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<div class="title">TopKV.cpp</div> </div>
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<a href="_top_k_v_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) 2019 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="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.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_p_p_top_k_v_8h.xhtml">arm_compute/runtime/CPP/functions/CPPTopKV.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="runtime_2_tensor_8h.xhtml">arm_compute/runtime/Tensor.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="_tensor_allocator_8h.xhtml">arm_compute/runtime/TensorAllocator.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="_accessor_8h.xhtml">tests/NEON/Accessor.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="_padding_calculator_8h.xhtml">tests/PaddingCalculator.h</a>&quot;</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="preprocessor">#include &quot;tests/datasets/ShapeDatasets.h&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="_asserts_8h.xhtml">tests/framework/Asserts.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="tests_2framework_2_macros_8h.xhtml">tests/framework/Macros.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="_datasets_8h.xhtml">tests/framework/datasets/Datasets.h</a>&quot;</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</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="l00035"></a><span class="lineno"> 35</span>&#160;<span class="preprocessor">#include &quot;tests/validation/fixtures/PermuteFixture.h&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> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6a5eef7d8485a2b8c04bf9b4638a90e9">fill_tensor</a>(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;} <span class="comment">// namespace</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8f65156abdd90180036790221cfc915f">TEST_SUITE</a>(CPP)</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8f65156abdd90180036790221cfc915f">TEST_SUITE</a>(TopKV)</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;<span class="comment">// *INDENT-OFF*</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160;<span class="comment">// clang-format off</span></div><div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a822e5814a7ccc966d5bac4d5f2fb0ebe"> 57</a></span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f1266d183bfb4d479ec334fed85dc27">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#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; framework::dataset::<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">make</a>(&quot;PredictionsInfo&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>(20, 10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</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>(10, 20), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>), <span class="comment">// Mismatching batch_size</span></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</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>(20, 10), 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">DataType::S8</a>), <span class="comment">// Unsupported data type</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</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>(10, 10, 10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>), <span class="comment">// Wrong predictions dimensions</span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</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>(20, 10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)}), <span class="comment">// Wrong output dimension</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;TargetsInfo&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>(10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>),</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</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>(10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>),</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</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>(10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>),</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</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>(10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>),</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</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>(10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>)})),</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;OutputInfo&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>(10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>),</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>(10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>),</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>(10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>),</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>(10), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>),</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>(1), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>)})),</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">&quot;k&quot;</span>,{ 0, 1, 2, 3, 4 })),</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</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> })),</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; prediction_info, targets_info, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a25cae7166733a51d1354f3f395652782">output_info</a>, k, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa6e67bddae371a5731f6d4002e787299">expected</a>)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160;{</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keyword">const</span> Status