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<div class="title">RefCreateWorkloadTests.cpp</div> </div>
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<a href="_ref_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>&#160;<span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;</div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_create_workload_8hpp.xhtml">test/CreateWorkload.hpp</a>&gt;</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;</div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_ref_tensor_handle_8hpp.xhtml">reference/RefTensorHandle.hpp</a>&gt;</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_ref_workload_factory_8hpp.xhtml">reference/RefWorkloadFactory.hpp</a>&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_ref_workloads_8hpp.xhtml">reference/workloads/RefWorkloads.hpp</a>&gt;</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;</div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="keyword">namespace</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;{</div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Workload&gt;</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="keywordtype">void</span> CheckInputOutput(std::unique_ptr&lt;Workload&gt; workload, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; inputInfo, <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; outputInfo)</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;{</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; <span class="keyword">auto</span> queueDescriptor = workload-&gt;GetData();</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; BOOST_TEST((inputHandle-&gt;GetTensorInfo() == inputInfo));</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; BOOST_TEST((outputHandle-&gt;GetTensorInfo() == outputInfo));</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;}</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Workload&gt;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="keywordtype">void</span> CheckInputsOutput(std::unique_ptr&lt;Workload&gt; workload,</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; inputInfo0,</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; inputInfo1,</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>&amp; outputInfo)</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;{</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <span class="keyword">auto</span> queueDescriptor = workload-&gt;GetData();</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; <span class="keyword">auto</span> inputHandle0 = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keyword">auto</span> inputHandle1 = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Inputs[1]);</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; BOOST_TEST((inputHandle0-&gt;GetTensorInfo() == inputInfo0));</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; BOOST_TEST((inputHandle1-&gt;GetTensorInfo() == inputInfo1));</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; BOOST_TEST((outputHandle-&gt;GetTensorInfo() == outputInfo));</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;}</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;<a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">armnn::RefWorkloadFactory</a> GetFactory()</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160;{</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; std::shared_ptr&lt;RefMemoryManager&gt; memoryManager = std::make_shared&lt;RefMemoryManager&gt;();</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <span class="keywordflow">return</span> <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a>(memoryManager);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;}</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160;}</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;<a class="code" href="_output_shape_of_squeeze_8cpp.xhtml#ae3a6cb217a792718f2bd0e8f45e3ca9e">BOOST_AUTO_TEST_SUITE</a>(CreateWorkloadRef)</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> ActivationWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateActivationWorkloadTest()</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160;{</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="keyword">auto</span> workload = CreateActivationWorkloadTest&lt;ActivationWorkloadType, DataType&gt;(factory, graph);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="comment">// Checks that outputs are as we expect them (see definition of CreateActivationWorkloadTest).</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <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="l00061"></a><span class="lineno"> 61</span>&#160; <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="l00062"></a><span class="lineno"> 62</span>&#160;}</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9"> 64</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateActivationFloat32Workload)</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160;{</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; RefCreateActivationWorkloadTest&lt;RefActivationWorkload, armnn::DataType::Float32&gt;();</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160;}</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160;</div><div class="line"><a name="l00069"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a8622e3bde188ef5c79024290da5c9ecb"> 69</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateActivationUint8Workload)</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;{</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; RefCreateActivationWorkloadTest&lt;RefActivationWorkload, armnn::DataType::QAsymmU8&gt;();</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160;}</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> WorkloadType,</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <span class="keyword">typename</span> DescriptorType,</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keyword">typename</span> <a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">LayerType</a>,</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>&gt;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateElementwiseWorkloadTest()</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160;{</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="keyword">auto</span> workload = CreateElementwiseWorkloadTest&lt;WorkloadType, DescriptorType, LayerType, DataType&gt;(</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; factory, graph);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; CheckInputsOutput(std::move(workload),</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <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="l00087"></a><span class="lineno"> 87</span>&#160; <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="l00088"></a><span class="lineno"> 88</span>&#160; <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="l00089"></a><span class="lineno"> 89</span>&#160;}</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160;</div><div class="line"><a name="l00091"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a91343c247a116b44c01af985c72b1e4d"> 91</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateAdditionFloatWorkload)</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160;{</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a7a9d365fbb868d53e67c4cdfdbf9cf7e">RefAdditionWorkload</a>,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">AdditionQueueDescriptor</a>,</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>&gt;();</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160;}</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160;</div><div class="line"><a name="l00099"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a272deaaf10839290c46ad4931cbe89db"> 99</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateAdditionUint8Workload)</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160;{</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a7a9d365fbb868d53e67c4cdfdbf9cf7e">RefAdditionWorkload</a>,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">AdditionQueueDescriptor</a>,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>&gt;();</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160;}</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160;</div><div class="line"><a name="l00107"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ab69409ef77bd36d828dad3b4b9b6f6b2"> 107</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateAdditionInt16Workload)</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160;{</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a7a9d365fbb868d53e67c4cdfdbf9cf7e">RefAdditionWorkload</a>,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; <a class="code" href="structarmnn_1_1_addition_queue_descriptor.xhtml">AdditionQueueDescriptor</a>,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <a class="code" href="classarmnn_1_1_addition_layer.xhtml">AdditionLayer</a>,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>&gt;();</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160;}</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160;</div><div class="line"><a name="l00115"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a04720c3eed6925141aac4468024fe077"> 115</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSubtractionFloat32Workload)</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160;{</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a01853f5d02495c04636016c1e3e7c144">RefSubtractionWorkload</a>,</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <a class="code" href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">SubtractionQueueDescriptor</a>,</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>,</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>&gt;();</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160;}</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160;</div><div class="line"><a name="l00123"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a5f8370f733e76f8b7de20d2152be1bfd"> 123</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSubtractionFloat16Workload)</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160;{</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a01853f5d02495c04636016c1e3e7c144">RefSubtractionWorkload</a>,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <a class="code" href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">SubtractionQueueDescriptor</a>,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>,</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>&gt;();</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160;}</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160;</div><div class="line"><a name="l00131"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a56236d80e962e94cdc3481f0de4d01ba"> 131</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSubtractionUint8Workload)</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160;{</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a01853f5d02495c04636016c1e3e7c144">RefSubtractionWorkload</a>,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <a class="code" href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">SubtractionQueueDescriptor</a>,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; <a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>&gt;();</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160;}</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160;</div><div class="line"><a name="l00139"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ad9ea48a7b8317731ccc17c096fb4e717"> 139</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSubtractionInt16Workload)</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160;{</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a01853f5d02495c04636016c1e3e7c144">RefSubtractionWorkload</a>,</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; <a class="code" href="structarmnn_1_1_subtraction_queue_descriptor.xhtml">SubtractionQueueDescriptor</a>,</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <a class="code" href="classarmnn_1_1_subtraction_layer.xhtml">SubtractionLayer</a>,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>&gt;();</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160;}</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160;</div><div class="line"><a name="l00147"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aa648d27419eef05aace4034b206692bb"> 147</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateMultiplicationFloatWorkload)</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160;{</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#aabff736a576814611f65ce1a14600a17">RefMultiplicationWorkload</a>,</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <a class="code" href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">MultiplicationQueueDescriptor</a>,</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>&gt;();</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160;}</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160;</div><div class="line"><a name="l00155"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ae5230b6bd0c53c06b7d6a241b7197085"> 155</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateMultiplicationUint8Workload)</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160;{</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#aabff736a576814611f65ce1a14600a17">RefMultiplicationWorkload</a>,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; <a class="code" href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">MultiplicationQueueDescriptor</a>,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; <a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>&gt;();</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160;}</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160;</div><div class="line"><a name="l00163"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ad5a322045505d8d860a22c27124450e0"> 