo.num_dimensions())</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  {</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</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> </div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keywordflow">if</span> (handleInfo->quantization_info() != expectedAclInfo.quantization_info())</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  {</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  }</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>  <span class="keywordflow">for</span> (std::size_t d = 0; d < expectedAclInfo.num_dimensions(); ++d)</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  {</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keywordflow">if</span> (handleInfo->dimension(d) != expectedAclInfo.dimension(d))</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  {</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</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> </div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> } <span class="comment">// namespace</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="keyword">template</span> <<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateActivationWorkloadTest()</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> {</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">auto</span> workload = CreateActivationWorkloadTest<NeonActivationWorkload, DataType>(factory, graph);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateActivationWorkloadTest).</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <a class="code" href="structarmnn_1_1_activation_queue_descriptor.xhtml">ActivationQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({1, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({1, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> }</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateActivationFloat16Workload)</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>  NeonCreateActivationWorkloadTest<DataType::Float16>();</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> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00091"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a7906dccbc8d08250fd4d7a79d4d9c722"> 91</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateActivationFloatWorkload)</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>  NeonCreateActivationWorkloadTest<DataType::Float32>();</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> }</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="keyword">template</span> <<span class="keyword">typename</span> WorkloadType,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keyword">typename</span> DescriptorType,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keyword">typename</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>,</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateElementwiseWorkloadTest()</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> {</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> </div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keyword">auto</span> workload = CreateElementwiseWorkloadTest<WorkloadType, DescriptorType, LayerType, DataType>(factory, graph);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  DescriptorType queueDescriptor = workload->GetData();</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keyword">auto</span> inputHandle1 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keyword">auto</span> inputHandle2 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]);</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle1, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle2, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> }</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span> </div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateAdditionFloat16Workload)</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>  NeonCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_neon_addition_workload.xhtml">NeonAdditionWorkload</a>,</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">AdditionQueueDescriptor</a>,</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  <a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>>();</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span> }</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> </div><div class="line"><a name="l00127"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a91343c247a116b44c01af985c72b1e4d"> 127</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateAdditionFloatWorkload)</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> {</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  NeonCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_neon_addition_workload.xhtml">NeonAdditionWorkload</a>,</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">AdditionQueueDescriptor</a>,</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>>();</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> }</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSubtractionFloat16Workload)</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> {</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  NeonCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_neon_subtraction_workload.xhtml">NeonSubtractionWorkload</a>,</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <a class="code" href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">SubtractionQueueDescriptor</a>,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>>();</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> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> </div><div class="line"><a name="l00145"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a18112ff3922073508feb3c25602eace2"> 145</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSubtractionFloatWorkload)</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> {</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  NeonCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_neon_subtraction_workload.xhtml">NeonSubtractionWorkload</a>,</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <a class="code" href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">SubtractionQueueDescriptor</a>,</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>>();</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"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a56236d80e962e94cdc3481f0de4d01ba"> 153</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSubtractionUint8Workload)</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> {</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  NeonCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_neon_subtraction_workload.xhtml">NeonSubtractionWorkload</a>,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <a class="code" href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">SubtractionQueueDescriptor</a>,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>>();</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> }</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateMultiplicationFloat16Workload)</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> {</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  NeonCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_neon_multiplication_workload.xhtml">NeonMultiplicationWorkload</a>,</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <a class="code" href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">MultiplicationQueueDescriptor</a>,</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>,</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>>();</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> }</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div><div class="line"><a name="l00171"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#aa648d27419eef05aace4034b206692bb"> 171</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateMultiplicationFloatWorkload)</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>  NeonCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_neon_multiplication_workload.xhtml">NeonMultiplicationWorkload</a>,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <a class="code" href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">MultiplicationQueueDescriptor</a>,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>,</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>>();</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"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ae5230b6bd0c53c06b7d6a241b7197085"> 179</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateMultiplicationUint8Workload)</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> {</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  NeonCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_neon_multiplication_workload.xhtml">NeonMultiplicationWorkload</a>,</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">MultiplicationQueueDescriptor</a>,</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>,</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>>();</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> }</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div><div class="line"><a name="l00187"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a0c06371a0bca0be0ef80ed2154ff8e34"> 187</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateDivisionFloatWorkloadTest)</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>  NeonCreateElementwiseWorkloadTest<<a class="code" href="classarmnn_1_1_neon_division_workload.xhtml">NeonDivisionWorkload</a>,</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <a class="code" href="structarmnn_1_1_division_queue_descriptor.xhtml">DivisionQueueDescriptor</a>,</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <a class="code" href="classarmnn_1_1_division_layer.xhtml">DivisionLayer</a>,</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>>();</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> }</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> </div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> <span class="keyword">template</span> <<span class="keyword">typename</span> BatchNormalizationWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateBatchNormalizationWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> {</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keyword">auto</span> workload = CreateBatchNormalizationWorkloadTest<BatchNormalizationWorkloadType, DataType></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  (factory, graph, dataLayout);</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">// Checks that outputs and inputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest).</span></div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <a class="code" href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">BatchNormalizationQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</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>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{2, 3, 4, 4} : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{2, 4, 4, 3};</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{2, 3, 4, 4} : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{2, 4, 4, 3};</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> }</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> </div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloat16NchwWorkload)</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>  NeonCreateBatchNormalizationWorkloadTest<NeonBatchNormalizationWorkload, DataType::Float16>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</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> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloat16NhwcWorkload)</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>  NeonCreateBatchNormalizationWorkloadTest<NeonBatchNormalizationWorkload, DataType::Float16>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> }</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> </div><div class="line"><a name="l00229"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ae4e714990000cacf540f2f1da8220120"> 229</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloatNchwWorkload)</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> {</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  NeonCreateBatchNormalizationWorkloadTest<NeonBatchNormalizationWorkload, DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> }</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> </div><div class="line"><a name="l00234"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a16f59a17052dcf58c1e71a70e5aac96f"> 234</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloatNhwcWorkload)</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> {</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  NeonCreateBatchNormalizationWorkloadTest<NeonBatchNormalizationWorkload, DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> }</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> <span class="keyword">template</span> <<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateConvolution2dWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> {</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreateConvolution2dWorkloadTest<NeonConvolution2dWorkload, DataType>(factory, graph, dataLayout);</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>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{2, 3, 8, 16} : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{2, 8, 16, 3};</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{2, 2, 2, 10} : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{2, 2, 10, 2};</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> </div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest).</span></div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <a class="code" href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">Convolution2dQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0]);</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]);</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> }</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> </div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFloat16NchwWorkload)</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>  NeonCreateConvolution2dWorkloadTest<DataType::Float16>();</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> }</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> </div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFloat16NhwcWorkload)</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> {</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  NeonCreateConvolution2dWorkloadTest<DataType::Float16>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</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> </div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00271"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a8a2458d4f6ff9103299e72433245db5b"> 271</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFloatNchwWorkload)</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> {</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  NeonCreateConvolution2dWorkloadTest<DataType::Float32>();</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> }</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> </div><div class="line"><a name="l00276"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a1738342e20abb6bebf8766a796424865"> 276</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFloatNhwcWorkload)</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>  NeonCreateConvolution2dWorkloadTest<DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> }</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> </div><div class="line"><a name="l00281"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ad04c259a5e036c490fa5db7f245cf341"> 281</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFastMathEnabledWorkload)</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="keyword">using</span> <a class="code" href="namespacearmnn.xhtml#a5b6893cda5b69359a4244c06054da18f">ModelOptions</a> = std::vector<BackendOptions>;</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <a class="code" href="namespacearmnn.xhtml#a5b6893cda5b69359a4244c06054da18f">ModelOptions</a> modelOptions = {};</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <a class="code" href="structarmnn_1_1_backend_options.xhtml">BackendOptions</a> cpuAcc(<span class="stringliteral">"CpuAcc"</span>,</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  {</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  { <span class="stringliteral">"FastMathEnabled"</span>, <span class="keyword">true</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>  modelOptions.push_back(cpuAcc);</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager(), modelOptions);</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> </div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keyword">auto</span> workload =</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  CreateConvolution2dWorkloadFastMathTest<NeonConvolution2dWorkload, armnn::DataType::Float32>(factory,</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  graph,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>,</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  modelOptions);</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> </div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(workload != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keyword">auto</span> conv2dWorkload = PolymorphicDowncast<NeonConvolution2dWorkload*>(workload.get());</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(conv2dWorkload);</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(conv2dWorkload != <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <a class="code" href="_assert_8hpp.xhtml#a5698be69cbd5dfe6c28fcd9867e8cbed">ARMNN_ASSERT</a>(conv2dWorkload->GetConvolutionMethod() == arm_compute::ConvolutionMethod::WINOGRAD);</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> }</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> </div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> <span class="keyword">template</span> <<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateDepthWiseConvolutionWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> {</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> </div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  <span class="keyword">auto</span> workload = CreateDepthwiseConvolution2dWorkloadTest<<a class="code" href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml">NeonDepthwiseConvolutionWorkload</a>,</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>>(factory, graph, dataLayout);</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> </div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateNormalizationWorkloadTest).</span></div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <a class="code" href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">DepthwiseConvolution2dQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? std::initializer_list<unsigned int>({ 2, 2, 5, 5 })</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  : std::initializer_list<unsigned int>({ 2, 5, 5, 2 });</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? std::initializer_list<unsigned int>({ 2, 2, 5, 5 })</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  : std::initializer_list<unsigned int>({ 2, 5, 5, 2 });</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> </div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</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> </div><div class="line"><a name="l00331"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ad1d15d5d79ac39eae35bc83bd6ce4475"> 331</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateDepthWiseConvolution2dFloat32NhwcWorkload)</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>  NeonCreateDepthWiseConvolutionWorkloadTest<DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</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> </div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateDepthWiseConvolution2dFloat16NhwcWorkload)</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> {</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  NeonCreateDepthWiseConvolutionWorkloadTest<DataType::Float16>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</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> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span> </div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span> <span class="keyword">template</span> <<span class="keyword">typename</span> FullyConnectedWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateFullyConnectedWorkloadTest()</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> </div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keyword">auto</span> workload = CreateFullyConnectedWorkloadTest<FullyConnectedWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> </div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest).</span></div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <a class="code" href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml">FullyConnectedQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> </div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest).</span></div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordtype">float</span> inputsQScale = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a> ? 1.0f : 0.0;</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="keywordtype">float</span> outputQScale = <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a> ? 2.0f : 0.0;</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({3, 1, 4, 5}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>, inputsQScale)));</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({3, 7}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>, outputQScale)));</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span> }</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> </div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateFullyConnectedFloat16Workload)</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span> {</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  NeonCreateFullyConnectedWorkloadTest<NeonFullyConnectedWorkload, DataType::Float16>();</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> }</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> </div><div class="line"><a name="l00371"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a990cfdd3b638907fc6142c57cae2ab80"> 371</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateFullyConnectedFloatWorkload)</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> {</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  NeonCreateFullyConnectedWorkloadTest<NeonFullyConnectedWorkload, DataType::Float32>();</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> </div><div class="line"><a name="l00376"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a36eb4714d2187b907f920ec02d2b32c5"> 376</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateFullyConnectedQAsymmU8Workload)</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> {</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  NeonCreateFullyConnectedWorkloadTest<NeonFullyConnectedWorkload, DataType::QAsymmU8>();</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> }</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div><div class="line"><a name="l00381"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ada75695cc6dd19b05488205d94e8ef75"> 381</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateFullyConnectedQAsymmS8Workload)</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>  NeonCreateFullyConnectedWorkloadTest<NeonFullyConnectedWorkload, DataType::QAsymmS8>();</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span> }</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> </div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span> <span class="keyword">template</span> <<span class="keyword">typename</span> NormalizationWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateNormalizationWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span> {</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</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="keyword">auto</span> workload = CreateNormalizationWorkloadTest<NormalizationWorkloadType, DataType>(factory, graph, dataLayout);</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> </div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateNormalizationWorkloadTest).