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<div class="title">PreluEndToEndTestImpl.hpp</div> </div>
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<a href="_prelu_end_to_end_test_impl_8hpp.html">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;<span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;</div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_resolve_type_8hpp.html">ResolveType.hpp</a>&gt;</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;</div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_i_network_8hpp.html">armnn/INetwork.hpp</a>&gt;</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;</div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_common_test_utils_8hpp.html">backendsCommon/test/CommonTestUtils.hpp</a>&gt;</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;</div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="keyword">namespace</span></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> armnn::DataType DataType&gt;</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> CreatePreluNetwork(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>&amp; inputInfo,</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>&amp; alphaInfo,</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a>&amp; outputInfo)</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;{</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net(<a class="code" href="classarmnn_1_1_i_network.html#a706f7345af3f18f4b16e226a672214c6">INetwork::Create</a>());</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; <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* input = net-&gt;AddInputLayer(0, <span class="stringliteral">&quot;input&quot;</span>);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* alpha = net-&gt;AddInputLayer(1, <span class="stringliteral">&quot;alpha&quot;</span>);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* prelu = net-&gt;AddPreluLayer(<span class="stringliteral">&quot;Prelu&quot;</span>);</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160; <a class="code" href="classarmnn_1_1_i_connectable_layer.html">IConnectableLayer</a>* output = net-&gt;AddOutputLayer(0, <span class="stringliteral">&quot;output&quot;</span>);</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="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(input, prelu, inputInfo, 0, 0);</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160; <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(alpha, prelu, alphaInfo, 0, 1);</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160; <a class="code" href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a>(prelu, output, outputInfo, 0, 0);</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">return</span> net;</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;</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;<span class="keywordtype">void</span> PreluEndToEnd(<span class="keyword">const</span> std::vector&lt;BackendId&gt;&amp; backends,</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <span class="keyword">const</span> std::vector&lt;T&gt;&amp; inputData,</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="keyword">const</span> std::vector&lt;T&gt;&amp; alphaData,</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="keyword">const</span> std::vector&lt;T&gt;&amp; expectedOutputData,</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="keyword">const</span> <span class="keywordtype">float</span> qScale ,</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160; <span class="keyword">const</span> int32_t qOffset)</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160;{</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; <span class="keyword">using namespace </span><a class="code" href="namespacearmnn.html">armnn</a>;</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; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> inputInfo({ 2, 2, 2, 1 }, ArmnnType);</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> alphaInfo({ 1, 2, 2, 1 }, ArmnnType);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a> outputInfo({ 2, 2, 2, 1 }, ArmnnType);</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; alphaInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160; alphaInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a63cbc581012c957f9d68d224ddc3e43c">SetQuantizationOffset</a>(qOffset);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a685739c4eb65a580e075282cfe6787d6">SetQuantizationScale</a>(qScale);</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; <a class="code" href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">INetworkPtr</a> net = CreatePreluNetwork&lt;ArmnnType&gt;(inputInfo, alphaInfo, outputInfo);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160;</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; BOOST_TEST_CHECKPOINT(<span class="stringliteral">&quot;Create a network&quot;</span>);</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; std::map&lt;int, std::vector&lt;T&gt;&gt; inputTensorData = { { 0, inputData }, { 