status = <a class="code" href="classarm__compute_1_1_c_p_p_top_k_v.xhtml#a78f9128e5b414dc15c66d2d21d55117c">CPPTopKV::validate</a>(&amp;prediction_info.clone()-&gt;set_is_resizable(<span class="keyword">false</span>),&amp;targets_info.clone()-&gt;set_is_resizable(<span class="keyword">false</span>), &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a25cae7166733a51d1354f3f395652782">output_info</a>.clone()-&gt;set_is_resizable(<span class="keyword">false</span>), k);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3c8562a1f05d23f44aed87545b7892cf">ARM_COMPUTE_EXPECT</a>(<span class="keywordtype">bool</span>(status) == <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="l00080"></a><span class="lineno"> 80</span>&#160;}</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160;<span class="comment">// clang-format on</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160;<span class="comment">// *INDENT-ON*</span></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160;</div><div class="line"><a name="l00084"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3f20e3c02fe7bf3da8f52d3fbaec2178"> 84</a></span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a963c5b8a3279186004d6a7e97a1b87e6">TEST_CASE</a>(Float, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>)</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160;{</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> k = 5;</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> predictions = create_tensor&lt;Tensor&gt;(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(10, 20), <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.xhtml">Tensor</a> targets = create_tensor&lt;Tensor&gt;(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(20), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160;</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160; predictions.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; targets.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <span class="comment">// Fill the tensors with random pre-generated values</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6a5eef7d8485a2b8c04bf9b4638a90e9">fill_tensor</a>(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(predictions), std::vector&lt;float&gt;</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; {</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; 0.8147, 0.6557, 0.4387, 0.7513, 0.3517, 0.1622, 0.1067, 0.8530, 0.7803, 0.5470,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; 0.9058, 0.0357, 0.3816, 0.2551, 0.8308, 0.7943, 0.9619, 0.6221, 0.3897, 0.2963,</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; 0.1270, 0.8491, 0.7655, 0.5060, 0.5853, 0.3112, 0.0046, 0.3510, 0.2417, 0.7447,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; 0.9134, 0.9340, 0.7952, 0.6991, 0.5497, 0.5285, 0.7749, 0.5132, 0.4039, 0.1890,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; 0.6324, 0.6787, 0.1869, 0.8909, 0.9172, 0.1656, 0.8173, 0.4018, 0.0965, 0.6868,</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; 0.0975, 0.7577, 0.4898, 0.9593, 0.2858, 0.6020, 0.8687, 0.0760, 0.1320, 0.1835,</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; 0.2785, 0.7431, 0.4456, 0.5472, 0.7572, 0.2630, 0.0844, 0.2399, 0.9421, 0.3685,</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; 0.5469, 0.3922, 0.6463, 0.1386, 0.7537, 0.6541, 0.3998, 0.1233, 0.9561, 0.6256,</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; 0.9575, 0.6555, 0.7094, 0.1493, 0.3804, 0.6892, 0.2599, 0.1839, 0.5752, 0.7802,</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; 0.9649, 0.1712, 0.7547, 0.2575, 0.5678, 0.7482, 0.8001, 0.2400, 0.0598, 0.0811,</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160; 0.1576, 0.7060, 0.2760, 0.8407, 0.0759, 0.4505, 0.4314, 0.4173, 0.2348, 0.9294,</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; 0.9706, 0.0318, 0.6797, 0.2543, 0.0540, 0.0838, 0.9106, 0.0497, 0.3532, 0.7757,</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; 0.9572, 0.2769, 0.6551, 0.8143, 0.5308, 0.2290, 0.1818, 0.9027, 0.8212, 0.4868,</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; 0.4854, 0.0462, 0.1626, 0.2435, 0.7792, 0.9133, 0.2638, 0.9448, 0.0154, 0.4359,</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; 0.8003, 0.0971, 0.1190, 0.9293, 0.9340, 0.1524, 0.1455, 0.4909, 0.0430, 0.4468,</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; 0.1419, 0.8235, 0.4984, 0.3500, 0.1299, 0.8258, 0.1361, 0.4893, 0.1690, 0.3063,</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; 0.4218, 0.6948, 0.9597, 0.1966, 0.5688, 0.5383, 0.8693, 0.3377, 0.6491, 0.5085,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; 0.9157, 0.3171, 0.3404, 0.2511, 0.4694, 0.9961, 0.5797, 0.9001, 0.7317, 0.5108,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; 0.7922, 0.9502, 0.5853, 0.6160, 0.0119, 0.0782, 0.5499, 0.3692, 0.6477, 0.8176,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; 0.9595, 0.0344, 0.2238, 0.4733, 0.3371, 0.4427, 0.1450, 0.1112, 0.4509, 0.7948</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; });</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6a5eef7d8485a2b8c04bf9b4638a90e9">fill_tensor</a>(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(targets), std::vector&lt;int&gt; { 1, 5, 7, 2, 8, 1, 2, 1, 2, 4, 3, 9, 4, 1, 9, 9, 4, 1, 2, 4 });</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="comment">// Determine the output through the CPP kernel</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> output;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; <a class="code" href="classarm__compute_1_1_c_p_p_top_k_v.xhtml">CPPTopKV</a> topkv;</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; topkv.