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<div class="title">PreluTestImpl.hpp File Reference</div> </div>
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<div class="textblock"><code>#include &quot;<a class="el" href="_layer_test_result_8hpp_source.xhtml">LayerTestResult.hpp</a>&quot;</code><br />
<code>#include &lt;<a class="el" href="_quantize_helper_8hpp_source.xhtml">QuantizeHelper.hpp</a>&gt;</code><br />
<code>#include &lt;<a class="el" href="_resolve_type_8hpp_source.xhtml">ResolveType.hpp</a>&gt;</code><br />
<code>#include &lt;<a class="el" href="include_2armnn_2backends_2_i_backend_internal_8hpp_source.xhtml">armnn/backends/IBackendInternal.hpp</a>&gt;</code><br />
<code>#include &lt;<a class="el" href="_workload_factory_8hpp_source.xhtml">backendsCommon/WorkloadFactory.hpp</a>&gt;</code><br />
<code>#include &lt;<a class="el" href="_tensor_copy_utils_8hpp_source.xhtml">backendsCommon/test/TensorCopyUtils.hpp</a>&gt;</code><br />
<code>#include &lt;<a class="el" href="_workload_test_utils_8hpp_source.xhtml">backendsCommon/test/WorkloadTestUtils.hpp</a>&gt;</code><br />
<code>#include &lt;<a class="el" href="_tensor_helpers_8hpp_source.xhtml">test/TensorHelpers.hpp</a>&gt;</code><br />
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<p><a href="_prelu_test_impl_8hpp_source.xhtml">Go to the source code of this file.</a></p>
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Functions</h2></td></tr>
<tr class="memitem:a1330e64bd2b612dfc2b2e87ff748654b"><td class="memTemplParams" colspan="2">template&lt;armnn::DataType ArmnnType, typename T = armnn::ResolveType&lt;ArmnnType&gt;&gt; </td></tr>
<tr class="memitem:a1330e64bd2b612dfc2b2e87ff748654b"><td class="memTemplItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt; T, 4 &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="_prelu_test_impl_8hpp.xhtml#a1330e64bd2b612dfc2b2e87ff748654b">PreluTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &amp;workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;memoryManager)</td></tr>
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<h2 class="memtitle"><span class="permalink"><a href="#a1330e64bd2b612dfc2b2e87ff748654b">&#9670;&nbsp;</a></span>PreluTest()</h2>
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<td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>&lt;T, 4&gt; PreluTest </td>
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<td class="paramname"><em>workloadFactory</em>, </td>
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<td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &amp;&#160;</td>
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<p class="definition">Definition at line <a class="el" href="_prelu_test_impl_8hpp_source.xhtml#l00023">23</a> of file <a class="el" href="_prelu_test_impl_8hpp_source.xhtml">PreluTestImpl.hpp</a>.</p>
<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01352">IWorkloadFactory::CreatePrelu()</a>, <a class="el" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">IWorkloadFactory::CreateTensorHandle()</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00040">LayerTestResult&lt; T, n &gt;::output</a>, <a class="el" href="_layer_test_result_8hpp_source.xhtml#l00041">LayerTestResult&lt; T, n &gt;::outputExpected</a>, and <a class="el" href="_tensor_8cpp_source.xhtml#l00259">TensorInfo::SetQuantizationScale()</a>.</p>
<div class="fragment"><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;{</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo ({ 1, 2, 2, 3 }, ArmnnType);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> alphaTensorInfo ({ 1, 1, 1, 3 }, ArmnnType);</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({ 1, 2, 2, 3 }, ArmnnType);</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160; <span class="keywordflow">if</span> (armnn::IsQuantizedType&lt;T&gt;())</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; {</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160; inputTensorInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(0.25f);</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160; inputTensorInfo.SetQuantizationOffset(128);</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; alphaTensorInfo.SetQuantizationScale(0.25f);</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; alphaTensorInfo.SetQuantizationOffset(50);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; outputTensorInfo.SetQuantizationScale(0.5f);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; outputTensorInfo.SetQuantizationOffset(120);</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;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; std::vector&lt;float&gt; inputData</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; <span class="comment">// Expected quantized values:</span></div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160; <span class="comment">// 128, 128, 128, 132, 132, 132, 124, 124, 124, 120, 120, 120</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; 0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -2.0f, -2.0f, -2.0f</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; std::vector&lt;float&gt; alphaData</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="comment">// Expected quantized values:</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="comment">// 50, 54, 58</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; 0.0f, 1.0f, 2.0f</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; };</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; std::vector&lt;float&gt; outputExpectedData =</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; {</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="comment">// Expected