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| <a href="_simple_tensor_8h.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2017-2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <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> <span class="comment"> * of this software and associated documentation files (the "Software"), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <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> <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> <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> <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> <span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <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> <span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <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> <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> <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> <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> <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> <span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#ifndef __ARM_COMPUTE_TEST_SIMPLE_TENSOR_H__</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define __ARM_COMPUTE_TEST_SIMPLE_TENSOR_H__</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="_tensor_shape_8h.xhtml">arm_compute/core/TensorShape.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="arm__compute_2core_2_utils_8h.xhtml">arm_compute/core/Utils.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_toolchain_support_8h.xhtml">support/ToolchainSupport.h</a>"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="_i_accessor_8h.xhtml">tests/IAccessor.h</a>"</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="tests_2_utils_8h.xhtml">tests/Utils.h</a>"</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include <algorithm></span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include <array></span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include <cstddef></span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#include <cstdint></span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#include <functional></span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include <memory></span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="preprocessor">#include <stdexcept></span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="preprocessor">#include <utility></span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> {</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">namespace </span>test</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="keyword">class </span>RawTensor;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml"> 59</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1_i_accessor.xhtml">IAccessor</a></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> {</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">format</a>);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> shape, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a> = 1,</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="structarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a> = <a class="code" href="structarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a>(),</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a> = <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &tensor);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad4622eda610d53fb6852209f0213aeed">operator=</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> tensor);</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &&) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a16d7ecd97f89cf9dc40b3fc7c9abe2cd">~SimpleTensor</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div><div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#afb9ded5f49336ae503bb9f2035ea902b"> 104</a></span>  <span class="keyword">using</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#afb9ded5f49336ae503bb9f2035ea902b">value_type</a> = T;</div><div class="line"><a name="l00106"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f"> 106</a></span>  <span class="keyword">using</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f">Buffer</a> = std::unique_ptr<value_type[]>;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00108"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a467ad6d14558452f498777a7823fa252"> 108</a></span>  <span class="keyword">friend</span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a>;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  T &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">const</span> T &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>) <span class="keyword">const</span>;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">element_size</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">size</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">format</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">num_elements</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a79e20eacb1e963e24a21ebd7369effd7">padding</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="code" href="structarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keyword">const</span> T *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  T *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>();</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keyword">const</span> <span class="keywordtype">void</span> *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &coord) <span class="keyword">const override</span>;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> </div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordtype">void</span> *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &coord) <span class="keyword">override</span>;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U></div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keyword">friend</span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<U></a> &tensor1, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<U></a> &tensor2);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> <span class="keyword">protected</span>:</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f">Buffer</a> _buffer{ <span class="keyword">nullptr</span> };</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> _shape{};</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> _format{ <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">Format::UNKNOWN</a> };</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> _data_type{ <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataType::UNKNOWN</a> };</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keywordtype">int</span> _num_channels{ 0 };</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="code" href="structarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> _quantization_info{};</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> _data_layout{ <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataLayout::UNKNOWN</a> };</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> };</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> </div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00224"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a057b52c2d0c51f410da5e48f47706c4e"> 224</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor<T>::SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">format</a>)</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  : _buffer(nullptr),</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  _shape(shape),</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  _format(format),</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  _quantization_info(),</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  _data_layout(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a>::<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">NCHW</a>)</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> {</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  _num_channels = <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>();</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  _buffer = support::cpp14::make_unique<T[]>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">num_elements</a>() * _num_channels);</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> }</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> </div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00236"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad2a966c334c9bb65621f891ff5e2b5bb"> 236</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor<T>::SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>, <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>, <a class="code" href="structarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a>)</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  : _buffer(nullptr),</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  _shape(shape),</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  _data_type(data_type),</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  _num_channels(num_channels),</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  _quantization_info(quantization_info),</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  _data_layout(data_layout)</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> {</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  _buffer = support::cpp14::make_unique<T[]>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">num_elements</a>() * this-><a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>());</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> }</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> </div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00248"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ae1769959044a4356fdc93cac2b03a5f6"> 248</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor<T>::SimpleTensor</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &tensor)</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  : _buffer(nullptr),</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  _shape(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>()),</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  _format(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">format</a>()),</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  _data_type(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>()),</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  _num_channels(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>()),</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  _quantization_info(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>()),</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  _data_layout(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a>())</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> {</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  _buffer = support::cpp14::make_unique<T[]>(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">num_elements</a>() * <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>());</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  std::copy_n(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">data</a>(), <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">num_elements</a>() * <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>(), _buffer.get());</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> }</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> </div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00262"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad4622eda610d53fb6852209f0213aeed"> 262</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad4622eda610d53fb6852209f0213aeed">SimpleTensor<T>::operator=</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> tensor)</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> {</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(*<span class="keyword">this</span>, tensor);</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> </div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> }</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> </div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00270"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52"> 270</a></span> T &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">SimpleTensor<T>::operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>)</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> {</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keywordflow">return</span> _buffer[<a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>];</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> }</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> </div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00276"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a73aecdf45b3f257e0c15757a18573ea4"> 276</a></span> <span class="keyword">const</span> T &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">SimpleTensor<T>::operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>)<span class="keyword"> const</span></div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> <span class="keyword"></span>{</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="keywordflow">return</span> _buffer[<a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>];</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> }</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> </div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00282"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba"> 282</a></span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">SimpleTensor<T>::shape</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span> <span class="keyword"></span>{</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="keywordflow">return</span> _shape;</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> }</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00288"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23"> 288</a></span> <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">SimpleTensor<T>::element_size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span> <span class="keyword"></span>{</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>() * <a class="code" href="namespacearm__compute.xhtml#a34b06c0cd94808a77b697e79880b84b0">element_size_from_data_type</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>());</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> }</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> </div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00294"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44"> 294</a></span> <a class="code" href="structarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">SimpleTensor<T>::quantization_info</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> <span class="keyword"></span>{</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  <span class="keywordflow">return</span> _quantization_info;</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> }</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16"> 300</a></span> <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">SimpleTensor<T>::size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> <span class="keyword"></span>{</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">size</a> = <a class="code" href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">std::accumulate</a>(_shape.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a4498730adaf901d945c12841df994bba">cbegin</a>(), _shape.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#adf9b6d55d708c285d58511a780e937fc">cend</a>(), 1, std::multiplies<size_t>());</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keywordflow">return</span> size * <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">element_size</a>();</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> }</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> </div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00307"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db"> 307</a></span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">SimpleTensor<T>::format</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="keyword"></span>{</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordflow">return</span> _format;</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> }</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> </div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00313"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c"> 313</a></span> <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">SimpleTensor<T>::data_layout</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="keyword"></span>{</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="keywordflow">return</span> _data_layout;</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> }</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> </div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00319"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881"> 319</a></span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">SimpleTensor<T>::data_type</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> <span class="keyword"></span>{</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keywordflow">if</span>(_format != <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">Format::UNKNOWN</a>)</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  {</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a59846ef5ca75cd81cdb7e8a1ce08f9db">data_type_from_format</a>(_format);</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  }</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  {</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keywordflow">return</span> _data_type;</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  }</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> }</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span> </div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00332"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb"> 332</a></span> <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">SimpleTensor<T>::num_channels</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> <span class="keyword"></span>{</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">switch</span>(_format)</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  {</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">Format::U8</a>:</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">Format::U16</a>:</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">Format::S16</a>:</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">Format::U32</a>:</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">Format::S32</a>:</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">Format::F16</a>:</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">Format::F32</a>:</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="comment">// Because the U and V channels are subsampled</span></div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="comment">// these formats appear like having only 2 channels:</span></div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a481e7a6945eb9f23e87f2de780b2e164">Format::YUYV422</a>:</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58af557448a61ad2927194f63442e131dfa">Format::UYVY422</a>:</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordflow">return</span> 2;</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a079eb95759d2ad31254f659d63651825">Format::UV88</a>:</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">return</span> 2;</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">Format::RGB888</a>:</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keywordflow">return</span> 3;</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a165f06116e7b8d9b2481dfc805db4619">Format::RGBA8888</a>:</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keywordflow">return</span> 4;</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">Format::UNKNOWN</a>:</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keywordflow">return</span> _num_channels;</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="comment">//Doesn't make sense for planar formats:</span></div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a202f5d8c2c70d31048154d8b8b28e755">Format::NV12</a>:</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a8e9f6aa1af7e0abbc7e64521e6ffe1b4">Format::NV21</a>:</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ab08f0cb36474118c5bbc03b3a172a778">Format::IYUV</a>:</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a11cfa56ee0ddbbc30a2fd189d7475f4c">Format::YUV444</a>:</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  }</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span> }</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span> </div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00368"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e"> 368</a></span> <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">SimpleTensor<T>::num_elements</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span> <span class="keyword"></span>{</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="keywordflow">return</span> _shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">total_size</a>();</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span> }</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> </div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00374"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a79e20eacb1e963e24a21ebd7369effd7"> 374</a></span> <a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a79e20eacb1e963e24a21ebd7369effd7">SimpleTensor<T>::padding</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> <span class="keyword"></span>{</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a4467b302fc9ec312c40580336ab783da">PaddingSize</a>(0);</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> }</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> </div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00380"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0"> 380</a></span> <span class="keyword">const</span> T *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">SimpleTensor<T>::data</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span> <span class="keyword"></span>{</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <span class="keywordflow">return</span> _buffer.get();</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> }</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span> </div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00386"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#adc1e16b293a89a9ccc9541058b5ca560"> 386</a></span> T *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">SimpleTensor<T>::data</a>()</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> {</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordflow">return</span> _buffer.get();</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span> }</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span> </div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00392"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f"> 392</a></span> <span class="keyword">const</span> <span class="keywordtype">void</span> *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">SimpleTensor<T>::operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &coord)<span class="keyword"> const</span></div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> <span class="keyword"></span>{</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="keywordflow">return</span> _buffer.get() + <a class="code" href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">coord2index</a>(_shape, coord) * _num_channels;</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span> }</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span> </div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00398"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a2df95f7046b81e69a1265a42202ea068"> 398</a></span> <span class="keywordtype">void</span> *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">SimpleTensor<T>::operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &coord)</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> {</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keywordflow">return</span> _buffer.get() + <a class="code" href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">coord2index</a>(_shape, coord) * _num_channels;</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> }</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span> </div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span> <span class="keyword">template</span> <<span class="keyword">typename</span> U></div><div class="line"><a name="l00404"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3"> 404</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<U></a> &tensor1, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<U></a> &tensor2)</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span> {</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  <span class="comment">// Use unqualified call to swap to enable ADL. But make std::swap available</span></div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="comment">// as backup.</span></div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keyword">using</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">std::swap</a>;</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._shape, tensor2._shape);</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._format, tensor2._format);</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._data_type, tensor2._data_type);</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._num_channels, tensor2._num_channels);</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._quantization_info, tensor2._quantization_info);</div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(tensor1._buffer, tensor2._buffer);</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> }</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span> } <span class="comment">// namespace test</span></div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> } <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> <span class="preprocessor">#endif </span><span class="comment">/* __ARM_COMPUTE_TEST_SIMPLE_TENSOR_H__ */</span><span class="preprocessor"></span></div><div class="ttc" id="_i_accessor_8h_xhtml"><div class="ttname"><a href="_i_accessor_8h.xhtml">IAccessor.