</span></div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <a class="code" href="structarmnn_1_1_normalization_queue_descriptor.xhtml">NormalizationQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> </div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{3, 5, 5, 1} : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{3, 1, 5, 5};</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{3, 5, 5, 1} : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{3, 1, 5, 5};</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span> </div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</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> </div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateNormalizationFloat16NchwWorkload)</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span> {</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  NeonCreateNormalizationWorkloadTest<NeonNormalizationFloatWorkload, DataType::Float16>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> }</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span> </div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateNormalizationFloat16NhwcWorkload)</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> {</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  NeonCreateNormalizationWorkloadTest<NeonNormalizationFloatWorkload, DataType::Float16>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span> }</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> </div><div class="line"><a name="l00419"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#af82ae890dad4e4d4383083c11eb30ab6"> 419</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateNormalizationFloatNchwWorkload)</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>  NeonCreateNormalizationWorkloadTest<NeonNormalizationFloatWorkload, DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span> }</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span> </div><div class="line"><a name="l00424"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a255b57d12f38c675e9b7c3f312b45827"> 424</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateNormalizationFloatNhwcWorkload)</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span> {</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  NeonCreateNormalizationWorkloadTest<NeonNormalizationFloatWorkload, DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> }</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> </div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span> </div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span> <span class="keyword">template</span> <<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreatePooling2dWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout = <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>)</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span> {</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keyword">auto</span> workload = CreatePooling2dWorkloadTest<NeonPooling2dWorkload, DataType>(factory, graph, dataLayout);</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> </div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{3, 2, 5, 5} : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{3, 5, 5, 2};</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{3, 2, 2, 4} : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{3, 2, 4, 2};</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span> </div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreatePooling2dWorkloadTest).</span></div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <a class="code" href="structarmnn_1_1_pooling2d_queue_descriptor.xhtml">Pooling2dQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[0]);</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]);</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span> }</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span> </div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dFloat16Workload)</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span> {</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  NeonCreatePooling2dWorkloadTest<DataType::Float16>();</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span> }</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div><div class="line"><a name="l00457"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#af32a90a1a11f2fabc7eb0508325f99e0"> 457</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dFloatNchwWorkload)</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span> {</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  NeonCreatePooling2dWorkloadTest<DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</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> </div><div class="line"><a name="l00462"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a11ff4c042447da348642135ed106597c"> 462</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dFloatNhwcWorkload)</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span> {</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  NeonCreatePooling2dWorkloadTest<DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</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> </div><div class="line"><a name="l00467"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a333b09023558637a4d6654368bccfe34"> 467</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dUint8NchwWorkload)</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span> {</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  NeonCreatePooling2dWorkloadTest<DataType::QAsymmU8>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span> }</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span> </div><div class="line"><a name="l00472"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a45f904a90c0b0cadb62097baaf1dce07"> 472</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dUint8NhwcWorkload)</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span> {</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  NeonCreatePooling2dWorkloadTest<DataType::QAsymmU8>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</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> </div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreatePreluWorkloadTest(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& inputShape,</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& alphaShape,</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>& outputShape,</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> dataType)</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span> {</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span> </div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  <span class="keyword">auto</span> workload = CreatePreluWorkloadTest<NeonPreluWorkload>(factory,</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  graph,</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  inputShape,</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  alphaShape,</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  outputShape,</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  dataType);</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span> </div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest).</span></div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <a class="code" href="structarmnn_1_1_prelu_queue_descriptor.xhtml">PreluQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keyword">auto</span> alphaHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]);</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, dataType)));</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  BOOST_TEST(TestNeonTensorHandleInfo(alphaHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(alphaShape, dataType)));</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, dataType)));</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span> }</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="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreatePreluFloat16Workload)</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span> {</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  NeonCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>);</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span> }</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span> </div><div class="line"><a name="l00510"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ac5559e752bd51c12a4bd1b3b50fa5837"> 510</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreatePreluFloatWorkload)</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span> {</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  NeonCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>);</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span> }</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span> </div><div class="line"><a name="l00515"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a12d17284981e1fff8f0fc76da9293e2c"> 515</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreatePreluUint8Workload)</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span> {</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  NeonCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>);</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span> }</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span> </div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span> <span class="keyword">template</span> <<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateReshapeWorkloadTest()</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span> {</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span> </div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  <span class="keyword">auto</span> workload = CreateReshapeWorkloadTest<NeonReshapeWorkload, DataType>(factory, graph);</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span> </div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest).</span></div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  <a class="code" href="structarmnn_1_1_reshape_queue_descriptor.xhtml">ReshapeQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({4, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({1, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span> }</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span> </div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateReshapeFloat16Workload)</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>  NeonCreateReshapeWorkloadTest<DataType::Float16>();</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span> }</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span> <span class="preprocessor">#endif</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"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a5e917bb46b0281f715abb63b979ccb41"> 544</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateReshapeFloatWorkload)</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span> {</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  NeonCreateReshapeWorkloadTest<DataType::Float32>();</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span> }</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span> </div><div class="line"><a name="l00549"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#aa4153a7dc499db9b5eddfb42976968db"> 549</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateReshapeUint8Workload)</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span> {</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  NeonCreateReshapeWorkloadTest<DataType::QAsymmU8>();</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span> }</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span> </div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span> <span class="keyword">template</span> <<span class="keyword">typename</span> ResizeWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateResizeWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span> {</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  <span class="keyword">auto</span> workload = CreateResizeBilinearWorkloadTest<ResizeWorkloadType, DataType>(factory, graph, dataLayout);</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="keyword">auto</span> queueDescriptor = workload->GetData();</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>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</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">switch</span> (dataLayout)</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  {</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>:</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  BOOST_TEST(CompareIAclTensorHandleShape(inputHandle, { 2, 4, 4, 3 }));</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  BOOST_TEST(CompareIAclTensorHandleShape(outputHandle, { 2, 2, 2, 3 }));</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>:</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  BOOST_TEST(CompareIAclTensorHandleShape(inputHandle, { 2, 3, 4, 4 }));</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  BOOST_TEST(CompareIAclTensorHandleShape(outputHandle, { 2, 3, 2, 2 }));</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  }</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span> }</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span> </div><div class="line"><a name="l00580"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#acecd2490c8eb6763c8500e3ae925c190"> 580</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateResizeFloat32NchwWorkload)</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span> {</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  NeonCreateResizeWorkloadTest<NeonResizeWorkload, armnn::DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span> }</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span> </div><div class="line"><a name="l00585"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ac932bc28ac59c177e36c62e4364735a0"> 585</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateResizeUint8NchwWorkload)</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span> {</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  NeonCreateResizeWorkloadTest<NeonResizeWorkload, armnn::DataType::QAsymmU8>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</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="_neon_create_workload_tests_8cpp.xhtml#a6699397e086ed473ba164574ffbcd2e4"> 590</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateResizeFloat32NhwcWorkload)</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span> {</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  NeonCreateResizeWorkloadTest<NeonResizeWorkload, armnn::DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span> }</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span> </div><div class="line"><a name="l00595"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a455f9af7175c5499cd667cc21b6fd96b"> 595</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateResizeUint8NhwcWorkload)</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>  NeonCreateResizeWorkloadTest<NeonResizeWorkload, armnn::DataType::QAsymmU8>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span> }</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span> </div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span> <span class="keyword">template</span> <<span class="keyword">typename</span> SoftmaxWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateSoftmaxWorkloadTest()</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</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">auto</span> workload = CreateSoftmaxWorkloadTest<SoftmaxWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span> </div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateSoftmaxWorkloadTest).</span></div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <a class="code" href="structarmnn_1_1_softmax_queue_descriptor.xhtml">SoftmaxQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo({4, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>);</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>)</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  {</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  tensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(0);</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  tensorInfo.SetQuantizationScale(1.f / 256);</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  }</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> == <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>)</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>  tensorInfo.SetQuantizationOffset(-128);</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  tensorInfo.SetQuantizationScale(1.f / 256);</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  }</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, tensorInfo));</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, tensorInfo));</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span> }</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> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSoftmaxFloat16Workload)</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>  NeonCreateSoftmaxWorkloadTest<NeonSoftmaxWorkload, DataType::Float16>();</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span> }</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span> </div><div class="line"><a name="l00635"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a49e154c923e22a5d09ae3afa2dee01b4"> 635</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSoftmaxFloatWorkload)</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span> {</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  NeonCreateSoftmaxWorkloadTest<NeonSoftmaxWorkload, DataType::Float32>();</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span> }</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span> </div><div class="line"><a name="l00640"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#aefd296f4bea755c458e645207441a3d0"> 640</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSoftmaxQAsymmU8Workload)</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span> {</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  NeonCreateSoftmaxWorkloadTest<NeonSoftmaxWorkload, DataType::QAsymmU8>();</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="_neon_create_workload_tests_8cpp.xhtml#a17b4b33a309ab1aaf6a800bcbffe914c"> 645</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSoftmaxQAsymmS8Workload)</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span> {</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  NeonCreateSoftmaxWorkloadTest<NeonSoftmaxWorkload, DataType::QAsymmS8>();</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span> }</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="keyword">template</span> <<span class="keyword">typename</span> SpaceToDepthWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonSpaceToDepthWorkloadTest()</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>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span> </div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <span class="keyword">auto</span> workload = CreateSpaceToDepthWorkloadTest<SpaceToDepthWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span> </div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  <a class="code" href="structarmnn_1_1_space_to_depth_queue_descriptor.xhtml">SpaceToDepthQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</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>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 2, 2, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 1, 1, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span> }</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span> </div><div class="line"><a name="l00667"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a1c4700174743960fe55fea9802ca7943"> 667</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthFloat32Workload)</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>  NeonSpaceToDepthWorkloadTest<NeonSpaceToDepthWorkload, armnn::DataType::Float32>();</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span> }</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span> </div><div class="line"><a name="l00672"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a59f3a522fe899842007639e90ced8ef4"> 672</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthFloat16Workload)</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span> {</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  NeonSpaceToDepthWorkloadTest<NeonSpaceToDepthWorkload, armnn::DataType::Float16>();</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span> }</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span> </div><div class="line"><a name="l00677"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a8675faeba30ecf6ea82ed14e7e03e5ab"> 677</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthQAsymm8Workload)</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span> {</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  NeonSpaceToDepthWorkloadTest<NeonSpaceToDepthWorkload, armnn::DataType::QAsymmU8>();</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span> }</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span> </div><div class="line"><a name="l00682"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a43e4abafcf0700a7531d8dc7f27d7eb6"> 682</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthQSymm16Workload)</div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span> {</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  NeonSpaceToDepthWorkloadTest<NeonSpaceToDepthWorkload, armnn::DataType::QSymmS16>();</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span> }</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span> </div><div class="line"><a name="l00687"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a68b8acab2ab427a8939b41aa8c5e0ae7"> 687</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSplitterWorkload)</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span> {</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span> </div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  <span class="keyword">auto</span> workload = CreateSplitterWorkloadTest<NeonSplitterWorkload, DataType::Float32>(factory, graph);</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span> </div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  <span class="comment">// Checks that outputs are as we expect them (see definition of CreateSplitterWorkloadTest).