quantized values:</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="comment">// 20, 120, 120, 122, 122, 122, 120, 118, 116, 120, 116, 112</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; 0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, -1.0f, -2.0f, 0.0f, -2.0f, -4.0f</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; };</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="keyword">auto</span> input = MakeTensor&lt;T, 4&gt;(inputTensorInfo,</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; armnnUtils::QuantizedVector&lt;T&gt;(inputData,</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; inputTensorInfo.GetQuantizationScale(),</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; inputTensorInfo.GetQuantizationOffset()));</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="keyword">auto</span> alpha = MakeTensor&lt;T, 4&gt;(alphaTensorInfo,</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; armnnUtils::QuantizedVector&lt;T&gt;(alphaData,</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; alphaTensorInfo.GetQuantizationScale(),</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; alphaTensorInfo.GetQuantizationOffset()));</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult&lt;T, 4&gt;</a> result(outputTensorInfo);</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; result.outputExpected =</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; MakeTensor&lt;T, 4&gt;(outputTensorInfo,</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; armnnUtils::QuantizedVector&lt;T&gt;(outputExpectedData,</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; outputTensorInfo.GetQuantizationScale(),</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; outputTensorInfo.GetQuantizationOffset()));</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; std::unique_ptr &lt;armnn::ITensorHandle&gt; inputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; std::unique_ptr &lt;armnn::ITensorHandle&gt; alphaHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(alphaTensorInfo);</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; std::unique_ptr &lt;armnn::ITensorHandle&gt; outputHandle = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <a class="code" href="structarmnn_1_1_prelu_queue_descriptor.xhtml">armnn::PreluQueueDescriptor</a> descriptor;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; AddInputToWorkload (descriptor, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; AddInputToWorkload (descriptor, info, alphaTensorInfo, alphaHandle.get());</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; std::unique_ptr&lt;armnn::IWorkload&gt; workload = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#adf4a93f605e4e7dad6aee0b4d2159171">CreatePrelu</a>(descriptor, info);</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"> 91</span>&#160; inputHandle-&gt;Allocate();</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; alphaHandle-&gt;Allocate();</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; outputHandle-&gt;Allocate();</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), &amp;input[0][0][0][0]);</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(alphaHandle.get(), &amp;alpha[0][0][0][0]);</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; workload-&gt;Execute();</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <a class="code" href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a>(&amp;result.output[0][0][0][0], outputHandle.get());</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keywordflow">return</span> result;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160;}</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="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &amp;&amp;...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div>
<div class="ttc" id="structarmnn_1_1_prelu_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_prelu_queue_descriptor.xhtml">armnn::PreluQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00489">WorkloadData.hpp:489</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00259">Tensor.cpp:259</a></div></div>
<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_a99b626c58a926dc7d6df78d22ec186c8"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#a99b626c58a926dc7d6df78d22ec186c8">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a15c140be4ddceffee16436f009d3ed94"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a15c140be4ddceffee16436f009d3ed94">armnn::IWorkloadFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr&lt; ITensorHandle &gt; CreateTensorHandle(const TensorInfo &amp;tensorInfo, const bool IsMemoryManaged=true) const =0</div></div>
<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div>
<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about inputs and outputs to a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div>
<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="_layer_test_result_8hpp_source.xhtml#l00029">LayerTestResult.hpp:29</a></div></div>
<div class="ttc" id="_tensor_copy_utils_8cpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="_tensor_copy_utils_8cpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_adf4a93f605e4e7dad6aee0b4d2159171"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#adf4a93f605e4e7dad6aee0b4d2159171">armnn::IWorkloadFactory::CreatePrelu</a></div><div class="ttdeci">virtual std::unique_ptr&lt; IWorkload &gt; CreatePrelu(const PreluQueueDescriptor &amp;descriptor, const WorkloadInfo &amp;info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01352">WorkloadFactory.cpp:1352</a></div></div>
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