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<div class="title">GenerateProposalsLayer.cpp</div> </div>
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<a href="_generate_proposals_layer_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 (c) 2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_l_scheduler_8h.xhtml">arm_compute/runtime/CL/CLScheduler.h</a>&quot;</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_l_compute_all_anchors_8h.xhtml">arm_compute/runtime/CL/functions/CLComputeAllAnchors.h</a>&quot;</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_l_generate_proposals_layer_8h.xhtml">arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h</a>&quot;</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_l_slice_8h.xhtml">arm_compute/runtime/CL/functions/CLSlice.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_l_accessor_8h.xhtml">tests/CL/CLAccessor.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_l_array_accessor_8h.xhtml">tests/CL/CLArrayAccessor.h</a>&quot;</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_globals_8h.xhtml">tests/Globals.h</a>&quot;</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tests_2framework_2_macros_8h.xhtml">tests/framework/Macros.h</a>&quot;</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_datasets_8h.xhtml">tests/framework/datasets/Datasets.h</a>&quot;</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_validation_8h.xhtml">tests/validation/Validation.h</a>&quot;</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="preprocessor">#include &quot;tests/validation/fixtures/ComputeAllAnchorsFixture.h&quot;</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="utils_2_type_printer_8h.xhtml">utils/TypePrinter.h</a>&quot;</span></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="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></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;<span class="keyword">namespace </span>test</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;{</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160;<span class="keyword">namespace </span>validation</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;<span class="keyword">namespace</span></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="keyword">template</span> &lt;<span class="keyword">typename</span> U, <span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;<span class="keyword">inline</span> <span class="keywordtype">void</span> fill_tensor(U &amp;&amp;tensor, <span class="keyword">const</span> std::vector&lt;T&gt; &amp;v)</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; std::memcpy(tensor.data(), v.data(), <span class="keyword">sizeof</span>(T) * v.size());</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;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;<span class="keyword">const</span> <span class="keyword">auto</span> ComputeAllInfoDataset = <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;ComputeAllInfo&quot;</span>,</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; ComputeAnchorsInfo(10U, 10U, 1. / 16.f),</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; ComputeAnchorsInfo(100U, 1U, 1. / 2.f),</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160; ComputeAnchorsInfo(100U, 1U, 1. / 4.f),</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; ComputeAnchorsInfo(100U, 100U, 1. / 4.f),</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;});</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160;} <span class="comment">// namespace</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;<a class="code" href="tests_2framework_2_macros_8h.xhtml#acd09bed517e43d28823e69494f259835">TEST_SUITE</a>(CL)</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160;<a class="code" href="tests_2framework_2_macros_8h.xhtml#acd09bed517e43d28823e69494f259835">TEST_SUITE</a>(GenerateProposals)</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;<span class="comment">// *INDENT-OFF*</span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160;<span class="comment">// clang-format off</span></div><div class="line"><a name="l00066"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a70d260ea6070965cb0bab9d6559abb28"> 66</a></span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a35d3ab6d678579401ec6efeccd788c3b">DATA_TEST_CASE</a>(Validate, framework::<a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cf">DatasetMode</a>::ALL, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8b21582e176d7bf27d350e5a10e8e554">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8b21582e176d7bf27d350e5a10e8e554">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8b21582e176d7bf27d350e5a10e8e554">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8b21582e176d7bf27d350e5a10e8e554">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8b21582e176d7bf27d350e5a10e8e554">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8b21582e176d7bf27d350e5a10e8e554">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8b21582e176d7bf27d350e5a10e8e554">zip</a>(</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; framework::dataset::<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">make</a>(&quot;scores&quot;, { <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>), <span class="comment">// Mismatching types</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>), <span class="comment">// Wrong deltas (number of transformation non multiple of 4)</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>), <span class="comment">// Wrong anchors (number of values per roi != 5)</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>), <span class="comment">// Output tensor num_valid_proposals not scalar</span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>)}), <span class="comment">// num_valid_proposals not U32</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;deltas&quot;</span>,{ <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 36<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 36<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 38<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 38<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 38<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 38<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)})),</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;anchors&quot;</span>, { <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(5<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)})),</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;proposals&quot;</span>, { <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(5<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>*100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>*9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(5U, 100U*100U*9U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(5U, 100U*100U*9U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(5U, 100U*100U*9U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(5U, 