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<div class="title">PreluEndToEndTestImpl.hpp</div> </div>
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<a href="_prelu_end_to_end_test_impl_8hpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">//</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment">// Copyright © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include <<a class="code" href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a>></span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_i_network_8hpp.xhtml">armnn/INetwork.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_common_test_utils_8hpp.xhtml">backendsCommon/test/CommonTestUtils.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> {</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="keyword">template</span><<span class="keyword">typename</span> armnn::DataType DataType></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> CreatePreluNetwork(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& inputInfo,</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& alphaInfo,</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>& outputInfo)</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> {</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> </div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">INetwork::Create</a>());</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> </div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* input = net->AddInputLayer(0, <span class="stringliteral">"input"</span>);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* alpha = net->AddInputLayer(1, <span class="stringliteral">"alpha"</span>);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* prelu = net->AddPreluLayer(<span class="stringliteral">"Prelu"</span>);</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  <a class="code" href="classarmnn_1_1_i_connectable_layer.xhtml">IConnectableLayer</a>* output = net->AddOutputLayer(0, <span class="stringliteral">"output"</span>);</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> </div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, prelu, inputInfo, 0, 0);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(alpha, prelu, alphaInfo, 0, 1);</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  <a class="code" href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a>(prelu, output, outputInfo, 0, 0);</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  <span class="keywordflow">return</span> net;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> }</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="keywordtype">void</span> PreluEndToEnd(<span class="keyword">const</span> std::vector<BackendId>& backends,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keyword">const</span> std::vector<T>& inputData,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keyword">const</span> std::vector<T>& alphaData,</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keyword">const</span> std::vector<T>& expectedOutputData,</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> qScale ,</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keyword">const</span> int32_t qOffset)</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> {</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a>;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({ 2, 2, 2, 1 }, ArmnnType);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> alphaInfo({ 1, 2, 2, 1 }, ArmnnType);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({ 2, 2, 2, 1 }, ArmnnType);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  alphaInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  alphaInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <a class="code" href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net = CreatePreluNetwork<ArmnnType>(inputInfo, alphaInfo, outputInfo);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  BOOST_TEST_CHECKPOINT(<span class="stringliteral">"Create a network"</span>);</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  std::map<int, std::vector<T>> inputTensorData = { { 0, inputData }, { 1, alphaData} };</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  std::map<int, std::vector<T>> expectedOutputTensorData = { { 0, expectedOutputData } };</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> </div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net),</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  inputTensorData,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  expectedOutputTensorData,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  backends);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> }</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="keywordtype">void</span> PreluEndToEndPositiveTest(<span class="keyword">const</span> std::vector<BackendId>& backends, <span class="keyword">const</span> <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">const</span> int32_t qOffset = 2)</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> {</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  std::vector<T> inputData{ 1, 2, 3, 4, 5, 6, 7, 8 };</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  std::vector<T> alphaData{ 2, 1, 1, 1 };</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  std::vector<T> expectedOutputData{ 2, 2, 3, 4, 5, 6, 7, 8 };</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> </div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  PreluEndToEnd<ArmnnType>(backends, inputData, alphaData, expectedOutputData, qScale, qOffset);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span> }</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="keyword">template</span><armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType<ArmnnType>></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="keywordtype">void</span> PreluEndToEndNegativeTest(<span class="keyword">const</span> std::vector<BackendId>& backends, <span class="keyword">const</span> <span class="keywordtype">float</span> qScale = 1.0f,</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keyword">const</span> int32_t qOffset = 0)</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> {</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  std::vector<T> inputData{ 1, -2, 3, 4, 5, 6, 7, 8 };</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  std::vector<T> alphaData{ 1, 2, 1, 1 };</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  std::vector<T> expectedOutputData{ 1, -4, 3, 4, 5, 6, 7, 8 };</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  PreluEndToEnd<ArmnnType>(backends, inputData, alphaData, expectedOutputData, qScale, qOffset);</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> }</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> } <span class="comment">// anonymous namespace</span></div><div class="ttc" id="classarmnn_1_1_i_connectable_layer_xhtml"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.xhtml">armnn::IConnectableLayer</a></div><div class="ttdoc">Interface for a layer that is connectable to other layers via InputSlots and OutputSlots. </div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00062">INetwork.hpp:62</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div>
<div class="ttc" id="_resolve_type_8hpp_xhtml"><div class="ttname"><a href="_resolve_type_8hpp.xhtml">ResolveType.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2021 ARM Limited and Contributors. </div><div class="ttdef"><b>Definition:</b> <a href="01__00__software__tools_8dox_source.xhtml#l00006">01_00_software_tools.dox:6</a></div></div>
<div class="ttc" id="_common_test_utils_8hpp_xhtml"><div class="ttname"><a href="_common_test_utils_8hpp.xhtml">CommonTestUtils.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a685739c4eb65a580e075282cfe6787d6">armnn::TensorInfo::SetQuantizationScale</a></div><div class="ttdeci">void SetQuantizationScale(float scale)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00464">Tensor.cpp:464</a></div></div>
<div class="ttc" id="_i_network_8hpp_xhtml"><div class="ttname"><a href="_i_network_8hpp.xhtml">INetwork.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a63cbc581012c957f9d68d224ddc3e43c">armnn::TensorInfo::SetQuantizationOffset</a></div><div class="ttdeci">void SetQuantizationOffset(int32_t offset)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8cpp_source.xhtml#l00480">Tensor.cpp:480</a></div></div>
<div class="ttc" id="_test_utils_8cpp_xhtml_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.xhtml#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.xhtml#l00012">TestUtils.cpp:12</a></div></div>
<div class="ttc" id="namespacearmnn_xhtml_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.xhtml#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr< INetwork, void(*)(INetwork *network)> INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.xhtml#l00173">INetwork.hpp:173</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_xhtml_a464f0ff87b1aabf71febaa71321dd40b"><div class="ttname"><a href="classarmnn_1_1_i_network.xhtml#a464f0ff87b1aabf71febaa71321dd40b">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create(NetworkOptions networkOptions={})</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.xhtml#l00510">Network.cpp:510</a></div></div>
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