<a class="code" href="classarm__compute_1_1_c_p_p_top_k_v.xhtml#ac886f64c915621a8a213f760bc0d9134">configure</a>(&amp;predictions, &amp;targets, &amp;output, k);</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; output.allocator()-&gt;allocate();</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160;</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; <span class="comment">// Run the kernel</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; topkv.<a class="code" href="classarm__compute_1_1_i_c_p_p_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</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="comment">// Validate against the expected values</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint8_t&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8ad4a9123e325f198138c3ecf1993616">expected_output</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(20), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6a5eef7d8485a2b8c04bf9b4638a90e9">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8ad4a9123e325f198138c3ecf1993616">expected_output</a>, std::vector&lt;uint8_t&gt; { 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 0 });</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</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_accessor.xhtml">Accessor</a>(output), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8ad4a9123e325f198138c3ecf1993616">expected_output</a>);</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;</div><div class="line"><a name="l00137"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a43d6fccd8ec91f04ba8f9e56f796c8f0"> 137</a></span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a963c5b8a3279186004d6a7e97a1b87e6">TEST_CASE</a>(Quantized, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>)</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160;{</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <span class="keyword">const</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> k = 5;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> predictions = create_tensor&lt;Tensor&gt;(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(10, 20), <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>, 1, <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a>());</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> targets = create_tensor&lt;Tensor&gt;(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(20), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160;</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; predictions.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; targets.<a class="code" href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">allocator</a>()-&gt;<a class="code" href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; <span class="comment">// Fill the tensors with random pre-generated values</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6a5eef7d8485a2b8c04bf9b4638a90e9">fill_tensor</a>(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(predictions), std::vector&lt;uint8_t&gt;</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; 133, 235, 69, 118, 140, 179, 189, 203, 137, 157,</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; 242, 1, 196, 170, 166, 25, 102, 244, 24, 254,</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; 164, 119, 49, 198, 140, 135, 175, 84, 29, 136,</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; 246, 109, 74, 90, 185, 136, 181, 172, 35, 123,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; 62, 118, 24, 170, 134, 221, 114, 113, 174, 206,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; 174, 198, 148, 107, 255, 125, 6, 214, 127, 59,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; 75, 83, 175, 216, 56, 101, 85, 197, 49, 128,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; 172, 201, 140, 214, 28, 172, 109, 43, 127, 231,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; 178, 121, 109, 66, 29, 190, 70, 221, 38, 148,</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; 18, 10, 165, 158, 17, 134, 51, 254, 15, 217,</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160; 66, 46, 166, 150, 104, 90, 211, 132, 218, 190,</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; 58, 185, 174, 139, 115, 39, 111, 227, 144, 151,</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; 171, 122, 163, 223, 94, 151, 228, 151, 238, 64,</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; 217, 40, 242, 68, 196, 68, 101, 40, 179, 171,</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; 89, 88, 54, 82, 161, 12, 197, 52, 150, 22,</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160; 200, 156, 182, 31, 198, 194, 102, 105, 209, 161,</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; 173, 50, 61, 241, 239, 63, 207, 192, 226, 170,</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160; 2, 190, 31, 166, 250, 114, 194, 212, 254, 187,</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160; 155, 63, 156, 123, 50, 177, 97, 203, 1, 229,</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160; 100, 235, 116, 164, 36, 92, 56, 82, 222, 252</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;</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6a5eef7d8485a2b8c04bf9b4638a90e9">fill_tensor</a>(<a class="code" href="classarm__compute_1_1test_1_1_accessor.xhtml">Accessor</a>(targets), std::vector&lt;int&gt; { 1, 5, 7, 2, 8, 1, 2, 1, 2, 4, 3, 9, 4, 1, 9, 9, 4, 1, 2, 4 });</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160;</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160; <span class="comment">// Determine the output through the CPP kernel</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160; <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> output;</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160; <a class="code" href="classarm__compute_1_1_c_p_p_top_k_v.xhtml">CPPTopKV</a> topkv;</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160; topkv.