100U*100U*9U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(5U, 100U*100U*9U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)})),</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;scores_out&quot;</span>, { <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>*100<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>*9<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100U*100U*9U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100U*100U*9U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100U*100U*9U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100U*100U*9U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(100U*100U*9U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)})),</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;num_valid_proposals&quot;</span>, { <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>),</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>),</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>),</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>),</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 10<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>),</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>, 1<a class="code" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">U</a>), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>)})),</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;generate_proposals_info&quot;</span>, { <a class="code" href="classarm__compute_1_1_generate_proposals_info.xhtml">GenerateProposalsInfo</a>(10.f, 10.f, 1.f),</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; <a class="code" href="classarm__compute_1_1_generate_proposals_info.xhtml">GenerateProposalsInfo</a>(10.f, 10.f, 1.f),</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <a class="code" href="classarm__compute_1_1_generate_proposals_info.xhtml">GenerateProposalsInfo</a>(10.f, 10.f, 1.f),</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <a class="code" href="classarm__compute_1_1_generate_proposals_info.xhtml">GenerateProposalsInfo</a>(10.f, 10.f, 1.f),</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; <a class="code" href="classarm__compute_1_1_generate_proposals_info.xhtml">GenerateProposalsInfo</a>(10.f, 10.f, 1.f),</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; <a class="code" href="classarm__compute_1_1_generate_proposals_info.xhtml">GenerateProposalsInfo</a>(10.f, 10.f, 1.f)})),</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;Expected&quot;</span>, { <span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span> })),</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; scores, deltas, anchors, proposals, scores_out, num_valid_proposals, generate_proposals_info, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa6e67bddae371a5731f6d4002e787299">expected</a>)</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160;{</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">ARM_COMPUTE_EXPECT</a>(<span class="keywordtype">bool</span>(<a class="code" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a0dd15c751cbdd5768cb781ef766e50dd">CLGenerateProposalsLayer::validate</a>(&amp;scores.clone()-&gt;set_is_resizable(<span class="keyword">true</span>),</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; &amp;deltas.clone()-&gt;set_is_resizable(<span class="keyword">true</span>),</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; &amp;anchors.clone()-&gt;set_is_resizable(<span class="keyword">true</span>),</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; &amp;proposals.clone()-&gt;set_is_resizable(<span class="keyword">true</span>),</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; &amp;scores_out.clone()-&gt;set_is_resizable(<span class="keyword">true</span>),</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; &amp;num_valid_proposals.clone()-&gt;set_is_resizable(<span class="keyword">true</span>),</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; generate_proposals_info)) == <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa6e67bddae371a5731f6d4002e787299">expected</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160;}</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;<span class="comment">// clang-format on</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160;<span class="comment">// *INDENT-ON*</span></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"> 123</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00124"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4241c6ea2277c5206b732934f400681f"> 124</a></span>&#160;<span class="keyword">using</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4241c6ea2277c5206b732934f400681f">CLComputeAllAnchorsFixture</a> = ComputeAllAnchorsFixture&lt;CLTensor, CLAccessor, CLComputeAllAnchors, T&gt;;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160;<a class="code" href="tests_2framework_2_macros_8h.xhtml#acd09bed517e43d28823e69494f259835">TEST_SUITE</a>(Float)</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160;<a class="code" href="tests_2framework_2_macros_8h.xhtml#acd09bed517e43d28823e69494f259835">TEST_SUITE</a>(FP32)</div><div class="line"><a name="l00128"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1c31e08a7ec435be0c95597312bdc876"> 128</a></span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a35d3ab6d678579401ec6efeccd788c3b">DATA_TEST_CASE</a>(IntegrationTestCaseAllAnchors, framework::<a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cf">DatasetMode</a>::ALL, framework::dataset::<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">make</a>(&quot;<a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a>&quot;, { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a> }),</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">data_type</a>)</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"> 131</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> values_per_roi = 4;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> num_anchors = 3;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> feature_height = 4;</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> feature_width = 3;</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> anchors_expected(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi, feature_width * feature_height * num_anchors), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160; fill_tensor(anchors_expected, std::vector&lt;float&gt; { -38, -16, 53, 31, -84, -40, 99, 55, -176, -88, 191, 103,</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; -22, -16, 69, 31, -68, -40, 115, 55, -160, -88, 207, 103,</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; -6, -16, 85, 31, -52, -40, 131, 55, -144, -88, 223, 103, -38,</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; 0, 53, 47, -84, -24, 99, 71,</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; -176, -72, 191, 119, -22, 0, 69, 47, -68, -24, 115, 71, -160, -72, 207,</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; 