163</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateMultiplicationInt16Workload)</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160;{</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#aabff736a576814611f65ce1a14600a17">RefMultiplicationWorkload</a>,</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; <a class="code" href="structarmnn_1_1_multiplication_queue_descriptor.xhtml">MultiplicationQueueDescriptor</a>,</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; <a class="code" href="classarmnn_1_1_multiplication_layer.xhtml">MultiplicationLayer</a>,</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>&gt;();</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160;}</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160;</div><div class="line"><a name="l00171"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a4ee8ff90da474e10de9bc16e30d4371f"> 171</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateDivisionFloat32Workload)</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160;{</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a5c3a2aa3adc87d79164914b63f27dc25">RefDivisionWorkload</a>,</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; <a class="code" href="structarmnn_1_1_division_queue_descriptor.xhtml">DivisionQueueDescriptor</a>,</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <a class="code" href="classarmnn_1_1_division_layer.xhtml">DivisionLayer</a>,</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>&gt;();</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160;}</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160;</div><div class="line"><a name="l00179"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a4879b55fbb91b51eff4658017db4d52b"> 179</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateDivisionFloat16Workload)</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160;{</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a5c3a2aa3adc87d79164914b63f27dc25">RefDivisionWorkload</a>,</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; <a class="code" href="structarmnn_1_1_division_queue_descriptor.xhtml">DivisionQueueDescriptor</a>,</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160; <a class="code" href="classarmnn_1_1_division_layer.xhtml">DivisionLayer</a>,</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>&gt;();</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160;}</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160;</div><div class="line"><a name="l00187"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#acc127e63cab0137b8646324a1920ea08"> 187</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateDivisionUint8Workload)</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>&#160;{</div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a5c3a2aa3adc87d79164914b63f27dc25">RefDivisionWorkload</a>,</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160; <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>&#160; <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>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>&gt;();</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160;}</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160;</div><div class="line"><a name="l00195"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a9cf5cf702dea9e8cc18b856969c5a9ff"> 195</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateDivisionInt16Workload)</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160;{</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; RefCreateElementwiseWorkloadTest&lt;<a class="code" href="namespacearmnn.xhtml#a5c3a2aa3adc87d79164914b63f27dc25">RefDivisionWorkload</a>,</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; <a class="code" href="structarmnn_1_1_division_queue_descriptor.xhtml">DivisionQueueDescriptor</a>,</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; <a class="code" href="classarmnn_1_1_division_layer.xhtml">DivisionLayer</a>,</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>&gt;();</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160;}</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160;</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> BatchNormalizationWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateBatchNormalizationWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160;{</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; <span class="keyword">auto</span> workload = CreateBatchNormalizationWorkloadTest&lt;BatchNormalizationWorkloadType, DataType&gt;(factory,</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; graph,</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; dataLayout);</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160;</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape;</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape;</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160;</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; {</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; inputShape = { 2, 4, 4, 3 };</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; outputShape = { 2, 4, 4, 3 };</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; <span class="keywordflow">default</span>:</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; inputShape = { 2, 3, 4, 4 };</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; outputShape = { 2, 3, 4, 4 };</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; }</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160;</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest).</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; CheckInputOutput(std::move(workload), <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>), <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="l00230"></a><span class="lineno"> 230</span>&#160;}</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160;</div><div class="line"><a name="l00232"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ab941b94da3362c927dc5832b49fffe92"> 232</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloat32Workload)</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160;{</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; RefCreateBatchNormalizationWorkloadTest&lt;RefBatchNormalizationWorkload,armnn::DataType::Float32&gt;</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; (DataLayout::NCHW);</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>&#160;}</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>&#160;</div><div class="line"><a name="l00238"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#abb4205da6dcd9c8111324f7c592becae"> 238</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloat32WorkloadNhwc)</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160;{</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; RefCreateBatchNormalizationWorkloadTest&lt;RefBatchNormalizationWorkload, armnn::DataType::Float32&gt;</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; (DataLayout::NHWC);</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160;}</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160;</div><div class="line"><a name="l00244"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ae6aaea75a9c06ecf746f060db5e312bf"> 244</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloat16Workload)</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160;{</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; RefCreateBatchNormalizationWorkloadTest&lt;RefBatchNormalizationWorkload,armnn::DataType::Float16&gt;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; (DataLayout::NCHW);</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>&#160;}</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>&#160;</div><div class="line"><a name="l00250"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aa88277834d3cd0570537d2fa2c47ffcf"> 250</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationFloat16WorkloadNhwc)</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>&#160;{</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>&#160; RefCreateBatchNormalizationWorkloadTest&lt;RefBatchNormalizationWorkload, armnn::DataType::Float16&gt;</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; (DataLayout::NHWC);</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160;}</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160;</div><div class="line"><a name="l00256"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ab927f6f0c661830d3a8da5d1b2b9874b"> 256</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationUint8Workload)</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160;{</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; RefCreateBatchNormalizationWorkloadTest&lt;RefBatchNormalizationWorkload, armnn::DataType::QAsymmU8&gt;</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; (DataLayout::NCHW);</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160;}</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>&#160;</div><div class="line"><a name="l00262"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aaa98b0b574f1231232753c0a173e9044"> 262</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationUint8WorkloadNhwc)</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160;{</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; RefCreateBatchNormalizationWorkloadTest&lt;RefBatchNormalizationWorkload, armnn::DataType::QAsymmU8&gt;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; (DataLayout::NHWC);</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160;}</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160;</div><div class="line"><a name="l00268"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#acbb8b2035830a03a7db7422181834792"> 268</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationInt16Workload)</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160;{</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; RefCreateBatchNormalizationWorkloadTest&lt;RefBatchNormalizationWorkload, armnn::DataType::QSymmS16&gt;</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; (DataLayout::NCHW);</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160;}</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>&#160;</div><div class="line"><a name="l00274"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a0d07b555444749c6778952ad8d5f1d90"> 274</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchNormalizationInt16WorkloadNhwc)</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160;{</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; RefCreateBatchNormalizationWorkloadTest&lt;RefBatchNormalizationWorkload, armnn::DataType::QSymmS16&gt;</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160; (DataLayout::NHWC);</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160;}</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160;</div><div class="line"><a name="l00280"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a2cd48cbae79d394f79c0c7acc456c436"> 280</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConvertFp16ToFp32Float32Workload)</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160;{</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; <span class="keyword">auto</span> workload = CreateConvertFp16ToFp32WorkloadTest&lt;RefConvertFp16ToFp32Workload&gt;(factory, graph);</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>&#160;</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them</span></div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; CheckInputOutput(</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; std::move(workload), <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({1, 3, 2, 3}, DataType::Float16), <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({1, 3, 2, 3}, DataType::Float32));</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160;}</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160;</div><div class="line"><a name="l00291"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ae45acf3d80e9e982acb8a5e8a22bfbd4"> 291</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConvertFp32ToFp16Float16Workload)</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160;{</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; <span class="keyword">auto</span> workload = CreateConvertFp32ToFp16WorkloadTest&lt;RefConvertFp32ToFp16Workload&gt;(factory, graph);</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them</span></div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; CheckInputOutput(</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; std::move(workload), <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({1, 3, 2, 3}, DataType::Float32), <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({1, 3, 2, 3}, DataType::Float16));</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160;}</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160;</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateConvolution2dWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout = DataLayout::NCHW)</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160;{</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; <span class="keyword">auto</span> workload = CreateConvolution2dWorkloadTest&lt;RefConvolution2dWorkload, DataType::Float32&gt;</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; (factory, graph, dataLayout);</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160;</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list&lt;unsigned int&gt;({2, 3, 8, 16})</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160; : std::initializer_list&lt;unsigned int&gt;({2, 8, 16, 3});</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list&lt;unsigned int&gt;({2, 2, 2, 10})</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160; : std::initializer_list&lt;unsigned int&gt;({2, 2, 10, 2});</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160;</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest).</span></div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, DataType::Float32),</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, DataType::Float32));</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>&#160;}</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>&#160;</div><div class="line"><a name="l00320"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a8a2458d4f6ff9103299e72433245db5b"> 320</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFloatNchwWorkload)</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>&#160;{</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>&#160; RefCreateConvolution2dWorkloadTest(DataLayout::NCHW);</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160;}</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>&#160;</div><div class="line"><a name="l00325"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a1738342e20abb6bebf8766a796424865"> 325</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConvolution2dFloatNhwcWorkload)</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>&#160;{</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>&#160; RefCreateConvolution2dWorkloadTest(DataLayout::NHWC);</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>&#160;}</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>&#160;</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateDepthwiseConvolutionWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160;{</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160; <span class="keyword">auto</span> workload = CreateDepthwiseConvolution2dWorkloadTest&lt;RefDepthwiseConvolution2dWorkload, DataType::Float32&gt;</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; (factory, graph, dataLayout);</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160;</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list&lt;unsigned int&gt;({ 2, 2, 5, 5 })</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; : std::initializer_list&lt;unsigned int&gt;({ 2, 5, 5, 2 });</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list&lt;unsigned int&gt;({ 2, 2, 5, 5 })</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; : std::initializer_list&lt;unsigned int&gt;({ 2, 5, 5, 2 });</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160;</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; <span class="comment">// Checks that inputs/outputs are as we expect them (see definition of CreateDepthwiseConvolution2dWorkloadTest).</span></div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, DataType::Float32),</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, DataType::Float32));</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160;}</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160;</div><div class="line"><a name="l00348"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ac96201c573891d4b179bf38af48a5fe5"> 348</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateDepthwiseConvolutionFloat32NhwcWorkload)</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160;{</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>&#160; RefCreateDepthwiseConvolutionWorkloadTest(DataLayout::NHWC);</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>&#160;}</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>&#160;</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> FullyConnectedWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateFullyConnectedWorkloadTest()</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>&#160;{</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>&#160; <span class="keyword">auto</span> workload = CreateFullyConnectedWorkloadTest&lt;FullyConnectedWorkloadType, DataType&gt;(factory, graph);</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>&#160;</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest).</span></div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>&#160; <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="l00362"></a><span class="lineno"> 362</span>&#160; <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="l00363"></a><span class="lineno"> 363</span>&#160; CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>&#160; <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="l00365"></a><span class="lineno"> 365</span>&#160; <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="l00366"></a><span class="lineno"> 366</span>&#160;}</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>&#160;</div><div class="line"><a name="l00368"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ac8d03744a709d27fde75e3e649cd7928"> 368</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateFullyConnectedWorkloadFloat32)</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>&#160;{</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>&#160; RefCreateFullyConnectedWorkloadTest&lt;RefFullyConnectedWorkload, armnn::DataType::Float32&gt;();</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>&#160;}</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>&#160;</div><div class="line"><a name="l00373"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a16b1fedc3b195f7641947bf5adc3dfae"> 373</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateFullyConnectedWorkloadQuantisedAsymm8)</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>&#160;{</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>&#160; RefCreateFullyConnectedWorkloadTest&lt;RefFullyConnectedWorkload, armnn::DataType::QAsymmU8&gt;();</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>&#160;}</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>&#160;</div><div class="line"><a name="l00378"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a9d96fd0c00a5920eb39a6b1c1dd91cd8"> 378</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateFullyConnectedWorkloadQuantisedSymm16)</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>&#160;{</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>&#160; RefCreateFullyConnectedWorkloadTest&lt;RefFullyConnectedWorkload, armnn::DataType::QSymmS16&gt;();</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>&#160;}</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>&#160;</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> NormalizationWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateNormalizationWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>&#160;{</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>&#160; <span class="keyword">auto</span> workload = CreateNormalizationWorkloadTest&lt;NormalizationWorkloadType, DataType&gt;(factory, graph, dataLayout);</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>&#160;</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape;</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape;</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>&#160;</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>&#160; <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>&#160; {</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>&#160; <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>&#160; inputShape = { 3, 1, 5, 5 };</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>&#160; outputShape = { 3, 1, 5, 5 };</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>&#160; <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>&#160; <span class="keywordflow">default</span>:</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>&#160; inputShape = { 3, 5, 5, 1 };</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>&#160; outputShape = { 3, 5, 5, 1 };</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>&#160; }</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>&#160;</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateNormalizationWorkloadTest).</span></div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>&#160; CheckInputOutput(std::move(workload), <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>), <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="l00408"></a><span class="lineno"> 408</span>&#160;}</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>&#160;</div><div class="line"><a name="l00410"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a1ff5ef9e4f21ed637b5f5c36889b49db"> 410</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateRefNormalizationFloat32NchwWorkload)</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>&#160;{</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>&#160; RefCreateNormalizationWorkloadTest&lt;RefNormalizationWorkload, armnn::DataType::Float32&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>&#160;}</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>&#160;</div><div class="line"><a name="l00415"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a489c80fd4209261c63dc4c6eb13adf82"> 415</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateRefNormalizationFloat32NhwcWorkload)</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>&#160;{</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span>&#160; RefCreateNormalizationWorkloadTest&lt;RefNormalizationWorkload, armnn::DataType::Float32&gt;(DataLayout::NHWC);</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>&#160;}</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>&#160;</div><div class="line"><a name="l00420"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a396d25919b4db95efc8163e5480eca41"> 420</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateRefNormalizationUint8NchwWorkload)</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>&#160;{</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>&#160; RefCreateNormalizationWorkloadTest&lt;RefNormalizationWorkload, armnn::DataType::QAsymmU8&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>&#160;}</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>&#160;</div><div class="line"><a name="l00425"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a8c3fd8a88966553acc63f26d55363392"> 425</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateRefNormalizationUint8NhwcWorkload)</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>&#160;{</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>&#160; RefCreateNormalizationWorkloadTest&lt;RefNormalizationWorkload, armnn::DataType::QAsymmU8&gt;(DataLayout::NHWC);</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>&#160;}</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>&#160;</div><div class="line"><a name="l00430"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a75adb0f986194f819918e15e9d056457"> 430</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateRefNormalizationInt16NchwWorkload)</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>&#160;{</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>&#160; RefCreateNormalizationWorkloadTest&lt;RefNormalizationWorkload, armnn::DataType::QSymmS16&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>&#160;}</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>&#160;</div><div class="line"><a name="l00435"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ab569bdd2d6d978c142800ddce8b63b45"> 435</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateRefNormalizationInt16NhwcWorkload)</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>&#160;{</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>&#160; RefCreateNormalizationWorkloadTest&lt;RefNormalizationWorkload, armnn::DataType::QSymmS16&gt;(DataLayout::NHWC);</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span>&#160;}</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>&#160;</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Pooling2dWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreatePooling2dWorkloadTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>&#160;{</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>&#160; <span class="keyword">auto</span> workload = CreatePooling2dWorkloadTest&lt;Pooling2dWorkloadType, DataType&gt;(factory, graph, dataLayout);</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>&#160;</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape;</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape;</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>&#160;</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>&#160; <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>&#160; {</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>&#160; <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>&#160; inputShape = { 3, 5, 5, 2 };</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>&#160; outputShape = { 3, 2, 4, 2 };</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>&#160; <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>&#160; <span class="keywordflow">default</span>:</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>&#160; inputShape = { 3, 2, 5, 5 };</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>&#160; outputShape = { 3, 2, 2, 4 };</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>&#160; }</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>&#160;</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreatePooling2dWorkloadTest).