<a class="code" href="classarm__compute_1_1_c_p_p_top_k_v.xhtml#ac886f64c915621a8a213f760bc0d9134">configure</a>(&amp;predictions, &amp;targets, &amp;output, k);</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160;</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160; output.allocator()-&gt;allocate();</div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160;</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>&#160; <span class="comment">// Run the kernel</span></div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>&#160; topkv.<a class="code" href="classarm__compute_1_1_i_c_p_p_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">run</a>();</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>&#160;</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>&#160; <span class="comment">// Validate against the expected values</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint8_t&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8ad4a9123e325f198138c3ecf1993616">expected_output</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(20), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>);</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6a5eef7d8485a2b8c04bf9b4638a90e9">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8ad4a9123e325f198138c3ecf1993616">expected_output</a>, std::vector&lt;uint8_t&gt; { 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 });</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</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_accessor.xhtml">Accessor</a>(output), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8ad4a9123e325f198138c3ecf1993616">expected_output</a>);</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;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ed31007ae463a3cec24a581f3651f6">TEST_SUITE_END</a>() <span class="comment">// TopKV</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>&#160;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ed31007ae463a3cec24a581f3651f6">TEST_SUITE_END</a>() <span class="comment">// CPP</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>&#160;} <span class="comment">// namespace validation</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>&#160;} <span class="comment">// namespace test</span></div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="_accessor_8h_xhtml"><div class="ttname"><a href="_accessor_8h.xhtml">Accessor.h</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="_padding_calculator_8h_xhtml"><div class="ttname"><a href="_padding_calculator_8h.xhtml">PaddingCalculator.h</a></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_batch_normalization_layer_8cpp_source.xhtml#l00197">BatchNormalizationLayer.cpp:197</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::Format::U8</a></div><div class="ttdoc">1 channel, 1 U8 per channel</div></div>
<div class="ttc" id="_tensor_allocator_8h_xhtml"><div class="ttname"><a href="_tensor_allocator_8h.xhtml">TensorAllocator.h</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="namespacearm__compute_1_1test_1_1validation_xhtml_a3c8562a1f05d23f44aed87545b7892cf"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a3c8562a1f05d23f44aed87545b7892cf">arm_compute::test::validation::ARM_COMPUTE_EXPECT</a></div><div class="ttdeci">ARM_COMPUTE_EXPECT(has_error==expected, framework::LogLevel::ERRORS)</div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a25cae7166733a51d1354f3f395652782"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a25cae7166733a51d1354f3f395652782">arm_compute::test::validation::output_info</a></div><div class="ttdeci">output_info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_winograd_8cpp_source.xhtml#l00328">Winograd.cpp:328</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="namespacearm__compute_1_1test_1_1validation_xhtml_a8ad4a9123e325f198138c3ecf1993616"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a8ad4a9123e325f198138c3ecf1993616">arm_compute::test::validation::expected_output</a></div><div class="ttdeci">SimpleTensor&lt; uint8_t &gt; expected_output(output_shape, DataType::QASYMM8, 1, qasymm)</div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a963c5b8a3279186004d6a7e97a1b87e6"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a963c5b8a3279186004d6a7e97a1b87e6">arm_compute::test::validation::TEST_CASE</a></div><div class="ttdeci">TEST_CASE(Configuration, framework::DatasetMode::ALL)</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_batch_concatenate_layer_8cpp_source.xhtml#l00086">BatchConcatenateLayer.cpp:86</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) 2017-2020 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_tensor_xhtml_adbd0cf83a8e1b335a9bf405a8e5019fa"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml#adbd0cf83a8e1b335a9bf405a8e5019fa">arm_compute::Tensor::allocator</a></div><div class="ttdeci">TensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8cpp_source.xhtml#l00048">Tensor.cpp:48</a></div></div>