119, -6, 0, 85, 47, -52, -24, 131, 71, -144, -72, 223, 119, -38, 16, 53,</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; 63, -84, -8, 99, 87, -176, -56, 191, 135, -22, 16, 69, 63, -68, -8, 115,</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; 87, -160, -56, 207, 135, -6, 16, 85, 63, -52, -8, 131, 87, -144, -56, 223,</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; 135, -38, 32, 53, 79, -84, 8, 99, 103, -176, -40, 191, 151, -22, 32, 69,</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; 79, -68, 8, 115, 103, -160, -40, 207, 151, -6, 32, 85, 79, -52, 8, 131,</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; 103, -144, -40, 223, 151</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;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> all_anchors;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> anchors = create_tensor&lt;CLTensor&gt;(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4, num_anchors), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">data_type</a>);</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160;</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; <span class="comment">// Create and configure function</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_compute_all_anchors.xhtml">CLComputeAllAnchors</a> compute_anchors;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; compute_anchors.<a class="code" href="classarm__compute_1_1_c_l_compute_all_anchors.xhtml#a4475c404f4bc3140b493a987d1fa0fc6">configure</a>(&amp;anchors, &amp;all_anchors, <a class="code" href="classarm__compute_1_1_compute_anchors_info.xhtml">ComputeAnchorsInfo</a>(feature_width, feature_height, 1. / 16.0));</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; anchors.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; all_anchors.allocator()-&gt;allocate();</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160;</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; fill_tensor(<a class="code" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>(anchors), std::vector&lt;float&gt; { -38, -16, 53, 31,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; -84, -40, 99, 55,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; -176, -88, 191, 103</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"> 163</span>&#160; <span class="comment">// Compute function</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; compute_anchors.run();</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae02c6fc90d9c60c634bfa258049eb46b">validate</a>(<a class="code" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>(all_anchors), anchors_expected);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160;}</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160;</div><div class="line"><a name="l00168"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa8cbbd68453259f0c10bde13e03bde34"> 168</a></span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a35d3ab6d678579401ec6efeccd788c3b">DATA_TEST_CASE</a>(IntegrationTestCaseGenerateProposals, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;DataType&quot;</span>, { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a> }),</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">data_type</a>)</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"> 171</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> values_per_roi = 4;</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> num_anchors = 2;</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> feature_height = 4;</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; <span class="keyword">const</span> <span class="keywordtype">int</span> feature_width = 5;</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160;</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; 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5.37420018e-03f, 5.26280981e-03f, 2.48894998e-04f, 1.06842002e-04f,</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; 3.92931997e-06f, 1.79388002e-03f, 4.79440019e-03f, 3.41609990e-07f,</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; 5.20430971e-04f, 3.34090000e-05f, 2.19159006e-07f, 2.28786003e-03f,</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>&#160; 5.16703985e-05f, 4.04523007e-06f, 1.79227004e-06f, 5.32449000e-08f</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;</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>&#160; std::vector&lt;float&gt; bbx_vector</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160; {</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160; -1.65040009e-02f, -1.84051003e-02f, -1.85930002e-02f, -2.08263006e-02f,</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160; -1.83814000e-02f, -2.89172009e-02f, -3.89706008e-02f, -7.52277970e-02f,</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160; -1.54091999e-01f, -2.55433004e-02f, -1.77490003e-02f, -1.10340998e-01f,</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>&#160; -4.20190990e-02f, -2.71421000e-02f, 6.89801015e-03f, 5.71171008e-02f,</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>&#160; -1.75665006e-01f, 2.30021998e-02f, 3.08554992e-02f, -1.39333997e-02f,</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>&#160; 3.40579003e-01f, 3.91070992e-01f, 3.91624004e-01f, 3.92527014e-01f,</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>&#160; 3.91445011e-01f, 3.79328012e-01f, 4.26631987e-01f, 3.64892989e-01f,</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>&#160; 2.76894987e-01f, 5.13985991e-01f, 3.79999995e-01f, 1.80457994e-01f,</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>&#160; 4.37402993e-01f, 4.18545991e-01f, 2.51549989e-01f, 4.48318988e-01f,</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>&#160; 1.68564007e-01f, 4.65440989e-01f, 4.21891987e-01f, 4.45928007e-01f,</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>&#160; 3.27155995e-03f, 3.71480011e-03f, 3.60032008e-03f, 4.27092984e-03f,</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>&#160; 3.74579988e-03f, 5.95752988e-03f, -3.14473989e-03f, 3.52022005e-03f,</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>&#160; -1.88564006e-02f, 1.65188999e-03f, 1.73791999e-03f, -3.56074013e-02f,</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>&#160; -1.66615995e-04f, 3.14146001e-03f, -1.11830998e-02f, -5.35363983e-03f,</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>&#160; 6.49790000e-03f, -9.27671045e-03f, -2.83346009e-02f, -1.61233004e-02f,</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>&#160; -2.15505004e-01f, -2.19910994e-01f, -2.20872998e-01f, -2.12831005e-01f,</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>&#160; -2.19145000e-01f, -2.27687001e-01f, -3.43973994e-01f, -2.75869995e-01f,</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>&#160; -3.19516987e-01f, -2.50418007e-01f, -2.48537004e-01f, -5.08224010e-01f,</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>&#160; -2.28724003e-01f, -2.82402009e-01f, -3.75815988e-01f, -2.86352992e-01f,</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>&#160; -5.28333001e-02f, -4.43836004e-01f, -4.55134988e-01f, -4.34897989e-01f,</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>&#160; -5.65053988e-03f, -9.25739005e-04f, -1.06790999e-03f, -2.37016007e-03f,</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>&#160; -9.71166010e-04f, -8.90910998e-03f, -1.17592998e-02f, -2.08992008e-02f,</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>&#160; -4.94231991e-02f, 