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101<a href="_activation_fixture_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>&#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 &quot;<a class="code" href="_tensor_copy_utils_8hpp.xhtml">TensorCopyUtils.hpp</a>&quot;</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_workload_test_utils_8hpp.xhtml">WorkloadTestUtils.hpp</a>&quot;</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;</div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="preprocessor">#include &lt;<a class="code" href="_tensor_helpers_8hpp.xhtml">test/TensorHelpers.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="preprocessor">#include &lt;boost/numeric/conversion/cast.hpp&gt;</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="preprocessor">#include &lt;boost/multi_array.hpp&gt;</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">struct </span>ActivationFixture</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;{</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160; ActivationFixture()</div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160; {</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160; <span class="keyword">auto</span> boostArrayExtents = boost::extents</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160; [<a class="code" href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">boost::numeric_cast</a>&lt;boost::multi_array_types::extent_gen::index&gt;(batchSize)]</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160; [boost::numeric_cast&lt;boost::multi_array_types::extent_gen::index&gt;(channels)]</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160; [<a class="code" href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">boost::numeric_cast</a>&lt;boost::multi_array_types::extent_gen::index&gt;(height)]</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160; [boost::numeric_cast&lt;boost::multi_array_types::extent_gen::index&gt;(width)];</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160; output.resize(boostArrayExtents);</div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160; outputExpected.resize(boostArrayExtents);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160; input.resize(boostArrayExtents);</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;</div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputShape[] = { batchSize, channels, height, width };</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputShape[] = { batchSize, channels, height, width };</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; inputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, inputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160; outputTensorInfo = <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a>(4, outputShape, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160; input = MakeRandomTensor&lt;float, 4&gt;(inputTensorInfo, 21453);</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;</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width = 17;</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 29;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> channels = 2;</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160; <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 5;</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; boost::multi_array&lt;float, 4&gt; output;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; boost::multi_array&lt;float, 4&gt; outputExpected;</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160; boost::multi_array&lt;float, 4&gt; input;</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.xhtml">armnn::TensorInfo</a> inputTensorInfo;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo;</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; <span class="comment">// Parameters used by some of the activation functions.</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; <span class="keywordtype">float</span> a = 0.234f;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160; <span class="keywordtype">float</span> b = -12.345f;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160;};</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;</div><div class="line"><a name="l00055"></a><span class="lineno"><a class="line" href="struct_positive_activation_fixture.xhtml"> 55</a></span>&#160;<span class="keyword">struct </span><a class="code" href="struct_positive_activation_fixture.xhtml">PositiveActivationFixture</a> : <span class="keyword">public</span> ActivationFixture</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"><a class="line" href="struct_positive_activation_fixture.xhtml#a42413470cac3e538dd3f8b88e9a30fdb"> 57</a></span>&#160; <a class="code" href="struct_positive_activation_fixture.xhtml#a42413470cac3e538dd3f8b88e9a30fdb">PositiveActivationFixture</a>()</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; input = MakeRandomTensor&lt;float, 4&gt;(inputTensorInfo, 2342423, 0.0f, 1.0f);</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="ttc" id="struct_positive_activation_fixture_xhtml"><div class="ttname"><a href="struct_positive_activation_fixture.xhtml">PositiveActivationFixture</a></div><div class="ttdef"><b>Definition:</b> <a href="_activation_fixture_8hpp_source.xhtml#l00055">ActivationFixture.hpp:55</a></div></div>
102<div class="ttc" id="_tensor_copy_utils_8hpp_xhtml"><div class="ttname"><a href="_tensor_copy_utils_8hpp.xhtml">TensorCopyUtils.hpp</a></div></div>
103<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>
104<div class="ttc" id="_workload_test_utils_8hpp_xhtml"><div class="ttname"><a href="_workload_test_utils_8hpp.xhtml">WorkloadTestUtils.hpp</a></div></div>
105<div class="ttc" id="_tensor_helpers_8hpp_xhtml"><div class="ttname"><a href="_tensor_helpers_8hpp.xhtml">TensorHelpers.hpp</a></div></div>
106<div class="ttc" id="struct_positive_activation_fixture_xhtml_a42413470cac3e538dd3f8b88e9a30fdb"><div class="ttname"><a href="struct_positive_activation_fixture.xhtml#a42413470cac3e538dd3f8b88e9a30fdb">PositiveActivationFixture::PositiveActivationFixture</a></div><div class="ttdeci">PositiveActivationFixture()</div><div class="ttdef"><b>Definition:</b> <a href="_activation_fixture_8hpp_source.xhtml#l00057">ActivationFixture.hpp:57</a></div></div>
107<div class="ttc" id="namespacearmnn_xhtml_a37fa39012e90d568df7f774cd6d1e956"><div class="ttname"><a href="namespacearmnn.xhtml#a37fa39012e90d568df7f774cd6d1e956">armnn::numeric_cast</a></div><div class="ttdeci">std::enable_if_t&lt; std::is_unsigned&lt; Source &gt;::value &amp;&amp;std::is_unsigned&lt; Dest &gt;::value, Dest &gt; numeric_cast(Source source)</div><div class="ttdef"><b>Definition:</b> <a href="_numeric_cast_8hpp_source.xhtml#l00033">NumericCast.hpp:33</a></div></div>
108<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div>
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