</span></div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>&#160; CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>&#160; <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="l00465"></a><span class="lineno"> 465</span>&#160; <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="l00466"></a><span class="lineno"> 466</span>&#160;}</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>&#160;</div><div class="line"><a name="l00468"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ac4446c616fa4040bfeeca1f7f9358633"> 468</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dFloat32Workload)</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>&#160;{</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>&#160; RefCreatePooling2dWorkloadTest&lt;RefPooling2dWorkload, armnn::DataType::Float32&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>&#160;}</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>&#160;</div><div class="line"><a name="l00473"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a594ea40c9b86061d10a2c80e4816a16e"> 473</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dFloat32NhwcWorkload)</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>&#160;{</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>&#160; RefCreatePooling2dWorkloadTest&lt;RefPooling2dWorkload, armnn::DataType::Float32&gt;(DataLayout::NHWC);</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>&#160;}</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>&#160;</div><div class="line"><a name="l00478"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aa1b2456a24a3dde7961cc8dee29eabf0"> 478</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dUint8Workload)</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>&#160;{</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>&#160; RefCreatePooling2dWorkloadTest&lt;RefPooling2dWorkload, armnn::DataType::QAsymmU8&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>&#160;}</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>&#160;</div><div class="line"><a name="l00483"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a45f904a90c0b0cadb62097baaf1dce07"> 483</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dUint8NhwcWorkload)</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>&#160;{</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>&#160; RefCreatePooling2dWorkloadTest&lt;RefPooling2dWorkload, armnn::DataType::QAsymmU8&gt;(DataLayout::NHWC);</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>&#160;}</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>&#160;</div><div class="line"><a name="l00488"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aa991974c576c289dea888237919a9e96"> 488</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dInt16Workload)</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>&#160;{</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>&#160; RefCreatePooling2dWorkloadTest&lt;RefPooling2dWorkload, armnn::DataType::QSymmS16&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>&#160;}</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>&#160;</div><div class="line"><a name="l00493"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aed0bef0163150d327fd07491e6842e1f"> 493</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePooling2dInt16NhwcWorkload)</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>&#160;{</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>&#160; RefCreatePooling2dWorkloadTest&lt;RefPooling2dWorkload, armnn::DataType::QSymmS16&gt;(DataLayout::NHWC);</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>&#160;}</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>&#160;</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> SoftmaxWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateSoftmaxWorkloadTest()</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>&#160;{</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>&#160; <span class="keyword">auto</span> workload = CreateSoftmaxWorkloadTest&lt;SoftmaxWorkloadType, DataType&gt;(factory, graph);</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>&#160;</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateSoftmaxWorkloadTest).</span></div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>&#160; CheckInputOutput(</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>&#160; std::move(workload),</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>&#160; <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="l00509"></a><span class="lineno"> 509</span>&#160; <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="l00510"></a><span class="lineno"> 510</span>&#160;}</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>&#160;</div><div class="line"><a name="l00512"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a1dd9876913e311bf87443aa0709d09ad"> 512</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSoftmaxFloat32Workload)</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>&#160;{</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>&#160; RefCreateSoftmaxWorkloadTest&lt;RefSoftmaxWorkload, armnn::DataType::Float32&gt;();</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>&#160;}</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>&#160;</div><div class="line"><a name="l00517"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a7d00a3e31deb447b0e818d09c4e2c122"> 517</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSoftmaxFloat16Workload)</div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>&#160;{</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>&#160; RefCreateSoftmaxWorkloadTest&lt;RefSoftmaxWorkload, armnn::DataType::Float16&gt;();</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>&#160;}</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>&#160;</div><div class="line"><a name="l00522"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a16715fe6153bb6b5b20b2b7ec7104b4a"> 522</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSoftmaxQuantisedAsymm8Workload)</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>&#160;{</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>&#160; RefCreateSoftmaxWorkloadTest&lt;RefSoftmaxWorkload, armnn::DataType::QAsymmU8&gt;();</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>&#160;}</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>&#160;</div><div class="line"><a name="l00527"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a64ccd24d1bd6ed8e04444e9fc020ab6e"> 527</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSoftmaxQuantisedSymm16Workload)</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>&#160;{</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>&#160; RefCreateSoftmaxWorkloadTest&lt;RefSoftmaxWorkload, armnn::DataType::QSymmS16&gt;();</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>&#160;}</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>&#160;</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> SplitterWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateSplitterWorkloadTest()</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>&#160;{</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>&#160; <span class="keyword">auto</span> workload = CreateSplitterWorkloadTest&lt;SplitterWorkloadType, DataType&gt;(factory, graph);</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>&#160;</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>&#160; <span class="comment">// Checks that outputs are as we expect them (see definition of CreateSplitterWorkloadTest).</span></div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>&#160; <a class="code" href="structarmnn_1_1_splitter_queue_descriptor.xhtml">SplitterQueueDescriptor</a> queueDescriptor = workload-&gt;GetData();</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>&#160; <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Inputs[0]);</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>&#160; BOOST_TEST((inputHandle-&gt;GetTensorInfo() == <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 5, 7, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>&#160;</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>&#160; <span class="keyword">auto</span> outputHandle0 = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>&#160; BOOST_TEST((outputHandle0-&gt;GetTensorInfo() == <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 7, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>&#160;</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>&#160; <span class="keyword">auto</span> outputHandle1 = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Outputs[1]);</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>&#160; BOOST_TEST((outputHandle1-&gt;GetTensorInfo() == <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 2, 7, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>&#160;</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>&#160; <span class="keyword">auto</span> outputHandle2 = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Outputs[2]);</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>&#160; BOOST_TEST((outputHandle2-&gt;GetTensorInfo() == <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 2, 7, 7 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>)));</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>&#160;}</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>&#160;</div><div class="line"><a name="l00554"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a5d79d058ed3ce5f796386364969e2581"> 554</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSplitterFloat32Workload)</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>&#160;{</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>&#160; RefCreateSplitterWorkloadTest&lt;RefSplitterWorkload, armnn::DataType::Float32&gt;();</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>&#160;}</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>&#160;</div><div class="line"><a name="l00559"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a856e926d6587c6025a56faa2ae276c03"> 559</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSplitterFloat16Workload)</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>&#160;{</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>&#160; RefCreateSplitterWorkloadTest&lt;RefSplitterWorkload, armnn::DataType::Float16&gt;();</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>&#160;}</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>&#160;</div><div class="line"><a name="l00564"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a73620793bccf4f93947feea2a810d413"> 564</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSplitterUint8Workload)</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>&#160;{</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>&#160; RefCreateSplitterWorkloadTest&lt;RefSplitterWorkload, armnn::DataType::QAsymmU8&gt;();</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>&#160;}</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>&#160;</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> SplitterWorkloadType, <span class="keyword">typename</span> ConcatWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateSplitterConcatWorkloadTest()</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>&#160;{</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>&#160; <span class="comment">// Tests that it is possible to decide which output of the splitter layer</span></div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>&#160; <span class="comment">// should be lined to which input of the concat layer.</span></div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>&#160; <span class="comment">// We tested that is is possible to specify 0th output</span></div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>&#160; <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="l00576"></a><span class="lineno"> 576</span>&#160; <span class="comment">// of the concat.</span></div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>&#160;</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>&#160; <span class="keyword">auto</span> workloads = CreateSplitterConcatWorkloadTest&lt;SplitterWorkloadType, ConcatWorkloadType, DataType&gt;</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>&#160; (factory, graph);</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>&#160;</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>&#160; <span class="keyword">auto</span> wlSplitter = std::move(workloads.first);</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>&#160; <span class="keyword">auto</span> wlConcat = std::move(workloads.second);</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>&#160;</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>&#160; <span class="comment">//Checks that the index of inputs/outputs matches what we declared on InputDescriptor construction.