6.63906988e-03f, 3.20469006e-03f, -6.44695014e-02f,</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>&#160; -3.11607006e-03f, 2.02738005e-03f, 1.48096997e-02f, 4.39785011e-02f,</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>&#160; -8.28424022e-02f, 3.62076014e-02f, 2.71668993e-02f, 1.38250999e-02f,</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>&#160; 6.76669031e-02f, 1.03252999e-01f, 1.03255004e-01f, 9.89722982e-02f,</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>&#160; 1.03646003e-01f, 4.79663983e-02f, 1.11014001e-01f, 9.31736007e-02f,</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>&#160; 1.15768999e-01f, 1.04014002e-01f, -8.90677981e-03f, 1.13103002e-01f,</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>&#160; 1.33085996e-01f, 1.25405997e-01f, 1.50051996e-01f, -1.13038003e-01f,</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160; 7.01059997e-02f, 1.79651007e-01f, 1.41055003e-01f, 1.62841007e-01f,</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; -1.00247003e-02f, -8.17587040e-03f, -8.32176022e-03f, -8.90108012e-03f,</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; -8.13035015e-03f, -1.77263003e-02f, -3.69572006e-02f, -3.51580009e-02f,</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; -5.92143014e-02f, -1.80795006e-02f, -5.46086021e-03f, -4.10550982e-02f,</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; -1.83081999e-02f, -2.15411000e-02f, -1.17953997e-02f, 3.33894007e-02f,</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; -5.29635996e-02f, -6.97528012e-03f, -3.15250992e-03f, -3.27355005e-02f,</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; 1.29676998e-01f, 1.16080999e-01f, 1.15947001e-01f, 1.21797003e-01f,</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; 1.16089001e-01f, 1.44875005e-01f, 1.15617000e-01f, 1.31586999e-01f,</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; 1.74735002e-02f, 1.21973999e-01f, 1.31596997e-01f, 2.48907991e-02f,</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; 6.18605018e-02f, 1.12855002e-01f, -6.99798986e-02f, 9.58312973e-02f,</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; 1.53593004e-01f, -8.75087008e-02f, -4.92327996e-02f, -3.32239009e-02f</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160; };</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; std::vector&lt;float&gt; anchors_vector{ -38, -16, 53, 31,</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160; -120, -120, 135, 135 };</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; <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> proposals_expected(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(5, 9), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>&#160; fill_tensor(proposals_expected, std::vector&lt;float&gt; { 0, 0, 0, 79, 59,</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>&#160; 0, 0, 5.0005703f, 52.63237f, 43.69501495f,</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>&#160; 0, 24.13628387f, 7.51243401f, 79, 46.06628418f,</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>&#160; 0, 0, 7.50924301f, 68.47792816f, 46.03357315f,</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>&#160; 0, 0, 23.09477997f, 51.61448669f, 59,</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>&#160; 0, 0, 39.52141571f, 52.44710541f, 59,</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>&#160; 0, 23.57396317f, 29.98791885f, 79, 59,</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>&#160; 0, 0, 41.90219116f, 79, 59,</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>&#160; 0, 0, 23.30098343f, 79, 59</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>&#160; });</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; <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> scores_expected(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(9), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>&#160; fill_tensor(scores_expected, std::vector&lt;float&gt;</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; 2.66913995e-02f,</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>&#160; 5.44218998e-03f,</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>&#160; 1.20544003e-03f,</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>&#160; 1.19207997e-03f,</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>&#160; 6.17993006e-04f,</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>&#160; 4.72735002e-04f,</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>&#160; 6.09605013e-05f,</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>&#160; 1.50015003e-05f,</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>&#160; 8.91025957e-06f</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"> 262</span>&#160;</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>&#160; <span class="comment">// Inputs</span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> scores = create_tensor&lt;CLTensor&gt;(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(feature_width, feature_height, num_anchors), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">data_type</a>);</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> bbox_deltas = create_tensor&lt;CLTensor&gt;(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(feature_width, feature_height, values_per_roi * num_anchors), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">data_type</a>);</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> anchors = create_tensor&lt;CLTensor&gt;(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi, num_anchors), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">data_type</a>);</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"> 268</span>&#160; <span class="comment">// Outputs</span></div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> proposals;</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> num_valid_proposals;</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> scores_out;</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>&#160; num_valid_proposals.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>));</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"> 274</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml">CLGenerateProposalsLayer</a> generate_proposals;</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>&#160; generate_proposals.