1, alphaData} };</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; std::map&lt;int, std::vector&lt;T&gt;&gt; expectedOutputTensorData = { { 0, expectedOutputData } };</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"> 64</span>&#160; EndToEndLayerTestImpl&lt;ArmnnType, ArmnnType&gt;(move(net),</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; inputTensorData,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; expectedOutputTensorData,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; backends);</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"> 69</span>&#160;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160;<span class="keywordtype">void</span> PreluEndToEndPositiveTest(<span class="keyword">const</span> std::vector&lt;BackendId&gt;&amp; 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>&#160; <span class="keyword">const</span> int32_t qOffset = 2)</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; std::vector&lt;T&gt; inputData{ 1, 2, 3, 4, 5, 6, 7, 8 };</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; std::vector&lt;T&gt; alphaData{ 2, 1, 1, 1 };</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; std::vector&lt;T&gt; expectedOutputData{ 2, 2, 3, 4, 5, 6, 7, 8 };</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; PreluEndToEnd&lt;ArmnnType&gt;(backends, inputData, alphaData, expectedOutputData, qScale, qOffset);</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;}</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;<span class="keyword">template</span>&lt;armnn::DataType ArmnnType, <span class="keyword">typename</span> T = armnn::ResolveType&lt;ArmnnType&gt;&gt;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160;<span class="keywordtype">void</span> PreluEndToEndNegativeTest(<span class="keyword">const</span> std::vector&lt;BackendId&gt;&amp; 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>&#160; <span class="keyword">const</span> int32_t qOffset = 0)</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160;{</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; std::vector&lt;T&gt; inputData{ 1, -2, 3, 4, 5, 6, 7, 8 };</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; std::vector&lt;T&gt; alphaData{ 1, 2, 1, 1 };</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::vector&lt;T&gt; expectedOutputData{ 1, -4, 3, 4, 5, 6, 7, 8 };</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; PreluEndToEnd&lt;ArmnnType&gt;(backends, inputData, alphaData, expectedOutputData, qScale, qOffset);</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;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160;} <span class="comment">// anonymous namespace</span></div><div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
<div class="ttc" id="_resolve_type_8hpp_html"><div class="ttname"><a href="_resolve_type_8hpp.html">ResolveType.hpp</a></div></div>
<div class="ttc" id="_common_test_utils_8hpp_html"><div class="ttname"><a href="_common_test_utils_8hpp.html">CommonTestUtils.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_a685739c4eb65a580e075282cfe6787d6"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#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.html#l00259">Tensor.cpp:259</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_network_html_a706f7345af3f18f4b16e226a672214c6"><div class="ttname"><a href="classarmnn_1_1_i_network.html#a706f7345af3f18f4b16e226a672214c6">armnn::INetwork::Create</a></div><div class="ttdeci">static INetworkPtr Create()</div><div class="ttdef"><b>Definition:</b> <a href="_network_8cpp_source.html#l00048">Network.cpp:48</a></div></div>
<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
<div class="ttc" id="namespacearmnn_html_ace74f6f9feb95a964a49d79458232703"><div class="ttname"><a href="namespacearmnn.html#ace74f6f9feb95a964a49d79458232703">armnn::INetworkPtr</a></div><div class="ttdeci">std::unique_ptr&lt; INetwork, void(*)(INetwork *network)&gt; INetworkPtr</div><div class="ttdef"><b>Definition:</b> <a href="_i_network_8hpp_source.html#l00085">INetwork.hpp:85</a></div></div>
<div class="ttc" id="_test_utils_8cpp_html_a0b295acb179f15eb3fb862b32008f782"><div class="ttname"><a href="_test_utils_8cpp.html#a0b295acb179f15eb3fb862b32008f782">Connect</a></div><div class="ttdeci">void Connect(armnn::IConnectableLayer *from, armnn::IConnectableLayer *to, const armnn::TensorInfo &amp;tensorInfo, unsigned int fromIndex, unsigned int toIndex)</div><div class="ttdef"><b>Definition:</b> <a href="_test_utils_8cpp_source.html#l00012">TestUtils.cpp:12</a></div></div>
<div class="ttc" id="classarmnn_1_1_i_connectable_layer_html"><div class="ttname"><a href="classarmnn_1_1_i_connectable_layer.html">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.html#l00061">INetwork.hpp:61</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_a63cbc581012c957f9d68d224ddc3e43c"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#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.html#l00275">Tensor.cpp:275</a></div></div>
<div class="ttc" id="_i_network_8hpp_html"><div class="ttname"><a href="_i_network_8hpp.html">INetwork.hpp</a></div></div>
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