</span></div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>&#160; <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* sOut0 = <span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">&gt;</span>(wlSplitter-&gt;GetData().m_Outputs[0]);</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>&#160; <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* sOut1 = <span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">&gt;</span>(wlSplitter-&gt;GetData().m_Outputs[1]);</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>&#160; <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* mIn0 = <span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">&gt;</span>(wlConcat-&gt;GetData().m_Inputs[0]);</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>&#160; <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* mIn1 = <span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">&gt;</span>(wlConcat-&gt;GetData().m_Inputs[1]);</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>&#160;</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>&#160; BOOST_TEST(sOut0);</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>&#160; BOOST_TEST(sOut1);</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>&#160; BOOST_TEST(mIn0);</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>&#160; BOOST_TEST(mIn1);</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>&#160;</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>&#160; <span class="keywordtype">bool</span> validDataPointers = (sOut0 == mIn1) &amp;&amp; (sOut1 == mIn0);</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>&#160;</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>&#160; BOOST_TEST(validDataPointers);</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>&#160;}</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>&#160;</div><div class="line"><a name="l00602"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a9b9b53471a49d63214ba072f1b213fa4"> 602</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSplitterConcatFloat32)</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>&#160;{</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>&#160; RefCreateSplitterConcatWorkloadTest&lt;RefSplitterWorkload, RefConcatWorkload, DataType::Float32&gt;();</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>&#160;}</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>&#160;</div><div class="line"><a name="l00607"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a949cc47e492ce11302f0ffdeeb7c70ca"> 607</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSplitterConcatFloat16)</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>&#160;{</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>&#160; RefCreateSplitterConcatWorkloadTest&lt;RefSplitterWorkload, RefConcatWorkload, DataType::Float16&gt;();</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>&#160;}</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>&#160;</div><div class="line"><a name="l00612"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aa03822e48c0af312c65f8ed819d164b6"> 612</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSplitterConcatUint8)</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>&#160;{</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>&#160; RefCreateSplitterConcatWorkloadTest&lt;RefSplitterWorkload, RefConcatWorkload, DataType::QAsymmU8&gt;();</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>&#160;}</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>&#160;</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> SplitterWorkloadType, <span class="keyword">typename</span> ActivationWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateSingleOutputMultipleInputsTest()</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>&#160;{</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>&#160; <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="l00621"></a><span class="lineno"> 621</span>&#160; <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="l00622"></a><span class="lineno"> 622</span>&#160;</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>&#160; std::unique_ptr&lt;SplitterWorkloadType&gt; wlSplitter;</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>&#160; std::unique_ptr&lt;ActivationWorkloadType&gt; wlActiv0_0;</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span>&#160; std::unique_ptr&lt;ActivationWorkloadType&gt; wlActiv0_1;</div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>&#160; std::unique_ptr&lt;ActivationWorkloadType&gt; wlActiv1_0;</div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>&#160; std::unique_ptr&lt;ActivationWorkloadType&gt; wlActiv1_1;</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>&#160;</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>&#160; CreateSplitterMultipleInputsOneOutputWorkloadTest&lt;SplitterWorkloadType,</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>&#160; ActivationWorkloadType, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>&gt;(factory, graph, wlSplitter, wlActiv0_0, wlActiv0_1, wlActiv1_0, wlActiv1_1);</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>&#160;</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>&#160; <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* sOut0 = <span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">&gt;</span>(wlSplitter-&gt;GetData().m_Outputs[0]);</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span>&#160; <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* sOut1 = <span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">&gt;</span>(wlSplitter-&gt;GetData().m_Outputs[1]);</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span>&#160; <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* activ0_0Im = <span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">&gt;</span>(wlActiv0_0-&gt;GetData().m_Inputs[0]);</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>&#160; <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* activ0_1Im = <span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">&gt;</span>(wlActiv0_1-&gt;GetData().m_Inputs[0]);</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>&#160; <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* activ1_0Im = <span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">&gt;</span>(wlActiv1_0-&gt;GetData().m_Inputs[0]);</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>&#160; <a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>* activ1_1Im = <span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a>*<span class="keyword">&gt;</span>(wlActiv1_1-&gt;GetData().m_Inputs[0]);</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>&#160;</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>&#160;</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>&#160; BOOST_TEST(sOut0);</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>&#160; BOOST_TEST(sOut1);</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>&#160; BOOST_TEST(activ0_0Im);</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>&#160; BOOST_TEST(activ0_1Im);</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>&#160; BOOST_TEST(activ1_0Im);</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>&#160; BOOST_TEST(activ1_1Im);</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span>&#160;</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>&#160; <span class="keywordtype">bool</span> validDataPointers = (sOut0 == activ0_0Im) &amp;&amp; (sOut0 == activ0_1Im) &amp;&amp;</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>&#160; (sOut1 == activ1_0Im) &amp;&amp; (sOut1 == activ1_1Im);</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span>&#160;</div><div class="line"><a name="l00652"></a><span class="lineno"> 652</span>&#160; BOOST_TEST(validDataPointers);</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>&#160;}</div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>&#160;</div><div class="line"><a name="l00655"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a168a7c8cf3d6baee1e61dc24832ac33f"> 655</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSingleOutputMultipleInputsFloat32)</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>&#160;{</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>&#160; RefCreateSingleOutputMultipleInputsTest&lt;<a class="code" href="classarmnn_1_1_ref_splitter_workload.xhtml">RefSplitterWorkload</a>, <a class="code" href="classarmnn_1_1_ref_activation_workload.xhtml">RefActivationWorkload</a>,</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>&gt;();</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>&#160;}</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>&#160;</div><div class="line"><a name="l00661"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#abf9fe44992f18b9501bbce9d7b19cdbe"> 661</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSingleOutputMultipleInputsUint8)</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>&#160;{</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>&#160; RefCreateSingleOutputMultipleInputsTest&lt;<a class="code" href="classarmnn_1_1_ref_splitter_workload.xhtml">RefSplitterWorkload</a>, <a class="code" href="classarmnn_1_1_ref_activation_workload.xhtml">RefActivationWorkload</a>,</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>&gt;();</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>&#160;}</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>&#160;</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> ResizeBilinearWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateResizeBilinearTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>&#160;{</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span>&#160; <span class="keyword">auto</span> workload = CreateResizeBilinearWorkloadTest&lt;ResizeBilinearWorkloadType, DataType&gt;(factory, graph, dataLayout);</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>&#160;</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape;</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape;</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>&#160;</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span>&#160; <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span>&#160; {</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>&#160; <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>&#160; inputShape = { 2, 4, 4, 3 };</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>&#160; outputShape = { 2, 2, 2, 3 };</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>&#160; <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>&#160; <span class="keywordflow">default</span>:</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>&#160; inputShape = { 2, 3, 4, 4 };</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span>&#160; outputShape = { 2, 3, 2, 2 };</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>&#160; }</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>&#160;</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateResizeBilinearWorkloadTest).</span></div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span>&#160; CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>&#160; <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="l00692"></a><span class="lineno"> 692</span>&#160; <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="l00693"></a><span class="lineno"> 693</span>&#160;}</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>&#160;</div><div class="line"><a name="l00695"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ad4530438508a0bb641649c558e19c89d"> 695</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateResizeBilinearFloat32)</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>&#160;{</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>&#160; RefCreateResizeBilinearTest&lt;RefResizeWorkload, armnn::DataType::Float32&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>&#160;}</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>&#160;</div><div class="line"><a name="l00700"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a701b321d642e2a1ecc2ed1792de717c3"> 700</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateResizeBilinearFloat16)</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>&#160;{</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>&#160; RefCreateResizeBilinearTest&lt;RefResizeWorkload, armnn::DataType::Float16&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>&#160;}</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>&#160;</div><div class="line"><a name="l00705"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a92781a1fe6584ff5ef611c6c4cdecc57"> 705</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateResizeBilinearUint8)</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>&#160;{</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>&#160; RefCreateResizeBilinearTest&lt;RefResizeWorkload, armnn::DataType::QAsymmU8&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>&#160;}</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>&#160;</div><div class="line"><a name="l00710"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ae72ce3fcfbf1ab16d24b14c59c4a4743"> 710</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateResizeBilinearQuantisedAsymm16)</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>&#160;{</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>&#160; RefCreateResizeBilinearTest&lt;RefResizeWorkload, armnn::DataType::QSymmS16&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>&#160;}</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>&#160;</div><div class="line"><a name="l00715"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a21967bb06657ebcef9e3ed6dbfd4a04b"> 715</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateResizeBilinearFloat32Nhwc)</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>&#160;{</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>&#160; RefCreateResizeBilinearTest&lt;RefResizeWorkload, armnn::DataType::Float32&gt;(DataLayout::NHWC);</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>&#160;}</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>&#160;</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> BatchToSpaceNdWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateBatchToSpaceNdTest()</div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>&#160;{</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory;</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>&#160;</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>&#160; <span class="keyword">auto</span> workload = CreateBatchToSpaceNdWorkloadTest&lt;BatchToSpaceNdWorkloadType, DataType&gt;(factory, graph);</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>&#160;</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>&#160; CheckInputOutput(std::move(workload),</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 1, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>),</div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>({ 1, 1, 1, 1 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>));</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span>&#160;}</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>&#160;</div><div class="line"><a name="l00733"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a4da7437861bb40c8a602f443f1b62953"> 733</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchToSpaceNdFloat32)</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span>&#160;{</div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>&#160; RefCreateBatchToSpaceNdTest&lt;RefBatchToSpaceNdWorkload, armnn::DataType::Float32&gt;();</div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>&#160;}</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>&#160;</div><div class="line"><a name="l00738"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ac0597b1862d3ea1574543dcc9e0721a5"> 738</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchToSpaceNdFloat16)</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>&#160;{</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span>&#160; RefCreateBatchToSpaceNdTest&lt;RefBatchToSpaceNdWorkload, armnn::DataType::Float16&gt;();</div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>&#160;}</div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>&#160;</div><div class="line"><a name="l00743"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ad756f39af220b6032c9d3987ba3e528b"> 743</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchToSpaceNdUint8)</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>&#160;{</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span>&#160; RefCreateBatchToSpaceNdTest&lt;RefBatchToSpaceNdWorkload, armnn::DataType::QAsymmU8&gt;();</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span>&#160;}</div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>&#160;</div><div class="line"><a name="l00748"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aed86bc11787de03c506f6a8e9d580355"> 748</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateBatchToSpaceNdQSymm16)</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>&#160;{</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>&#160; RefCreateBatchToSpaceNdTest&lt;RefBatchToSpaceNdWorkload, armnn::DataType::QSymmS16&gt;();</div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span>&#160;}</div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span>&#160;</div><div class="line"><a name="l00753"></a><span class="lineno"> 753</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> L2NormalizationWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateL2NormalizationTest(<a class="code" href="namespacearmnn.