<a class="code" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a01a8a849ea1f7fb96263093b7d6978a9">configure</a>(&amp;scores, &amp;bbox_deltas, &amp;anchors, &amp;proposals, &amp;scores_out, &amp;num_valid_proposals,</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>&#160; <a class="code" href="classarm__compute_1_1_generate_proposals_info.xhtml">GenerateProposalsInfo</a>(80, 60, 0.166667f, 1 / 16.0, 6000, 300, 0.7f, 16.0f));</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>&#160;</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>&#160; <span class="comment">// Allocate memory for input/output tensors</span></div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>&#160; scores.allocator()-&gt;allocate();</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>&#160; bbox_deltas.allocator()-&gt;allocate();</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>&#160; anchors.allocator()-&gt;allocate();</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>&#160; proposals.allocator()-&gt;allocate();</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>&#160; num_valid_proposals.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>&#160; scores_out.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</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">// Fill inputs</span></div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>&#160; fill_tensor(<a class="code" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>(scores), scores_vector);</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160; fill_tensor(<a class="code" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>(bbox_deltas), bbx_vector);</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; fill_tensor(<a class="code" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>(anchors), anchors_vector);</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"> 291</span>&#160; <span class="comment">// Run operator</span></div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160; generate_proposals.<a class="code" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160;</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; <span class="comment">// Gather num_valid_proposals</span></div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; num_valid_proposals.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a14c53d2d17be6fa8a2c9861527c7b002">map</a>();</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; <span class="keyword">const</span> uint32_t N = *<span class="keyword">reinterpret_cast&lt;</span>uint32_t *<span class="keyword">&gt;</span>(num_valid_proposals.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(<a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(0, 0)));</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; num_valid_proposals.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a1ffeb3b5abb3d61f62b58a391816201c">unmap</a>();</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160;</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; <span class="comment">// Select the first N entries of the proposals</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> proposals_final;</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_slice.xhtml">CLSlice</a> select_proposals;</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; select_proposals.<a class="code" href="classarm__compute_1_1_c_l_slice.xhtml#ae883a7cb96f6111b0e8bf3a64842c438">configure</a>(&amp;proposals, &amp;proposals_final, <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(0, 0), <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(values_per_roi + 1, N));</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; proposals_final.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; select_proposals.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160;</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; <span class="comment">// Select the first N entries of the proposals</span></div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> scores_final;</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; <a class="code" href="classarm__compute_1_1_c_l_slice.xhtml">CLSlice</a> select_scores;</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; select_scores.<a class="code" href="classarm__compute_1_1_c_l_slice.xhtml#ae883a7cb96f6111b0e8bf3a64842c438">configure</a>(&amp;scores_out, &amp;scores_final, <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(0), <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(N));</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160; scores_final.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>&#160; select_scores.<a class="code" href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>&#160;</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1validation_1_1_relative_tolerance.xhtml">RelativeTolerance&lt;float&gt;</a> tolerance_f32(1e-6f);</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>&#160; <span class="comment">// Validate the output</span></div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae02c6fc90d9c60c634bfa258049eb46b">validate</a>(<a class="code" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>(proposals_final), proposals_expected, tolerance_f32);</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae02c6fc90d9c60c634bfa258049eb46b">validate</a>(<a class="code" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>(scores_final), scores_expected, tolerance_f32);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>&#160;}</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"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a915053eca2fe8b7193255831e6801e79"> 319</a></span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6b5e9878192726548c5546a4cbc175ab">FIXTURE_DATA_TEST_CASE</a>(ComputeAllAnchors, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4241c6ea2277c5206b732934f400681f">CLComputeAllAnchorsFixture&lt;float&gt;</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>,</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a092f97d313b94fd7b22c461576328682">combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a092f97d313b94fd7b22c461576328682">combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;NumAnchors&quot;</span>, { 2, 4, 8 }), ComputeAllInfoDataset), <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;DataType&quot;</span>, { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a> })))</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; <span class="comment">// Validate output</span></div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae02c6fc90d9c60c634bfa258049eb46b">validate</a>(<a class="code" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>(_target), _reference);</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"> 325</span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a38fe4b20a05bbaa1c844f3d7a19791ae">TEST_SUITE_END</a>() <span class="comment">// FP32</span></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;<a class="code" href="tests_2framework_2_macros_8h.xhtml#acd09bed517e43d28823e69494f259835">TEST_SUITE</a>(FP16)</div><div class="line"><a name="l00328"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#ab948045b334214fc919dcf54da707147"> 