</span></div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  <a class="code" href="structarmnn_1_1_splitter_queue_descriptor.xhtml">SplitterQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({5, 7, 7}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)));</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span> </div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <span class="keyword">auto</span> outputHandle0 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle0, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({1, 7, 7}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)));</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span> </div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <span class="keyword">auto</span> outputHandle1 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]);</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle1, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 7, 7}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)));</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span> </div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  <span class="keyword">auto</span> outputHandle2 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[2]);</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle2, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({2, 7, 7}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)));</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span> }</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span> </div><div class="line"><a name="l00710"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#afebcdbb1621edb19775965935c360131"> 710</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSplitterConcat)</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span> {</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <span class="comment">// Tests that it is possible to decide which output of the splitter layer</span></div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <span class="comment">// should be lined to which input of the concat layer.</span></div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <span class="comment">// We tested that is is possible to specify 0th output</span></div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  <span class="comment">// of the splitter to be the 1st input to the concat, and the 1st output of the splitter to be 0th input</span></div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <span class="comment">// of the concat.</span></div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span> </div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span> </div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <span class="keyword">auto</span> workloads =</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  CreateSplitterConcatWorkloadTest<<a class="code" href="classarmnn_1_1_neon_splitter_workload.xhtml">NeonSplitterWorkload</a>, <a class="code" href="classarmnn_1_1_neon_concat_workload.xhtml">NeonConcatWorkload</a>,</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>>(factory, graph);</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span> </div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  <span class="keyword">auto</span> wlSplitter = std::move(workloads.first);</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  <span class="keyword">auto</span> wlConcat = std::move(workloads.second);</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span> </div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  <span class="comment">//Checks that the index of inputs/outputs matches what we declared on InputDescriptor construction.</span></div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* sOut0 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[0]);</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* sOut1 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[1]);</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* mIn0 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>*<span class="keyword">></span>(wlConcat->GetData().m_Inputs[0]);</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* mIn1 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>*<span class="keyword">></span>(wlConcat->GetData().m_Inputs[1]);</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span> </div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  BOOST_TEST(sOut0);</div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  BOOST_TEST(sOut1);</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  BOOST_TEST(mIn0);</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  BOOST_TEST(mIn1);</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span> </div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span>  <span class="keywordtype">bool</span> validDataPointers = (sOut0 == mIn1) && (sOut1 == mIn0);</div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span> </div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  BOOST_TEST(validDataPointers);</div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span> }</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span> </div><div class="line"><a name="l00745"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ad1867af9782d8dc17efb28c13096f5cf"> 745</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateSingleOutputMultipleInputs)</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span> {</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  <span class="comment">// Tests that it is possible to assign multiple (two) different layers to each of the outputs of a splitter layer.</span></div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  <span class="comment">// We created a splitter with two outputs. That each of those outputs is used by two different activation layers</span></div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span> </div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</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>  std::unique_ptr<NeonSplitterWorkload> wlSplitter;</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  std::unique_ptr<NeonActivationWorkload> wlActiv0_0;</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  std::unique_ptr<NeonActivationWorkload> wlActiv0_1;</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  std::unique_ptr<NeonActivationWorkload> wlActiv1_0;</div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  std::unique_ptr<NeonActivationWorkload> wlActiv1_1;</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>  CreateSplitterMultipleInputsOneOutputWorkloadTest<<a class="code" href="classarmnn_1_1_neon_splitter_workload.xhtml">NeonSplitterWorkload</a>,</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  <a class="code" href="classarmnn_1_1_neon_activation_workload.xhtml">NeonActivationWorkload</a>, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>>(factory, graph, wlSplitter, wlActiv0_0, wlActiv0_1,</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  wlActiv1_0, wlActiv1_1);</div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span> </div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* sOut0 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[0]);</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* sOut1 = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>*<span class="keyword">></span>(wlSplitter->GetData().m_Outputs[1]);</div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* activ0_0Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>*<span class="keyword">></span>(wlActiv0_0->GetData().m_Inputs[0]);</div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* activ0_1Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>*<span class="keyword">></span>(wlActiv0_1->GetData().m_Inputs[0]);</div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* activ1_0Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>*<span class="keyword">></span>(wlActiv1_0->GetData().m_Inputs[0]);</div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>* activ1_1Im = <span class="keyword">dynamic_cast<</span><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a>*<span class="keyword">></span>(wlActiv1_1->GetData().m_Inputs[0]);</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"> 772</span>  BOOST_TEST(sOut0);</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  BOOST_TEST(sOut1);</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  BOOST_TEST(activ0_0Im);</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  BOOST_TEST(activ0_1Im);</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  BOOST_TEST(activ1_0Im);</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  BOOST_TEST(activ1_1Im);</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>  <span class="keywordtype">bool</span> validDataPointers = (sOut0 == activ0_0Im) && (sOut0 == activ0_1Im) &&</div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  (sOut1 == activ1_0Im) && (sOut1 == activ1_1Im);</div><div class="line"><a name="l00781"></a><span class="lineno"> 781</span> </div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  BOOST_TEST(validDataPointers);</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span> }</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span> </div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span> <span class="preprocessor">#if defined(ARMNNREF_ENABLED)</span></div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span> </div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span> <span class="comment">// This test unit needs the reference backend, it's not available if the reference backend is not built</span></div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span> </div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateMemCopyWorkloadsNeon)</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span> {</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  CreateMemCopyWorkloads<IAclTensorHandle>(factory);</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> </div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span> <span class="preprocessor">#endif</span></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="keyword">template</span> <<span class="keyword">typename</span> L2NormalizationWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateL2NormalizationWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span> {</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span> </div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <span class="keyword">auto</span> workload =</div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  CreateL2NormalizationWorkloadTest<L2NormalizationWorkloadType, DataType>(factory, graph, dataLayout);</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span> </div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateNormalizationWorkloadTest).</span></div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  <a class="code" href="structarmnn_1_1_l2_normalization_queue_descriptor.xhtml">L2NormalizationQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span> </div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ?</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{ 5, 20, 50, 67 } : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{ 5, 50, 67, 20 };</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == <a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ?</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{ 5, 20, 50, 67 } : <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>{ 5, 50, 67, 20 };</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span> </div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span> }</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="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationFloat16NchwWorkload)</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span> {</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  NeonCreateL2NormalizationWorkloadTest<NeonL2NormalizationFloatWorkload, DataType::Float16>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span> }</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span> </div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationFloat16NhwcWorkload)</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>  NeonCreateL2NormalizationWorkloadTest<NeonL2NormalizationFloatWorkload, DataType::Float16>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</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> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span> </div><div class="line"><a name="l00834"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#adbe5208a88359f30446c5de9a790d5f3"> 834</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationNchwWorkload)</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span> {</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  NeonCreateL2NormalizationWorkloadTest<NeonL2NormalizationFloatWorkload, DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</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> </div><div class="line"><a name="l00839"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#af9acbac7fe022ed53ada8e6aa135e4fa"> 839</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationNhwcWorkload)</div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span> {</div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  NeonCreateL2NormalizationWorkloadTest<NeonL2NormalizationFloatWorkload, DataType::Float32>(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span> }</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span> </div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span> <span class="keyword">template</span> <<span class="keyword">typename</span> LogSoftmaxWorkloadType, <span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateLogSoftmaxWorkloadTest()</div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span> {</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span> </div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <span class="keyword">auto</span> workload = CreateLogSoftmaxWorkloadTest<LogSoftmaxWorkloadType, DataType>(factory, graph);</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span> </div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateLogSoftmaxWorkloadTest).</span></div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  <a class="code" href="structarmnn_1_1_log_softmax_queue_descriptor.xhtml">LogSoftmaxQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo({4, 1}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>);</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>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, tensorInfo));</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, tensorInfo));</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> </div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateLogSoftmaxFloat16Workload)</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span> {</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  NeonCreateLogSoftmaxWorkloadTest<NeonLogSoftmaxWorkload, DataType::Float16>();</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span> }</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span> </div><div class="line"><a name="l00870"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ae3c59f61513ac1da8a40a02d05f2befc"> 870</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateLogSoftmaxFloatWorkload)</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span> {</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  NeonCreateLogSoftmaxWorkloadTest<NeonLogSoftmaxWorkload, DataType::Float32>();</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> </div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span> <span class="keyword">template</span> <<span class="keyword">typename</span> LstmWorkloadType></div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateLstmWorkloadTest()</div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span> {</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span> </div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  <span class="keyword">auto</span> workload = CreateLstmWorkloadTest<LstmWorkloadType>(factory, graph);</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span> </div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  <a class="code" href="structarmnn_1_1_lstm_queue_descriptor.xhtml">LstmQueueDescriptor</a> queueDescriptor = workload->GetData();</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>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]);</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span> </div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 2, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)));</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 2, 4 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>)));</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> </div><div class="line"><a name="l00893"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a15cb5d6986ed78434fa442039242b3fe"> 893</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateLSTMWorkloadFloatWorkload)</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>  NeonCreateLstmWorkloadTest<NeonLstmFloatWorkload>();</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> <<span class="keyword">typename</span> ConcatWorkloadType, armnn::DataType DataType></div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateConcatWorkloadTest(std::initializer_list<unsigned int> outputShape,</div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> concatAxis)</div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span> {</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreateConcatWorkloadTest<ConcatWorkloadType, DataType>(factory, graph, outputShape, concatAxis);</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span> </div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  <a class="code" href="structarmnn_1_1_concat_queue_descriptor.xhtml">ConcatQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  <span class="keyword">auto</span> inputHandle0 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  <span class="keyword">auto</span> inputHandle1 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]);</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</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>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle0, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 2, 3, 2, 5 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle1, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 2, 3, 2, 5 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span> }</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span> </div><div class="line"><a name="l00918"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a8782f9dbea0bfb27baa047d5c961ff3e"> 918</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim0Float32Workload)</div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span> {</div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  NeonCreateConcatWorkloadTest<NeonConcatWorkload, armnn::DataType::Float32>({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span> }</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span> </div><div class="line"><a name="l00923"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a6e908cfa4b2b0d235a7a83bb450af212"> 923</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim1Float32Workload)</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span> {</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  NeonCreateConcatWorkloadTest<NeonConcatWorkload, armnn::DataType::Float32>({ 2, 6, 2, 5 }, 1);</div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span> }</div><div class="line"><a name="l00927"></a><span class="lineno"> 927</span> </div><div class="line"><a name="l00928"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a15c6731388ff09e4fb01e12100138e40"> 928</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim3Float32Workload)</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span> {</div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  NeonCreateConcatWorkloadTest<NeonConcatWorkload, armnn::DataType::Float32>({ 2, 3, 2, 10 }, 3);</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span> }</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span> </div><div class="line"><a name="l00933"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ab4f6f715f63bf06d9bb87a21e77f2129"> 933</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim0Uint8Workload)</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span> {</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  NeonCreateConcatWorkloadTest<NeonConcatWorkload, armnn::DataType::QAsymmU8>({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span> }</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span> </div><div class="line"><a name="l00938"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#ad76e3bac3ab907f6ebf516ca8f40ad49"> 938</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim1Uint8Workload)</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>  NeonCreateConcatWorkloadTest<NeonConcatWorkload, armnn::DataType::QAsymmU8>({ 2, 6, 2, 5 }, 1);</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="_neon_create_workload_tests_8cpp.xhtml#a41bdcd447af6e0fe880fd6c746830468"> 943</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim3Uint8Workload)</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span> {</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  NeonCreateConcatWorkloadTest<NeonConcatWorkload, armnn::DataType::QAsymmU8>({ 2, 3, 2, 10 }, 3);</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span> }</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="keyword">template</span> <armnn::DataType DataType></div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateStackWorkloadTest(<span class="keyword">const</span> std::initializer_list<unsigned int>& inputShape,</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  <span class="keyword">const</span> std::initializer_list<unsigned int>& outputShape,</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axis,</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs)</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span> {</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory =</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreateStackWorkloadTest<NeonStackWorkload, DataType>(factory,</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  graph,</div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(inputShape),</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>(outputShape),</div><div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  axis,</div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span>  numInputs);</div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span> </div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  <span class="comment">// Check inputs and output are as expected</span></div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  <a class="code" href="structarmnn_1_1_stack_queue_descriptor.xhtml">StackQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < numInputs; ++i)</div><div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  {</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  <span class="keyword">auto</span> inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[i]);</div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  }</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  <span class="keyword">auto</span> outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span> }</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span> </div><div