<div class="ttc" id="classarm__compute_1_1_quantization_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_quantization_info.xhtml">arm_compute::QuantizationInfo</a></div><div class="ttdoc">Quantization information.</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00069">QuantizationInfo.h:69</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_accessor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_accessor.xhtml">arm_compute::test::Accessor</a></div><div class="ttdoc">Accessor implementation for Tensor objects.</div><div class="ttdef"><b>Definition:</b> <a href="_accessor_8h_source.xhtml#l00035">Accessor.h:35</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="namespacearm__compute_1_1test_1_1validation_xhtml_a6a5eef7d8485a2b8c04bf9b4638a90e9"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a6a5eef7d8485a2b8c04bf9b4638a90e9">arm_compute::test::validation::fill_tensor</a></div><div class="ttdeci">fill_tensor(input_to_input_weights, std::vector&lt; uint8_t &gt;{ 122, 130, 124, 134, 120, 122, 134, 134 })</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="_datasets_8h_xhtml"><div class="ttname"><a href="_datasets_8h.xhtml">Datasets.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_p_p_top_k_v_xhtml_ac886f64c915621a8a213f760bc0d9134"><div class="ttname"><a href="classarm__compute_1_1_c_p_p_top_k_v.xhtml#ac886f64c915621a8a213f760bc0d9134">arm_compute::CPPTopKV::configure</a></div><div class="ttdeci">void configure(const ITensor *predictions, const ITensor *targets, ITensor *output, const unsigned int k)</div><div class="ttdoc">Set the input and output of the kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_top_k_v_8cpp_source.xhtml#l00031">CPPTopKV.cpp:31</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::DataType::QASYMM8</a></div><div class="ttdoc">quantized, asymmetric fixed-point 8-bit number unsigned</div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::TensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of CPU memory.</div><div class="ttdef"><b>Definition:</b> <a href="src_2runtime_2_tensor_allocator_8cpp_source.xhtml#l00133">TensorAllocator.cpp:133</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml">arm_compute::Tensor</a></div><div class="ttdoc">Basic implementation of the tensor interface.</div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8h_source.xhtml#l00037">Tensor.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="_c_p_p_top_k_v_8h_xhtml"><div class="ttname"><a href="_c_p_p_top_k_v_8h.xhtml">CPPTopKV.h</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&lt; uint8_t &gt;</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_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="namespacearm__compute_1_1test_1_1validation_xhtml_ac2ed31007ae463a3cec24a581f3651f6"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ed31007ae463a3cec24a581f3651f6">arm_compute::test::validation::TEST_SUITE_END</a></div><div class="ttdeci">TEST_SUITE_END() FIXTURE_DATA_TEST_CASE(RunSmall</div><div class="ttdoc">Input data sets.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_dequantization_layer_8cpp_source.xhtml#l00137">DequantizationLayer.cpp:137</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'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_i_c_p_p_simple_function_xhtml_a92fe532c342ae2b07956a65520c05362"><div class="ttname"><a href="classarm__compute_1_1_i_c_p_p_simple_function.xhtml#a92fe532c342ae2b07956a65520c05362">arm_compute::ICPPSimpleFunction::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_p_p_simple_function_8cpp_source.xhtml#l00035">ICPPSimpleFunction.cpp:35</a></div></div>
<div class="ttc" id="classarm__compute_1_1_c_p_p_top_k_v_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_p_p_top_k_v.xhtml">arm_compute::CPPTopKV</a></div><div class="ttdoc">Basic function to run CPPTopKVKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_top_k_v_8h_source.xhtml#l00036">CPPTopKV.h:36</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a96f9e78d0c2a93f0e3a876eeae4be4b0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">arm_compute::test::validation::zip</a></div><div class="ttdeci">zip(zip(framework::dataset::make(&quot;Weights&quot;, { TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U, 2U), 1, DataType::F32), TensorInfo(TensorShape(32U, 13U, 2U, 1U), 1, DataType::F32), }), framework::dataset::make(&quot;MVBGInfo&quot;,{ TensorInfo(TensorShape(2U), 1, DataType::F32), TensorInfo(TensorShape(2U), 1, DataType::F16), TensorInfo(TensorShape(5U), 1, DataType::F32), })), framework::dataset::make(&quot;Expected&quot;, { true, false, false}))</div></div>
<div class="ttc" id="arm__compute_2core_2_types_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_types_8h.xhtml">Types.h</a></div></div>
<div class="ttc" id="runtime_2_tensor_8h_xhtml"><div class="ttname"><a href="runtime_2_tensor_8h.xhtml">Tensor.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">arm_compute::DataType::S8</a></div><div class="ttdoc">signed 8-bit number</div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a8f65156abdd90180036790221cfc915f"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a8f65156abdd90180036790221cfc915f">arm_compute::test::validation::TEST_SUITE</a></div><div class="ttdeci">TEST_SUITE(U8_to_S8) DATA_TEST_CASE(Configuration</div></div>
<div class="ttc" id="_asserts_8h_xhtml"><div class="ttname"><a href="_asserts_8h.xhtml">Asserts.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a1f1266d183bfb4d479ec334fed85dc27"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f1266d183bfb4d479ec334fed85dc27">arm_compute::test::validation::DATA_TEST_CASE</a></div><div class="ttdeci">DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(datasets::SmallShapes(), 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_p_p_top_k_v_xhtml_a78f9128e5b414dc15c66d2d21d55117c"><div class="ttname"><a href="classarm__compute_1_1_c_p_p_top_k_v.xhtml#a78f9128e5b414dc15c66d2d21d55117c">arm_compute::CPPTopKV::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *predictions, const ITensorInfo *targets, ITensorInfo *output, const unsigned int k)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CPPTopKVKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_top_k_v_8cpp_source.xhtml#l00038">CPPTopKV.cpp:38</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_420d2db1b9c99f59825a3985434c3703.xhtml">CPP</a></li><li class="navelem"><a class="el" href="_top_k_v_8cpp.xhtml">TopKV.cpp</a></li>
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