328</a></span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6b5e9878192726548c5546a4cbc175ab">FIXTURE_DATA_TEST_CASE</a>(ComputeAllAnchors, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4241c6ea2277c5206b732934f400681f">CLComputeAllAnchorsFixture</a>&lt;<a class="code" href="namespacearm__compute.xhtml#a73e2825fd61d349c5ca2f5313e3c8ea1">half</a>&gt;, framework::<a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cf">DatasetMode</a>::ALL,</div><div class="line"><a name="l00329"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac80f82e8dc7ce5ac80f1134cb662e0f1"> 329</a></span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a092f97d313b94fd7b22c461576328682">combine</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a092f97d313b94fd7b22c461576328682">combine</a>(framework::dataset::<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">make</a>(&quot;NumAnchors&quot;, { 2, 4, 8 }), ComputeAllInfoDataset), <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;DataType&quot;</span>, { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a> })))</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>&#160;{</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160; <span class="comment">// Validate output</span></div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae02c6fc90d9c60c634bfa258049eb46b">validate</a>(<a class="code" href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">CLAccessor</a>(_target), _reference);</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160;}</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a38fe4b20a05bbaa1c844f3d7a19791ae">TEST_SUITE_END</a>() <span class="comment">// FP16</span></div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a38fe4b20a05bbaa1c844f3d7a19791ae">TEST_SUITE_END</a>() <span class="comment">// Float</span></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="namespacearm__compute_1_1test_1_1validation.xhtml#a38fe4b20a05bbaa1c844f3d7a19791ae">TEST_SUITE_END</a>() <span class="comment">// GenerateProposals</span></div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a38fe4b20a05bbaa1c844f3d7a19791ae">TEST_SUITE_END</a>() <span class="comment">// CL</span></div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160;</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160;} <span class="comment">// namespace validation</span></div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160;} <span class="comment">// namespace test</span></div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="classarm__compute_1_1_c_l_generate_proposals_layer_xhtml_a01a8a849ea1f7fb96263093b7d6978a9"><div class="ttname"><a href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a01a8a849ea1f7fb96263093b7d6978a9">arm_compute::CLGenerateProposalsLayer::configure</a></div><div class="ttdeci">void configure(const ICLTensor *scores, const ICLTensor *deltas, const ICLTensor *anchors, ICLTensor *proposals, ICLTensor *scores_out, ICLTensor *num_valid_proposals, const GenerateProposalsInfo &amp;info)</div><div class="ttdoc">Set the input and output tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_generate_proposals_layer_8cpp_source.xhtml#l00057">CLGenerateProposalsLayer.cpp:57</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a4241c6ea2277c5206b732934f400681f"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a4241c6ea2277c5206b732934f400681f">arm_compute::test::validation::CLComputeAllAnchorsFixture</a></div><div class="ttdeci">ComputeAllAnchorsFixture&lt; CLTensor, CLAccessor, CLComputeAllAnchors, T &gt; CLComputeAllAnchorsFixture</div><div class="ttdef"><b>Definition:</b> <a href="_generate_proposals_layer_8cpp_source.xhtml#l00124">GenerateProposalsLayer.cpp:124</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_adbd73147d41e8a640bc299d12613c31e"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">arm_compute::ITensor::ptr_to_element</a></div><div class="ttdeci">uint8_t * ptr_to_element(const Coordinates &amp;id) const</div><div class="ttdoc">Return a pointer to the element at the passed coordinates. </div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00063">ITensor.h:63</a></div></div>
<div class="ttc" id="classarm__compute_1_1_generate_proposals_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_generate_proposals_info.xhtml">arm_compute::GenerateProposalsInfo</a></div><div class="ttdoc">Generate Proposals Information class. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01085">Types.h:1085</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a8b21582e176d7bf27d350e5a10e8e554"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a8b21582e176d7bf27d350e5a10e8e554">arm_compute::test::validation::zip</a></div><div class="ttdeci">zip(zip(zip(framework::dataset::make(&quot;InputInfo&quot;,{ TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::F16), TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::QASYMM8), TensorInfo(TensorShape(5U, 5U, 5U, 3U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 37U, 2U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 37U, 22U), 1, DataType::F32) }), framework::dataset::make(&quot;OutputInfo&quot;, { TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F16), TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::QASYMM8), TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F32), TensorInfo(TensorShape(1U, 1U, 16U), 1, DataType::F32), TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F32), TensorInfo(TensorShape(2U, 37U, 16U), 1, DataType::F32), TensorInfo(TensorShape(22U, 37U, 36U), 1, DataType::F32) })), framework::dataset::make(&quot;WinogradInfo&quot;, { WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(3U, 3U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(4U, 4U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW) })), framework::dataset::make(&quot;Expected&quot;, { true, false, false, false, true, true, true }))</div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_aa6e67bddae371a5731f6d4002e787299"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#aa6e67bddae371a5731f6d4002e787299">arm_compute::test::validation::expected</a></div><div class="ttdeci">expected</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00342">Winograd.cpp:342</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a73e2825fd61d349c5ca2f5313e3c8ea1"><div class="ttname"><a href="namespacearm__compute.xhtml#a73e2825fd61d349c5ca2f5313e3c8ea1">arm_compute::half</a></div><div class="ttdeci">half_float::half half</div><div class="ttdoc">16-bit floating point type </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00044">Types.h:44</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_generate_proposals_layer_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::CLGenerateProposalsLayer::run</a></div><div class="ttdeci">void run() override</div><div class="ttdoc">Run the kernels contained in the function. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_generate_proposals_layer_8cpp_source.xhtml#l00230">CLGenerateProposalsLayer.cpp:230</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_a4083de30daebd6bdee6b35d9c8262108"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">arm_compute::CLTensor::allocator</a></div><div class="ttdeci">CLTensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor&amp;#39;s allocator. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00050">CLTensor.cpp:50</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1framework_1_1dataset_xhtml_a352791fb808d42a82ad70df5efa3508b"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">arm_compute::test::framework::dataset::make</a></div><div class="ttdeci">std::enable_if&lt; is_container&lt; T &gt;::value, ContainerDataset&lt; T &gt; &gt;::type make(std::string name, T &amp;&amp;values)</div><div class="ttdoc">Helper function to create a ContainerDataset. </div><div class="ttdef"><b>Definition:</b> <a href="_container_dataset_8h_source.xhtml#l00161">ContainerDataset.h:161</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_slice_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_l_slice.xhtml">arm_compute::CLSlice</a></div><div class="ttdoc">Basic function to perform tensor slicing. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_slice_8h_source.xhtml#l00035">CLSlice.h:35</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_allocator_xhtml_af36143939a43fa124312e395975091ed"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">arm_compute::ITensorAllocator::init</a></div><div class="ttdeci">void init(const TensorInfo &amp;input, size_t alignment=0)</div><div class="ttdoc">Initialize a tensor based on the passed TensorInfo. </div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_allocator_8cpp_source.xhtml#l00038">ITensorAllocator.cpp:38</a></div></div>
<div class="ttc" id="_c_l_accessor_8h_xhtml"><div class="ttname"><a href="_c_l_accessor_8h.xhtml">CLAccessor.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2018 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_a14c53d2d17be6fa8a2c9861527c7b002"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a14c53d2d17be6fa8a2c9861527c7b002">arm_compute::CLTensor::map</a></div><div class="ttdeci">void map(bool blocking=true)</div><div class="ttdoc">Enqueue a map operation of the allocated buffer. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00055">CLTensor.cpp:55</a></div></div>
<div class="ttc" id="tests_2framework_2_macros_8h_xhtml_acd09bed517e43d28823e69494f259835"><div class="ttname"><a href="tests_2framework_2_macros_8h.xhtml#acd09bed517e43d28823e69494f259835">TEST_SUITE</a></div><div class="ttdeci">#define TEST_SUITE(SUITE_NAME)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2framework_2_macros_8h_source.xhtml#l00034">Macros.h:34</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ac2ad7f431e3446fddcd9b6b9f93c4c14"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ad7f431e3446fddcd9b6b9f93c4c14">arm_compute::test::validation::data_type</a></div><div class="ttdeci">data_type</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_arithmetic_subtraction_8cpp_source.xhtml#l00174">ArithmeticSubtraction.cpp:174</a></div></div>
<div class="ttc" id="_c_l_scheduler_8h_xhtml"><div class="ttname"><a href="_c_l_scheduler_8h.xhtml">CLScheduler.h</a></div></div>
<div class="ttc" id="_globals_8h_xhtml"><div class="ttname"><a href="_globals_8h.xhtml">Globals.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a6b5e9878192726548c5546a4cbc175ab"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a6b5e9878192726548c5546a4cbc175ab">arm_compute::test::validation::FIXTURE_DATA_TEST_CASE</a></div><div class="ttdeci">FIXTURE_DATA_TEST_CASE(RunSmall, CLAbsoluteDifferenceFixture&lt; uint8_t &gt;, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallShapes(), AbsoluteDifferenceU8Dataset))</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00083">AbsoluteDifference.cpp:83</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1framework_xhtml_a7edf31944a6144ffd493d2f9a7bfb5cf"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cf">arm_compute::test::framework::DatasetMode</a></div><div class="ttdeci">DatasetMode</div><div class="ttdoc">Possible dataset modes. </div><div class="ttdef"><b>Definition:</b> <a href="_dataset_modes_8h_source.xhtml#l00040">DatasetModes.h:40</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_compute_all_anchors_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_l_compute_all_anchors.xhtml">arm_compute::CLComputeAllAnchors</a></div><div class="ttdoc">Basic function to run CLComputeAllAnchorsKernel. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_compute_all_anchors_8h_source.xhtml#l00039">CLComputeAllAnchors.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_c_l_simple_function_xhtml_a92fe532c342ae2b07956a65520c05362"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">arm_compute::ICLSimpleFunction::run</a></div><div class="ttdeci">void run() override final</div><div class="ttdoc">Run the kernels contained in the function. </div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_simple_function_8cpp_source.xhtml#l00037">ICLSimpleFunction.cpp:37</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::Format::U32</a></div><div class="ttdoc">1 channel, 1 U32 per channel </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb"><div class="ttname"><a href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::Channel::U</a></div><div class="ttdoc">Cb/U channel. </div></div>
<div class="ttc" id="_datasets_8h_xhtml"><div class="ttname"><a href="_datasets_8h.xhtml">Datasets.h</a></div></div>
<div class="ttc" id="_c_l_slice_8h_xhtml"><div class="ttname"><a href="_c_l_slice_8h.xhtml">CLSlice.h</a></div></div>
<div class="ttc" id="utils_2_type_printer_8h_xhtml"><div class="ttname"><a href="utils_2_type_printer_8h.xhtml">TypePrinter.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_c_l_accessor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_c_l_accessor.xhtml">arm_compute::test::CLAccessor</a></div><div class="ttdoc">Accessor implementation for CLTensor objects. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_accessor_8h_source.xhtml#l00035">CLAccessor.h:35</a></div></div>
<div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item. </div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