class="line"><a name="l00976"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a72d6262ab8544dbfa7cfc22910e3011c"> 976</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateStackFloat32Workload)</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span> {</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  NeonCreateStackWorkloadTest<armnn::DataType::Float32>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span> }</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span> </div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateStackFloat16Workload)</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span> {</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  NeonCreateStackWorkloadTest<armnn::DataType::Float16>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span> }</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span> </div><div class="line"><a name="l00988"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a966e80d9fbe654c47b44265d982d3c33"> 988</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateStackUint8Workload)</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span> {</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  NeonCreateStackWorkloadTest<armnn::DataType::QAsymmU8>({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span> }</div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span> </div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span> <span class="keyword">template</span> <<span class="keyword">typename</span> QuantizedLstmWorkloadType></div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateQuantizedLstmWorkloadTest()</div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span> {</div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory = NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span> </div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span>  <span class="keyword">auto</span> workload = CreateQuantizedLstmWorkloadTest<QuantizedLstmWorkloadType>(factory, graph);</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>  <a class="code" href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml">QuantizedLstmQueueDescriptor</a> queueDescriptor = workload->GetData();</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>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>  BOOST_TEST((inputHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 2})));</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  BOOST_TEST((inputHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QASYMM8));</div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span> </div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* cellStateInHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]);</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  BOOST_TEST((cellStateInHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  BOOST_TEST((cellStateInHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QSYMM16));</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span> </div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* outputStateInHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[2]);</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  BOOST_TEST((outputStateInHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  BOOST_TEST((outputStateInHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QASYMM8));</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span> </div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* cellStateOutHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  BOOST_TEST((cellStateOutHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  BOOST_TEST((cellStateOutHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QSYMM16));</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span> </div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* outputStateOutHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]);</div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>  BOOST_TEST((outputStateOutHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  BOOST_TEST((outputStateOutHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QASYMM8));</div><div class="line"><a name="l01022"></a><span class="lineno"> 1022</span> }</div><div class="line"><a name="l01023"></a><span class="lineno"> 1023</span> </div><div class="line"><a name="l01024"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#aed3a050eccd0708a65889e9fd33a8cbd"> 1024</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateQuantizedLstmWorkload)</div><div class="line"><a name="l01025"></a><span class="lineno"> 1025</span> {</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>  NeonCreateQuantizedLstmWorkloadTest<NeonQuantizedLstmWorkload>();</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span> }</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> <span class="keyword">template</span> <<span class="keyword">typename</span> QLstmWorkloadType></div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span> <span class="keyword">static</span> <span class="keywordtype">void</span> NeonCreateQLstmWorkloadTest()</div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span> {</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>  <a class="code" href="classarmnn_1_1_neon_workload_factory.xhtml">NeonWorkloadFactory</a> factory = NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager());</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>  <span class="keyword">auto</span> workload = CreateQLstmWorkloadTest<QLstmWorkloadType>(factory, graph);</div><div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>  <a class="code" href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml">QLstmQueueDescriptor</a> queueDescriptor = workload->GetData();</div><div class="line"><a name="l01037"></a><span class="lineno"> 1037</span> </div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>  BOOST_TEST((inputHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>  BOOST_TEST((inputHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QASYMM8_SIGNED));</div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span> </div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* cellStateOutHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]);</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  BOOST_TEST((cellStateOutHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>  BOOST_TEST((cellStateOutHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QSYMM16));</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>  <a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml">IAclTensorHandle</a>* outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[2]);</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  BOOST_TEST((outputHandle-><a class="code" href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">GetShape</a>() == <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a>({2, 4})));</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>  BOOST_TEST((outputHandle-><a class="code" href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">GetDataType</a>() == arm_compute::DataType::QASYMM8_SIGNED));</div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span> }</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span> </div><div class="line"><a name="l01051"></a><span class="lineno"><a class="line" href="_neon_create_workload_tests_8cpp.xhtml#a7bfad4da743703b05cfc0a4691759543"> 1051</a></span> <a class="code" href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">BOOST_AUTO_TEST_CASE</a>(CreateQLstmWorkloadTest)</div><div class="line"><a name="l01052"></a><span class="lineno"> 1052</span> {</div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  NeonCreateQLstmWorkloadTest<NeonQLstmWorkload>();</div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span> }</div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span> </div><div class="line"><a name="l01056"></a><span class="lineno"> 1056</span> <a class="code" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a>()</div><div class="ttc" id="structarmnn_1_1_multiplication_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">armnn::MultiplicationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00246">WorkloadData.hpp:246</a></div></div>
<div class="ttc" id="_output_shape_of_squeeze_8cpp_xhtml_ae3a6cb217a792718f2bd0e8f45e3ca9e"><div class="ttname"><a href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)</div></div>
<div class="ttc" id="_mem_copy_workload_8hpp_xhtml"><div class="ttname"><a href="_mem_copy_workload_8hpp.xhtml">MemCopyWorkload.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_neon_subtraction_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_subtraction_workload.xhtml">armnn::NeonSubtractionWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_subtraction_workload_8hpp_source.xhtml#l00024">NeonSubtractionWorkload.hpp:24</a></div></div>
<div class="ttc" id="_ignore_unused_8hpp_xhtml"><div class="ttname"><a href="_ignore_unused_8hpp.xhtml">IgnoreUnused.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_neon_division_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_division_workload.xhtml">armnn::NeonDivisionWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_division_workload_8hpp_source.xhtml#l00020">NeonDivisionWorkload.hpp:20</a></div></div>
<div class="ttc" id="classarmnn_1_1_neon_depthwise_convolution_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_depthwise_convolution_workload.xhtml">armnn::NeonDepthwiseConvolutionWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_depthwise_convolution_workload_8hpp_source.xhtml#l00026">NeonDepthwiseConvolutionWorkload.hpp:26</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_acl_tensor_handle_xhtml_a326e78519af5570a5921c6aa39968a20"><div class="ttname"><a href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a326e78519af5570a5921c6aa39968a20">armnn::IAclTensorHandle::GetTensor</a></div><div class="ttdeci">virtual arm_compute::ITensor & GetTensor()=0</div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">armnn::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00050">Types.hpp:50</a></div></div>
<div class="ttc" id="classarmnn_1_1_neon_concat_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_concat_workload.xhtml">armnn::NeonConcatWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_concat_workload_8hpp_source.xhtml#l00022">NeonConcatWorkload.hpp:22</a></div></div>
<div class="ttc" id="_neon_workloads_8hpp_xhtml"><div class="ttname"><a href="_neon_workloads_8hpp.xhtml">NeonWorkloads.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_splitter_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_splitter_queue_descriptor.xhtml">armnn::SplitterQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00101">WorkloadData.hpp:101</a></div></div>
<div class="ttc" id="structarmnn_1_1_quantized_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_quantized_lstm_queue_descriptor.xhtml">armnn::QuantizedLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00604">WorkloadData.hpp:604</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="namespacearmnn_xhtml_a5b6893cda5b69359a4244c06054da18f"><div class="ttname"><a href="namespacearmnn.xhtml#a5b6893cda5b69359a4244c06054da18f">armnn::ModelOptions</a></div><div class="ttdeci">std::vector< BackendOptions > ModelOptions</div><div class="ttdef"><b>Definition:</b> <a href="_backend_options_8hpp_source.xhtml#l00017">BackendOptions.hpp:17</a></div></div>
<div class="ttc" id="classarmnn_1_1_neon_multiplication_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_multiplication_workload.xhtml">armnn::NeonMultiplicationWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_multiplication_workload_8hpp_source.xhtml#l00023">NeonMultiplicationWorkload.hpp:23</a></div></div>