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> dataLayout)</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>&#160;{</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span>&#160; <span class="keyword">auto</span> workload =</div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>&#160; CreateL2NormalizationWorkloadTest&lt;L2NormalizationWorkloadType, DataType&gt;(factory, graph, dataLayout);</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>&#160;</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> inputShape;</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span>&#160; <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">TensorShape</a> outputShape;</div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span>&#160;</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span>&#160; <span class="keywordflow">switch</span> (dataLayout)</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>&#160; {</div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span>&#160; <span class="keywordflow">case</span> DataLayout::NHWC:</div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span>&#160; inputShape = { 5, 50, 67, 20 };</div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span>&#160; outputShape = { 5, 50, 67, 20 };</div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span>&#160; <span class="keywordflow">case</span> DataLayout::NCHW:</div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span>&#160; <span class="keywordflow">default</span>:</div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span>&#160; inputShape = { 5, 20, 50, 67 };</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>&#160; outputShape = { 5, 20, 50, 67 };</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span>&#160; }</div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>&#160;</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateL2NormalizationWorkloadTest).</span></div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>&#160; CheckInputOutput(std::move(workload), <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>), <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="l00779"></a><span class="lineno"> 779</span>&#160;}</div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span>&#160;</div><div class="line"><a name="l00781"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a06e01df743165fbe9237a36a2ee806bd"> 781</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationFloat32)</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>&#160;{</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>&#160; RefCreateL2NormalizationTest&lt;RefL2NormalizationWorkload, armnn::DataType::Float32&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>&#160;}</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>&#160;</div><div class="line"><a name="l00786"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a7e2e2fb5fd24d59d5c7b8671cd9d8bbe"> 786</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationFloat32Nhwc)</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>&#160;{</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>&#160; RefCreateL2NormalizationTest&lt;RefL2NormalizationWorkload, armnn::DataType::Float32&gt;(DataLayout::NHWC);</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>&#160;}</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>&#160;</div><div class="line"><a name="l00791"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aed895fa5ab4bf4d616bd8896d5b4b50e"> 791</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationInt16)</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>&#160;{</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>&#160; RefCreateL2NormalizationTest&lt;RefL2NormalizationWorkload, armnn::DataType::QSymmS16&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>&#160;}</div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>&#160;</div><div class="line"><a name="l00796"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aa89f98885f79f976e56256660d929d54"> 796</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationInt16Nhwc)</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>&#160;{</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>&#160; RefCreateL2NormalizationTest&lt;RefL2NormalizationWorkload, armnn::DataType::QSymmS16&gt;(DataLayout::NHWC);</div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>&#160;}</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>&#160;</div><div class="line"><a name="l00801"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a23898a843f8463238d4341ac74107ed2"> 801</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationUint8)</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>&#160;{</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>&#160; RefCreateL2NormalizationTest&lt;RefL2NormalizationWorkload, armnn::DataType::QAsymmU8&gt;(DataLayout::NCHW);</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>&#160;}</div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>&#160;</div><div class="line"><a name="l00806"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ad548e3f61c6c8ab695b2365afd272ce0"> 806</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateL2NormalizationUint8Nhwc)</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>&#160;{</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>&#160; RefCreateL2NormalizationTest&lt;RefL2NormalizationWorkload, armnn::DataType::QAsymmU8&gt;(DataLayout::NHWC);</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>&#160;}</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>&#160;</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> ReshapeWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateReshapeWorkloadTest()</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>&#160;{</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span>&#160; <span class="keyword">auto</span> workload = CreateReshapeWorkloadTest&lt;ReshapeWorkloadType, DataType&gt;(factory, graph);</div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span>&#160;</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>&#160; <span class="comment">// Checks that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest).</span></div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>&#160; CheckInputOutput(</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>&#160; std::move(workload),</div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span>&#160; <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="l00822"></a><span class="lineno"> 822</span>&#160; <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="l00823"></a><span class="lineno"> 823</span>&#160;}</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>&#160;</div><div class="line"><a name="l00825"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a15827696bbfafbab550d1745f3e27930"> 825</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateReshapeWorkloadFloat32)</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>&#160;{</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span>&#160; RefCreateReshapeWorkloadTest&lt;RefReshapeWorkload, armnn::DataType::Float32&gt;();</div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>&#160;}</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span>&#160;</div><div class="line"><a name="l00830"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a46ebad6ae89f77b0c2946d98a9510bff"> 830</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateReshapeWorkloadQuantisedAsymm8)</div><div class="line"><a name="l00831"></a><span class="lineno"> 831</span>&#160;{</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span>&#160; RefCreateReshapeWorkloadTest&lt;RefReshapeWorkload, armnn::DataType::QAsymmU8&gt;();</div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span>&#160;}</div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span>&#160;</div><div class="line"><a name="l00835"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a14965f32deab9acee2bdfbeba9bb2af1"> 835</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateReshapeWorkloadQuantisedSymm16)</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>&#160;{</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span>&#160; RefCreateReshapeWorkloadTest&lt;RefReshapeWorkload, armnn::DataType::QSymmS16&gt;();</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>&#160;}</div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span>&#160;</div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> ConcatWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateConcatWorkloadTest(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>&amp; outputShape,</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> concatAxis)</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>&#160;{</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>&#160; <span class="keyword">auto</span> workload = CreateConcatWorkloadTest&lt;ConcatWorkloadType, DataType&gt;(factory, graph, outputShape, concatAxis);</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>&#160;</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>&#160; CheckInputsOutput(std::move(workload),</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>&#160; <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="l00850"></a><span class="lineno"> 850</span>&#160; <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="l00851"></a><span class="lineno"> 851</span>&#160; <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="l00852"></a><span class="lineno"> 852</span>&#160;}</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>&#160;</div><div class="line"><a name="l00854"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a8782f9dbea0bfb27baa047d5c961ff3e"> 854</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim0Float32Workload)</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>&#160;{</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>&#160; RefCreateConcatWorkloadTest&lt;RefConcatWorkload, armnn::DataType::Float32&gt;({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>&#160;}</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>&#160;</div><div class="line"><a name="l00859"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#abd3c9dcbed34397d70c0b22e6fec617f"> 859</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim0Float16Workload)</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span>&#160;{</div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span>&#160; RefCreateConcatWorkloadTest&lt;RefConcatWorkload, armnn::DataType::Float16&gt;({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>&#160;}</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>&#160;</div><div class="line"><a name="l00864"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ab4f6f715f63bf06d9bb87a21e77f2129"> 864</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim0Uint8Workload)</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>&#160;{</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span>&#160; RefCreateConcatWorkloadTest&lt;RefConcatWorkload, armnn::DataType::QAsymmU8&gt;({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>&#160;}</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span>&#160;</div><div class="line"><a name="l00869"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a3dc599556b9f3c1c617b043c87d82c74"> 869</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim0Uint16Workload)</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span>&#160;{</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>&#160; RefCreateConcatWorkloadTest&lt;RefConcatWorkload, armnn::DataType::QSymmS16&gt;({ 4, 3, 2, 5 }, 0);</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>&#160;}</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>&#160;</div><div class="line"><a name="l00874"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a6e908cfa4b2b0d235a7a83bb450af212"> 874</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim1Float32Workload)</div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>&#160;{</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span>&#160; RefCreateConcatWorkloadTest&lt;RefConcatWorkload, armnn::DataType::Float32&gt;({ 2, 6, 2, 5 }, 