<div class="ttc" id="tests_2framework_2_macros_8h_xhtml"><div class="ttname"><a href="tests_2framework_2_macros_8h.xhtml">Macros.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_slice_xhtml_ae883a7cb96f6111b0e8bf3a64842c438"><div class="ttname"><a href="classarm__compute_1_1_c_l_slice.xhtml#ae883a7cb96f6111b0e8bf3a64842c438">arm_compute::CLSlice::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output, const Coordinates &amp;starts, const Coordinates &amp;ends)</div><div class="ttdoc">Configure kernel. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_slice_8cpp_source.xhtml#l00034">CLSlice.cpp:34</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a35d3ab6d678579401ec6efeccd788c3b"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a35d3ab6d678579401ec6efeccd788c3b">arm_compute::test::validation::DATA_TEST_CASE</a></div><div class="ttdeci">DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), AbsoluteDifferenceU8Dataset), shape, data_type0, data_type1, output_data_type)</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00060">AbsoluteDifference.cpp:60</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_generate_proposals_layer_xhtml_a0dd15c751cbdd5768cb781ef766e50dd"><div class="ttname"><a href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a0dd15c751cbdd5768cb781ef766e50dd">arm_compute::CLGenerateProposalsLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *scores, const ITensorInfo *deltas, const ITensorInfo *anchors, const ITensorInfo *proposals, const ITensorInfo *scores_out, const ITensorInfo *num_valid_proposals, const GenerateProposalsInfo &amp;info)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLGenerateProposalsLayer...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_generate_proposals_layer_8cpp_source.xhtml#l00140">CLGenerateProposalsLayer.cpp:140</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::CLTensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of OpenCL memory. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_allocator_8cpp_source.xhtml#l00074">CLTensorAllocator.cpp:74</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">arm_compute::test::SimpleTensor</a></div><div class="ttdoc">Simple tensor object that stores elements in a consecutive chunk of memory. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00059">SimpleTensor.h:59</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a092f97d313b94fd7b22c461576328682"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a092f97d313b94fd7b22c461576328682">arm_compute::test::validation::combine</a></div><div class="ttdeci">combine(combine(framework::dataset::concat(datasets::SmallShapes(), datasets::LargeShapes()), framework::dataset::make(&quot;DataType&quot;, { DataType::U8, DataType::S16 })), framework::dataset::make(&quot;ConvertPolicy&quot;, { ConvertPolicy::SATURATE, ConvertPolicy::WRAP }))</div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_compute_all_anchors_xhtml_a4475c404f4bc3140b493a987d1fa0fc6"><div class="ttname"><a href="classarm__compute_1_1_c_l_compute_all_anchors.xhtml#a4475c404f4bc3140b493a987d1fa0fc6">arm_compute::CLComputeAllAnchors::configure</a></div><div class="ttdeci">void configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &amp;info)</div><div class="ttdoc">Set the input and output tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_compute_all_anchors_8cpp_source.xhtml#l00030">CLComputeAllAnchors.cpp:30</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_ae02c6fc90d9c60c634bfa258049eb46b"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ae02c6fc90d9c60c634bfa258049eb46b">arm_compute::test::validation::validate</a></div><div class="ttdeci">validate(dst.info() -&gt;valid_region(), valid_region)</div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a38fe4b20a05bbaa1c844f3d7a19791ae"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a38fe4b20a05bbaa1c844f3d7a19791ae">arm_compute::test::validation::TEST_SUITE_END</a></div><div class="ttdeci">TEST_SUITE_END() DATA_TEST_CASE(Configuration</div></div>
<div class="ttc" id="_c_l_compute_all_anchors_8h_xhtml"><div class="ttname"><a href="_c_l_compute_all_anchors_8h.xhtml">CLComputeAllAnchors.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1validation_1_1_relative_tolerance_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1validation_1_1_relative_tolerance.xhtml">arm_compute::test::validation::RelativeTolerance</a></div><div class="ttdoc">Class reprensenting a relative tolerance value. </div><div class="ttdef"><b>Definition:</b> <a href="_validation_8h_source.xhtml#l00086">Validation.h:86</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_af3c1de77fd86df539395c75c17ec230e"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#af3c1de77fd86df539395c75c17ec230e">arm_compute::test::validation::ARM_COMPUTE_EXPECT</a></div><div class="ttdeci">ARM_COMPUTE_EXPECT(src.info() -&gt;is_resizable(), framework::LogLevel::ERRORS)</div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1framework_xhtml_a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">arm_compute::test::framework::DatasetMode::ALL</a></div></div>
<div class="ttc" id="_c_l_generate_proposals_layer_8h_xhtml"><div class="ttname"><a href="_c_l_generate_proposals_layer_8h.xhtml">CLGenerateProposalsLayer.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_compute_anchors_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_compute_anchors_info.xhtml">arm_compute::ComputeAnchorsInfo</a></div><div class="ttdoc">ComputeAnchors information class. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01166">Types.h:1166</a></div></div>
<div class="ttc" id="_validation_8h_xhtml"><div class="ttname"><a href="_validation_8h.xhtml">Validation.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor&amp;#39;s metadata. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1framework_xhtml_aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">arm_compute::test::framework::LogLevel::ERRORS</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_generate_proposals_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml">arm_compute::CLGenerateProposalsLayer</a></div><div class="ttdoc">Basic function to generate proposals for a RPN (Region Proposal Network) </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_generate_proposals_layer_8h_source.xhtml#l00058">CLGenerateProposalsLayer.h:58</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00074">Types.h:74</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_a1ffeb3b5abb3d61f62b58a391816201c"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a1ffeb3b5abb3d61f62b58a391816201c">arm_compute::CLTensor::unmap</a></div><div class="ttdeci">void unmap()</div><div class="ttdoc">Enqueue an unmap operation of the allocated and mapped buffer. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00060">CLTensor.cpp:60</a></div></div>
<div class="ttc" id="_c_l_array_accessor_8h_xhtml"><div class="ttname"><a href="_c_l_array_accessor_8h.xhtml">CLArrayAccessor.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml">arm_compute::CLTensor</a></div><div class="ttdoc">Basic implementation of the OpenCL tensor interface. </div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8h_source.xhtml#l00039">CLTensor.h:39</a></div></div>
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<li class="navelem"><a class="el" href="dir_59425e443f801f1f2fd8bbe4959a3ccf.xhtml">tests</a></li><li class="navelem"><a class="el" href="dir_e7c7b16542faa38cb4655ff1750d3604.xhtml">validation</a></li><li class="navelem"><a class="el" href="dir_f7024513cd67abef53e86ee9382ac5ce.xhtml">CL</a></li><li class="navelem"><a class="el" href="_generate_proposals_layer_8cpp.xhtml">GenerateProposalsLayer.cpp</a></li>
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