<div class="ttc" id="_neon_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_neon_tensor_handle_8hpp.xhtml">NeonTensorHandle.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_stack_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_stack_queue_descriptor.xhtml">armnn::StackQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00142">WorkloadData.hpp:142</a></div></div>
<div class="ttc" id="_arm_compute_tensor_utils_8hpp_xhtml"><div class="ttname"><a href="_arm_compute_tensor_utils_8hpp.xhtml">ArmComputeTensorUtils.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div>
<div class="ttc" id="structarmnn_1_1_addition_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_addition_queue_descriptor.xhtml">armnn::AdditionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00240">WorkloadData.hpp:240</a></div></div>
<div class="ttc" id="classarmnn_1_1_neon_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_workload_factory.xhtml">armnn::NeonWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_factory_8hpp_source.xhtml#l00020">NeonWorkloadFactory.hpp:20</a></div></div>
<div class="ttc" id="structarmnn_1_1_fully_connected_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_fully_connected_queue_descriptor.xhtml">armnn::FullyConnectedQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00165">WorkloadData.hpp:165</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="structarmnn_1_1_prelu_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_prelu_queue_descriptor.xhtml">armnn::PreluQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00529">WorkloadData.hpp:529</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_acl_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_acl_tensor_handle.xhtml">armnn::IAclTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_tensor_handle_8hpp_source.xhtml#l00016">ArmComputeTensorHandle.hpp:16</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="structarmnn_1_1_softmax_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_softmax_queue_descriptor.xhtml">armnn::SoftmaxQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00095">WorkloadData.hpp:95</a></div></div>
<div class="ttc" id="structarmnn_1_1_division_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_division_queue_descriptor.xhtml">armnn::DivisionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00252">WorkloadData.hpp:252</a></div></div>
<div class="ttc" id="structarmnn_1_1_subtraction_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">armnn::SubtractionQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00258">WorkloadData.hpp:258</a></div></div>
<div class="ttc" id="structarmnn_1_1_concat_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_concat_queue_descriptor.xhtml">armnn::ConcatQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00120">WorkloadData.hpp:120</a></div></div>
<div class="ttc" id="_create_workload_cl_neon_8hpp_xhtml"><div class="ttname"><a href="_create_workload_cl_neon_8hpp.xhtml">CreateWorkloadClNeon.hpp</a></div></div>
<div class="ttc" id="structarmnn_1_1_space_to_depth_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_space_to_depth_queue_descriptor.xhtml">armnn::SpaceToDepthQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00377">WorkloadData.hpp:377</a></div></div>
<div class="ttc" id="_polymorphic_downcast_8hpp_xhtml"><div class="ttname"><a href="_polymorphic_downcast_8hpp.xhtml">PolymorphicDowncast.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_acl_tensor_handle_xhtml_a3767f569fc55323ddf7b2ee57987d9c5"><div class="ttname"><a href="classarmnn_1_1_i_acl_tensor_handle.xhtml#a3767f569fc55323ddf7b2ee57987d9c5">armnn::IAclTensorHandle::GetDataType</a></div><div class="ttdeci">virtual arm_compute::DataType GetDataType() const =0</div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00032">Types.hpp:32</a></div></div>
<div class="ttc" id="structarmnn_1_1_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_lstm_queue_descriptor.xhtml">armnn::LstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00387">WorkloadData.hpp:387</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a></div></div>
<div class="ttc" id="_neon_workload_factory_helper_8hpp_xhtml"><div class="ttname"><a href="_neon_workload_factory_helper_8hpp.xhtml">NeonWorkloadFactoryHelper.hpp</a></div></div>
<div class="ttc" id="_neon_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_neon_workload_utils_8hpp.xhtml">NeonWorkloadUtils.hpp</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="namespacearmnn_xhtml_a10d15f3df1ab52b3b915a4be1dbf386b"><div class="ttname"><a href="namespacearmnn.xhtml#a10d15f3df1ab52b3b915a4be1dbf386b">armnn::BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)</div><div class="ttdef"><b>Definition:</b> <a href="_const_tensor_layer_visitor_8cpp_source.xhtml#l00268">ConstTensorLayerVisitor.cpp:268</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_tensor_handle_xhtml_affd5aae75cad90f472f96cfd25a13f29"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle.xhtml#affd5aae75cad90f472f96cfd25a13f29">armnn::ITensorHandle::GetShape</a></div><div class="ttdeci">virtual TensorShape GetShape() const =0</div><div class="ttdoc">Get the number of elements for each dimension ordered from slowest iterating dimension to fastest ite...</div></div>
<div class="ttc" id="classarmnn_1_1_neon_activation_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_activation_workload.xhtml">armnn::NeonActivationWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_activation_workload_8hpp_source.xhtml#l00020">NeonActivationWorkload.hpp:20</a></div></div>
<div class="ttc" id="classarmnn_1_1_graph_xhtml"><div class="ttname"><a href="classarmnn_1_1_graph.xhtml">armnn::Graph</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_8hpp_source.xhtml#l00029">Graph.hpp:29</a></div></div>
<div class="ttc" id="classarmnn_1_1_addition_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_addition_layer.xhtml">armnn::AdditionLayer</a></div><div class="ttdoc">This layer represents an addition operation. </div><div class="ttdef"><b>Definition:</b> <a href="_addition_layer_8hpp_source.xhtml#l00013">AdditionLayer.hpp:13</a></div></div>
<div class="ttc" id="structarmnn_1_1_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_convolution2d_queue_descriptor.xhtml">armnn::Convolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00192">WorkloadData.hpp:192</a></div></div>
<div class="ttc" id="structarmnn_1_1_backend_options_xhtml"><div class="ttname"><a href="structarmnn_1_1_backend_options.xhtml">armnn::BackendOptions</a></div><div class="ttdoc">Struct for the users to pass backend specific options. </div><div class="ttdef"><b>Definition:</b> <a href="_backend_options_8hpp_source.xhtml#l00020">BackendOptions.hpp:20</a></div></div>
<div class="ttc" id="_assert_8hpp_xhtml"><div class="ttname"><a href="_assert_8hpp.xhtml">Assert.hpp</a></div></div>
<div class="ttc" id="_profiler_tests_8cpp_xhtml_af7f71af5c6c124222dd1c42c5df892f4"><div class="ttname"><a href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END</a></div><div class="ttdeci">BOOST_AUTO_TEST_SUITE_END()</div></div>
<div class="ttc" id="classarmnn_1_1_subtraction_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_subtraction_layer.xhtml">armnn::SubtractionLayer</a></div><div class="ttdoc">This layer represents a subtraction operation. </div><div class="ttdef"><b>Definition:</b> <a href="_subtraction_layer_8hpp_source.xhtml#l00014">SubtractionLayer.hpp:14</a></div></div>
<div class="ttc" id="structarmnn_1_1_l2_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_l2_normalization_queue_descriptor.xhtml">armnn::L2NormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00345">WorkloadData.hpp:345</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00031">WorkloadData.hpp:31</a></div></div>
<div class="ttc" id="structarmnn_1_1_q_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_q_lstm_queue_descriptor.xhtml">armnn::QLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00552">WorkloadData.hpp:552</a></div></div>
<div class="ttc" id="structarmnn_1_1_batch_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_batch_normalization_queue_descriptor.xhtml">armnn::BatchNormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00293">WorkloadData.hpp:293</a></div></div>
<div class="ttc" id="classarmnn_1_1_division_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_division_layer.xhtml">armnn::DivisionLayer</a></div><div class="ttdoc">This layer represents a division operation. </div><div class="ttdef"><b>Definition:</b> <a href="_division_layer_8hpp_source.xhtml#l00014">DivisionLayer.hpp:14</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
<div class="ttc" id="classarmnn_1_1_neon_splitter_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_splitter_workload.xhtml">armnn::NeonSplitterWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_splitter_workload_8hpp_source.xhtml#l00022">NeonSplitterWorkload.hpp:22</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="classarmnn_1_1_neon_addition_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_neon_addition_workload.xhtml">armnn::NeonAdditionWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_neon_addition_workload_8hpp_source.xhtml#l00022">NeonAdditionWorkload.hpp:22</a></div></div>
<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00030">WorkloadData.hpp:30</a></div></div>
<div class="ttc" id="_neon_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_neon_workload_factory_8hpp.xhtml">NeonWorkloadFactory.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">armnn::DataLayout::NCHW</a></div></div>
<div class="ttc" id="structarmnn_1_1_pooling2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_pooling2d_queue_descriptor.xhtml">armnn::Pooling2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00186">WorkloadData.hpp:186</a></div></div>
<div class="ttc" id="classarmnn_1_1_multiplication_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_multiplication_layer.xhtml">armnn::MultiplicationLayer</a></div><div class="ttdoc">This layer represents a multiplication operation. </div><div class="ttdef"><b>Definition:</b> <a href="_multiplication_layer_8hpp_source.xhtml#l00014">MultiplicationLayer.hpp:14</a></div></div>
<div class="ttc" id="namespacearmnn_1_1armcomputetensorutils_xhtml"><div class="ttname"><a href="namespacearmnn_1_1armcomputetensorutils.xhtml">armnn::armcomputetensorutils</a></div><div class="ttdef"><b>Definition:</b> <a href="_arm_compute_tensor_utils_8cpp_source.xhtml#l00013">ArmComputeTensorUtils.cpp:13</a></div></div>
<div class="ttc" id="structarmnn_1_1_log_softmax_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_log_softmax_queue_descriptor.xhtml">armnn::LogSoftmaxQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00350">WorkloadData.hpp:350</a></div></div>
<div class="ttc" id="structarmnn_1_1_reshape_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_reshape_queue_descriptor.xhtml">armnn::ReshapeQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00367">WorkloadData.hpp:367</a></div></div>
<div class="ttc" id="structarmnn_1_1_depthwise_convolution2d_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_depthwise_convolution2d_queue_descriptor.xhtml">armnn::DepthwiseConvolution2dQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00207">WorkloadData.hpp:207</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_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">armnn::DataLayout::NHWC</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdoc">When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00419">Types.hpp:419</a></div></div>
<div class="ttc" id="structarmnn_1_1_normalization_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_normalization_queue_descriptor.xhtml">armnn::NormalizationQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00234">WorkloadData.hpp:234</a></div></div>
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