1);</div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span>&#160;}</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span>&#160;</div><div class="line"><a name="l00879"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ad76e3bac3ab907f6ebf516ca8f40ad49"> 879</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim1Uint8Workload)</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span>&#160;{</div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span>&#160; RefCreateConcatWorkloadTest&lt;RefConcatWorkload, armnn::DataType::QAsymmU8&gt;({ 2, 6, 2, 5 }, 1);</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span>&#160;}</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>&#160;</div><div class="line"><a name="l00884"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ab1af54a3eec17165e9cee8b0bcf3d55c"> 884</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim2Float32Workload)</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span>&#160;{</div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span>&#160; RefCreateConcatWorkloadTest&lt;RefConcatWorkload, armnn::DataType::Float32&gt;({ 2, 3, 4, 5 }, 2);</div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>&#160;}</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span>&#160;</div><div class="line"><a name="l00889"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ab78fddea7399be741a003deb254dbf62"> 889</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim2Uint8Workload)</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>&#160;{</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>&#160; RefCreateConcatWorkloadTest&lt;RefConcatWorkload, armnn::DataType::QAsymmU8&gt;({ 2, 3, 4, 5 }, 2);</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>&#160;}</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>&#160;</div><div class="line"><a name="l00894"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a15c6731388ff09e4fb01e12100138e40"> 894</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim3Float32Workload)</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>&#160;{</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span>&#160; RefCreateConcatWorkloadTest&lt;RefConcatWorkload, armnn::DataType::Float32&gt;({ 2, 3, 2, 10 }, 3);</div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span>&#160;}</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span>&#160;</div><div class="line"><a name="l00899"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a41bdcd447af6e0fe880fd6c746830468"> 899</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConcatDim3Uint8Workload)</div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span>&#160;{</div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span>&#160; RefCreateConcatWorkloadTest&lt;RefConcatWorkload, armnn::DataType::QAsymmU8&gt;({ 2, 3, 2, 10 }, 3);</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span>&#160;}</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>&#160;</div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> ConstantWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateConstantWorkloadTest(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>&amp; outputShape)</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>&#160;{</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory = GetFactory();</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>&#160; <span class="keyword">auto</span> workload = CreateConstantWorkloadTest&lt;ConstantWorkloadType, DataType&gt;(factory, graph, outputShape);</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>&#160;</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>&#160; <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span>&#160; <span class="keyword">auto</span> queueDescriptor = workload-&gt;GetData();</div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span>&#160; <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>&#160; BOOST_TEST((outputHandle-&gt;GetTensorInfo() == <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="l00915"></a><span class="lineno"> 915</span>&#160;}</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span>&#160;</div><div class="line"><a name="l00917"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a7969d45c3cccd8daa055e3412b4bed68"> 917</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConstantUint8Workload)</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span>&#160;{</div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span>&#160; RefCreateConstantWorkloadTest&lt;RefConstantWorkload, armnn::DataType::QAsymmU8&gt;({ 2, 3, 2, 10 });</div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span>&#160;}</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span>&#160;</div><div class="line"><a name="l00922"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a4db8dc5565b0621adadf181bcfb5e42c"> 922</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConstantInt16Workload)</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>&#160;{</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span>&#160; RefCreateConstantWorkloadTest&lt;RefConstantWorkload, armnn::DataType::QSymmS16&gt;({ 2, 3, 2, 10 });</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>&#160;}</div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span>&#160;</div><div class="line"><a name="l00927"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a4a90c2b6944e9e8e96c25516549c0cc9"> 927</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConstantFloat32Workload)</div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>&#160;{</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span>&#160; RefCreateConstantWorkloadTest&lt;RefConstantWorkload, armnn::DataType::Float32&gt;({ 2, 3, 2, 10 });</div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>&#160;}</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>&#160;</div><div class="line"><a name="l00932"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a88e28a1faa66d1ab0a0ffa6ad9a47b60"> 932</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateConstantSigned32Workload)</div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span>&#160;{</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span>&#160; RefCreateConstantWorkloadTest&lt;RefConstantWorkload, armnn::DataType::Signed32&gt;({ 2, 3, 2, 10 });</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>&#160;}</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>&#160;</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreatePreluWorkloadTest(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>&amp; inputShape,</div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>&amp; alphaShape,</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>&amp; outputShape,</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">armnn::DataType</a> dataType)</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span>&#160;{</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory;</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>&#160; <span class="keyword">auto</span> workload = CreatePreluWorkloadTest&lt;RefPreluWorkload&gt;(factory,</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>&#160; graph,</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>&#160; inputShape,</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span>&#160; alphaShape,</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span>&#160; outputShape,</div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span>&#160; dataType);</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span>&#160;</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span>&#160; <span class="comment">// Check output is as expected</span></div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>&#160; <span class="keyword">auto</span> queueDescriptor = workload-&gt;GetData();</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>&#160; <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>&#160; BOOST_TEST((outputHandle-&gt;GetTensorInfo() == <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>(outputShape, dataType)));</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span>&#160;}</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span>&#160;</div><div class="line"><a name="l00957"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#afcadab839f145917ff02c8451a76a152"> 957</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePreluFloat32Workload)</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span>&#160;{</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>&#160; RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span>&#160;}</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span>&#160;</div><div class="line"><a name="l00962"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#aa73ba7a4ea3327d87efd4618c083b333"> 962</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePreluFloat16Workload)</div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span>&#160;{</div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>&#160; RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>);</div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span>&#160;}</div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span>&#160;</div><div class="line"><a name="l00967"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a12d17284981e1fff8f0fc76da9293e2c"> 967</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePreluUint8Workload)</div><div class="line"><a name="l00968"></a><span class="lineno"> 968</span>&#160;{</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span>&#160; RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>);</div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>&#160;}</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>&#160;</div><div class="line"><a name="l00972"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ad9bbc84cf48c0112c698e7d678a318f6"> 972</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePreluInt16Workload)</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>&#160;{</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>&#160; RefCreatePreluWorkloadTest({ 1, 4, 1, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 }, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>);</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span>&#160;}</div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span>&#160;</div><div class="line"><a name="l00977"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a16addc490db90b266ef38af9ebd3d731"> 977</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePreluFloat32NoBroadcastWorkload)</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>&#160;{</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span>&#160; BOOST_CHECK_THROW(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 },</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>),</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span>&#160; <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>);</div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>&#160;}</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>&#160;</div><div class="line"><a name="l00984"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a7124dca744920ec86ae32fbc5dd9285f"> 984</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePreluFloat16NoBroadcastWorkload)</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>&#160;{</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span>&#160; BOOST_CHECK_THROW(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 },</div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">armnn::DataType::Float16</a>),</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>&#160; <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>);</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>&#160;}</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>&#160;</div><div class="line"><a name="l00991"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a7132a0f1bbefa31da10ad1b4f6812f7e"> 991</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePreluUint8NoBroadcastWorkload)</div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span>&#160;{</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span>&#160; BOOST_CHECK_THROW(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 },</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">armnn::DataType::QAsymmU8</a>),</div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span>&#160; <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>);</div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span>&#160;}</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span>&#160;</div><div class="line"><a name="l00998"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a63bce6d36ea8f3c55eebcb98cf80f63e"> 998</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreatePreluInt16NoBroadcastWorkload)</div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span>&#160;{</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>&#160; BOOST_CHECK_THROW(RefCreatePreluWorkloadTest({ 1, 4, 7, 2 }, { 5, 4, 3, 1 }, { 5, 4, 3, 2 },</div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>&#160; <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</a>),</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>&#160; <a class="code" href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a>);</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>&#160;}</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>&#160;</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> SpaceToDepthWorkloadType, armnn::DataType DataType&gt;</div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateSpaceToDepthWorkloadTest()</div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>&#160;{</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">Graph</a> graph;</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory;</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>&#160;</div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>&#160; <span class="keyword">auto</span> workload = CreateSpaceToDepthWorkloadTest&lt;SpaceToDepthWorkloadType, DataType&gt;(factory, graph);</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>&#160;</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>&#160; CheckInputOutput(std::move(workload),</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>&#160; <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="l01015"></a><span class="lineno"> 1015</span>&#160; <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="l01016"></a><span class="lineno"> 1016</span>&#160;}</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>&#160;</div><div class="line"><a name="l01018"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#adc18533dddc0d2c073e07b650955a6d9"> 1018</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthWorkloadFloat32)</div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>&#160;{</div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span>&#160; RefCreateSpaceToDepthWorkloadTest&lt;RefSpaceToDepthWorkload, armnn::DataType::Float32&gt;();</div><div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>&#160;}</div><div class="line"><a name="l01022"></a><span class="lineno"> 1022</span>&#160;</div><div class="line"><a name="l01023"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#af47399c946f0281f6f63251302b0bdfc"> 1023</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthWorkloadFloat16)</div><div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>&#160;{</div><div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>&#160; RefCreateSpaceToDepthWorkloadTest&lt;RefSpaceToDepthWorkload, armnn::DataType::Float16&gt;();</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span>&#160;}</div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>&#160;</div><div class="line"><a name="l01028"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ad2344fbc180e3d6442aad31dbad08954"> 1028</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthWorkloadQASymm8)</div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>&#160;{</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span>&#160; RefCreateSpaceToDepthWorkloadTest&lt;RefSpaceToDepthWorkload, armnn::DataType::QAsymmU8&gt;();</div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>&#160;}</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>&#160;</div><div class="line"><a name="l01033"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#ad362fa938c5f64b1f3ef834f3131bda6"> 1033</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateSpaceToDepthWorkloadQSymm16)</div><div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>&#160;{</div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span>&#160; RefCreateSpaceToDepthWorkloadTest&lt;RefSpaceToDepthWorkload, armnn::DataType::QSymmS16&gt;();</div><div class="line"><a name="l01036"></a><span class="lineno"> 1036</span>&#160;}</div><div class="line"><a name="l01037"></a><span class="lineno"> 1037</span>&#160;</div><div class="line"><a name="l01038"></a><span class="lineno"> 1038</span>&#160;<span class="keyword">template</span> &lt;armnn::DataType DataType&gt;</div><div class="line"><a name="l01039"></a><span class="lineno"> 1039</span>&#160;<span class="keyword">static</span> <span class="keywordtype">void</span> RefCreateStackWorkloadTest(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>&amp; inputShape,</div><div class="line"><a name="l01040"></a><span class="lineno"> 1040</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.xhtml">armnn::TensorShape</a>&amp; outputShape,</div><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> axis,</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> numInputs)</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>&#160;{</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>&#160; <a class="code" href="classarmnn_1_1_graph.xhtml">armnn::Graph</a> graph;</div><div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>&#160; <a class="code" href="classarmnn_1_1_ref_workload_factory.xhtml">RefWorkloadFactory</a> factory;</div><div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>&#160; <span class="keyword">auto</span> workload = CreateStackWorkloadTest&lt;RefStackWorkload, DataType&gt;(factory,</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>&#160; graph,</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span>&#160; inputShape,</div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>&#160; outputShape,</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>&#160; axis,</div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>&#160; numInputs);</div><div class="line"><a name="l01052"></a><span class="lineno"> 1052</span>&#160;</div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>&#160; <span class="comment">// Check inputs and output are as expected</span></div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span>&#160; <a class="code" href="structarmnn_1_1_stack_queue_descriptor.xhtml">StackQueueDescriptor</a> queueDescriptor = workload-&gt;GetData();</div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>&#160; <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; numInputs; ++i)</div><div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>&#160; {</div><div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>&#160; <span class="keyword">auto</span> inputHandle = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Inputs[i]);</div><div class="line"><a name="l01058"></a><span class="lineno"> 1058</span>&#160; BOOST_TEST((inputHandle-&gt;GetTensorInfo() == <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="l01059"></a><span class="lineno"> 1059</span>&#160; }</div><div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>&#160; <span class="keyword">auto</span> outputHandle = boost::polymorphic_downcast&lt;RefTensorHandle*&gt;(queueDescriptor.m_Outputs[0]);</div><div class="line"><a name="l01061"></a><span class="lineno"> 1061</span>&#160; BOOST_TEST((outputHandle-&gt;GetTensorInfo() == <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="l01062"></a><span class="lineno"> 1062</span>&#160;}</div><div class="line"><a name="l01063"></a><span class="lineno"> 1063</span>&#160;</div><div class="line"><a name="l01064"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a72d6262ab8544dbfa7cfc22910e3011c"> 1064</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateStackFloat32Workload)</div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>&#160;{</div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>&#160; RefCreateStackWorkloadTest&lt;armnn::DataType::Float32&gt;({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>&#160;}</div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>&#160;</div><div class="line"><a name="l01069"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a966e80d9fbe654c47b44265d982d3c33"> 1069</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateStackUint8Workload)</div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span>&#160;{</div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>&#160; RefCreateStackWorkloadTest&lt;armnn::DataType::QAsymmU8&gt;({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>&#160;}</div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>&#160;</div><div class="line"><a name="l01074"></a><span class="lineno"><a class="line" href="_ref_create_workload_tests_8cpp.xhtml#a76cbb6d4fcc4fb2927e37c2c886e9cf5"> 1074</a></span>&#160;<a class="code" href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a>(CreateStackUint16Workload)</div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>&#160;{</div><div class="line"><a name="l01076"></a><span class="lineno"> 1076</span>&#160; RefCreateStackWorkloadTest&lt;armnn::DataType::QSymmS16&gt;({ 3, 4, 5 }, { 3, 4, 2, 5 }, 2, 2);</div><div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>&#160;}</div><div class="line"><a name="l01078"></a><span class="lineno"> 1078</span>&#160;</div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>&#160;<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#l00222">WorkloadData.hpp:222</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="namespacearmnn_xhtml_a5c3a2aa3adc87d79164914b63f27dc25"><div class="ttname"><a href="namespacearmnn.xhtml#a5c3a2aa3adc87d79164914b63f27dc25">armnn::RefDivisionWorkload</a></div><div class="ttdeci">RefElementwiseWorkload&lt; std::divides&lt; float &gt;, DivisionQueueDescriptor, StringMapping::RefDivisionWorkload_Execute &gt; RefDivisionWorkload</div><div class="ttdef"><b>Definition:</b> <a href="_ref_elementwise_workload_8hpp_source.xhtml#l00056">RefElementwiseWorkload.hpp:56</a></div></div>
<div class="ttc" id="_ref_workload_factory_8hpp_xhtml"><div class="ttname"><a href="_ref_workload_factory_8hpp.xhtml">RefWorkloadFactory.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a01853f5d02495c04636016c1e3e7c144"><div class="ttname"><a href="namespacearmnn.xhtml#a01853f5d02495c04636016c1e3e7c144">armnn::RefSubtractionWorkload</a></div><div class="ttdeci">RefElementwiseWorkload&lt; std::minus&lt; float &gt;, SubtractionQueueDescriptor, StringMapping::RefSubtractionWorkload_Execute &gt; RefSubtractionWorkload</div><div class="ttdef"><b>Definition:</b> <a href="_ref_elementwise_workload_8hpp_source.xhtml#l00046">RefElementwiseWorkload.hpp:46</a></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#l00049">Types.hpp:49</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#l00083">WorkloadData.hpp:83</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_a7a9d365fbb868d53e67c4cdfdbf9cf7e"><div class="ttname"><a href="namespacearmnn.xhtml#a7a9d365fbb868d53e67c4cdfdbf9cf7e">armnn::RefAdditionWorkload</a></div><div class="ttdeci">RefElementwiseWorkload&lt; std::plus&lt; float &gt;, AdditionQueueDescriptor, StringMapping::RefAdditionWorkload_Execute &gt; RefAdditionWorkload</div><div class="ttdef"><b>Definition:</b> <a href="_ref_elementwise_workload_8hpp_source.xhtml#l00041">RefElementwiseWorkload.hpp:41</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_aabff736a576814611f65ce1a14600a17"><div class="ttname"><a href="namespacearmnn.xhtml#aabff736a576814611f65ce1a14600a17">armnn::RefMultiplicationWorkload</a></div><div class="ttdeci">RefElementwiseWorkload&lt; std::multiplies&lt; float &gt;, MultiplicationQueueDescriptor, StringMapping::RefMultiplicationWorkload_Execute &gt; RefMultiplicationWorkload</div><div class="ttdef"><b>Definition:</b> <a href="_ref_elementwise_workload_8hpp_source.xhtml#l00051">RefElementwiseWorkload.hpp:51</a></div></div>
<div class="ttc" id="classarmnn_1_1_ref_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_ref_tensor_handle.xhtml">armnn::RefTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="_ref_tensor_handle_8hpp_source.xhtml#l00015">RefTensorHandle.hpp:15</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
<div class="ttc" id="classarmnn_1_1_ref_splitter_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_ref_splitter_workload.xhtml">armnn::RefSplitterWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_ref_splitter_workload_8hpp_source.xhtml#l00016">RefSplitterWorkload.hpp:16</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#l00124">WorkloadData.hpp:124</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#l00216">WorkloadData.hpp:216</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a053c769dcf82d66ef326c86980c02ba7">armnn::DataType::QSymmS16</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_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#l00228">WorkloadData.hpp:228</a></div></div>
<div class="ttc" id="_create_workload_8hpp_xhtml"><div class="ttname"><a href="_create_workload_8hpp.xhtml">CreateWorkload.hpp</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#l00234">WorkloadData.hpp:234</a></div></div>
<div class="ttc" id="_ref_workloads_8hpp_xhtml"><div class="ttname"><a href="_ref_workloads_8hpp.xhtml">RefWorkloads.hpp</a></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="classarmnn_1_1_ref_activation_workload_xhtml"><div class="ttname"><a href="classarmnn_1_1_ref_activation_workload.xhtml">armnn::RefActivationWorkload</a></div><div class="ttdef"><b>Definition:</b> <a href="_ref_activation_workload_8hpp_source.xhtml#l00014">RefActivationWorkload.hpp:14</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="classarmnn_1_1_ref_workload_factory_xhtml"><div class="ttname"><a href="classarmnn_1_1_ref_workload_factory.xhtml">armnn::RefWorkloadFactory</a></div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_factory_8hpp_source.xhtml#l00030">RefWorkloadFactory.hpp:30</a></div></div>
<div class="ttc" id="classarmnn_1_1_invalid_argument_exception_xhtml"><div class="ttname"><a href="classarmnn_1_1_invalid_argument_exception.xhtml">armnn::InvalidArgumentException</a></div><div class="ttdef"><b>Definition:</b> <a href="_exceptions_8hpp_source.xhtml#l00080">Exceptions.hpp:80</a></div></div>
<div class="ttc" id="_ref_tensor_handle_8hpp_xhtml"><div class="ttname"><a href="_ref_tensor_handle_8hpp.xhtml">RefTensorHandle.hpp</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="_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="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="_ref_create_workload_tests_8cpp_xhtml_a192497d6feca90c8a4ef93dcf5eac7b9"><div class="ttname"><a href="_ref_create_workload_tests_8cpp.xhtml#a192497d6feca90c8a4ef93dcf5eac7b9">BOOST_AUTO_TEST_CASE</a></div><div class="ttdeci">BOOST_AUTO_TEST_CASE(CreateActivationFloat32Workload)</div><div class="ttdef"><b>Definition:</b> <a href="_ref_create_workload_tests_8cpp_source.xhtml#l00064">RefCreateWorkloadTests.cpp:64</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_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_xhtml_a56943a0946e5f15e5e58054b8e7a04a4"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4">armnn::LayerType</a></div><div class="ttdeci">LayerType</div><div class="ttdef"><b>Definition:</b> <a href="_internal_types_8hpp_source.xhtml#l00014">InternalTypes.hpp:14</a></div></div>
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