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a51920d34b0fa5415e84891ad8e755224"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">arm_compute::test::SimpleTensor::swap</a></div><div class="ttdeci">friend void swap(SimpleTensor< U > &tensor1, SimpleTensor< U > &tensor2)</div><div class="ttdoc">Swaps the content of the provided tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00404">SimpleTensor.h:404</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a4498730adaf901d945c12841df994bba"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a4498730adaf901d945c12841df994bba">arm_compute::Dimensions::cbegin</a></div><div class="ttdeci">std::array< T, num_max_dimensions >::const_iterator cbegin() const </div><div class="ttdoc">Returns a read-only (constant) iterator that points to the first element in the dimension array...</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00189">Dimensions.h:189</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58af557448a61ad2927194f63442e131dfa"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58af557448a61ad2927194f63442e131dfa">arm_compute::Format::UYVY422</a></div><div class="ttdoc">A single plane of 32-bit macro pixel of U0, Y0, V0, Y1 byte. </div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a62b67b578f684c4d516843c9dea86a23"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">arm_compute::test::SimpleTensor::element_size</a></div><div class="ttdeci">size_t element_size() const override</div><div class="ttdoc">Size of each element in the tensor in bytes. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00288">SimpleTensor.h:288</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">arm_compute::test::RawTensor</a></div><div class="ttdoc">Subclass of SimpleTensor using uint8_t as value type. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8h_source.xhtml#l00038">RawTensor.h:38</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="_toolchain_support_8h_xhtml"><div class="ttname"><a href="_toolchain_support_8h.xhtml">ToolchainSupport.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ad7701a09a964eab360a8e51fa7ad2c16"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">arm_compute::test::SimpleTensor::size</a></div><div class="ttdeci">size_t size() const override</div><div class="ttdoc">Total size of the tensor in bytes. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00300">SimpleTensor.h:300</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_af6124c81d1e81f182d64ae76caa3fa52"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">arm_compute::test::SimpleTensor::operator[]</a></div><div class="ttdeci">T & operator[](size_t offset)</div><div class="ttdoc">Return value at offset in the buffer. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00270">SimpleTensor.h:270</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_border_size_xhtml"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml">arm_compute::BorderSize</a></div><div class="ttdoc">Container for 2D border size. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00289">Types.h:289</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="namespacearm__compute_xhtml_a34b06c0cd94808a77b697e79880b84b0"><div class="ttname"><a href="namespacearm__compute.xhtml#a34b06c0cd94808a77b697e79880b84b0">arm_compute::element_size_from_data_type</a></div><div class="ttdeci">size_t element_size_from_data_type(DataType dt)</div><div class="ttdoc">The size in bytes of the data type. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00179">Utils.h:179</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ac4b36cc1e56b0b7e579bb4b7196490db"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">arm_compute::test::SimpleTensor::format</a></div><div class="ttdeci">Format format() const override</div><div class="ttdoc">Image format of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00307">SimpleTensor.h:307</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_1test_1_1_simple_tensor_xhtml_a9a3e72153aeb3ed212e9c3698774e881"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">arm_compute::test::SimpleTensor::data_type</a></div><div class="ttdeci">DataType data_type() const override</div><div class="ttdoc">Data type of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00319">SimpleTensor.h:319</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a202f5d8c2c70d31048154d8b8b28e755"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a202f5d8c2c70d31048154d8b8b28e755">arm_compute::Format::NV12</a></div><div class="ttdoc">A 2 plane YUV format of Luma (Y) and interleaved UV data at 4:2:0 sampling. </div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a28edc8880596d14c099f3c2509efc8b3"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">arm_compute::test::swap</a></div><div class="ttdeci">void swap(SimpleTensor< U > &tensor1, SimpleTensor< U > &tensor2)</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00404">SimpleTensor.h:404</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::Format::U16</a></div><div class="ttdoc">1 channel, 1 U16 per channel </div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_aba5871b3e4a65d057ec1c28fce8b00ba"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">arm_compute::test::SimpleTensor::shape</a></div><div class="ttdeci">TensorShape shape() const override</div><div class="ttdoc">Shape of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00282">SimpleTensor.h:282</a></div></div> |
| <div class="ttc" id="helpers_8h_xhtml_a009469e4d9b8fce3b6d5e97d2077827d"><div class="ttname"><a href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a></div><div class="ttdeci">__global uchar * offset(const Image *img, int x, int y)</div><div class="ttdoc">Get the pointer position of a Image. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00311">helpers.h:311</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a8e9f6aa1af7e0abbc7e64521e6ffe1b4"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a8e9f6aa1af7e0abbc7e64521e6ffe1b4">arm_compute::Format::NV21</a></div><div class="ttdoc">A 2 plane YUV format of Luma (Y) and interleaved VU data at 4:2:0 sampling. </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">This file contains all available output stages for GEMMLowp on OpenCL. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00001">00_introduction.dox:1</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a9be4cb7e6ee20063a4a10bc3abb750b9"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">arm_compute::test::coord2index</a></div><div class="ttdeci">int coord2index(const TensorShape &shape, const Coordinates &coord)</div><div class="ttdoc">Linearise the given coordinate. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00477">Utils.h:477</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="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 S32 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">arm_compute::Format::RGB888</a></div><div class="ttdoc">3 channels, 1 U8 per channel </div></div> |
| <div class="ttc" id="arm__compute_2core_2_utils_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_utils_8h.xhtml">Utils.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_adf9b6d55d708c285d58511a780e937fc"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#adf9b6d55d708c285d58511a780e937fc">arm_compute::Dimensions::cend</a></div><div class="ttdeci">std::array< T, num_max_dimensions >::const_iterator cend() const </div><div class="ttdoc">Returns a read-only (constant) iterator that points one past the last element in the dimension array...</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00213">Dimensions.h:213</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a0c52a8f0085b55d907af7210ef2069d0"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a0c52a8f0085b55d907af7210ef2069d0">arm_compute::test::SimpleTensor::data</a></div><div class="ttdeci">const T * data() const </div><div class="ttdoc">Constant pointer to the underlying buffer. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00380">SimpleTensor.h:380</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_ab4e88c89b3b7ea1735996cc4def22d58"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">arm_compute::Format</a></div><div class="ttdeci">Format</div><div class="ttdoc">Image colour formats. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00050">Types.h:50</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a16d7ecd97f89cf9dc40b3fc7c9abe2cd"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a16d7ecd97f89cf9dc40b3fc7c9abe2cd">arm_compute::test::SimpleTensor::~SimpleTensor</a></div><div class="ttdeci">~SimpleTensor()=default</div><div class="ttdoc">Default destructor. </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="classarm__compute_1_1test_1_1_simple_tensor_xhtml_afb9ded5f49336ae503bb9f2035ea902b"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#afb9ded5f49336ae503bb9f2035ea902b">arm_compute::test::SimpleTensor< uint8_t >::value_type</a></div><div class="ttdeci">uint8_t value_type</div><div class="ttdoc">Tensor value type. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00104">SimpleTensor.h:104</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a11cfa56ee0ddbbc30a2fd189d7475f4c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a11cfa56ee0ddbbc30a2fd189d7475f4c">arm_compute::Format::YUV444</a></div><div class="ttdoc">A 3 plane of 8 bit 4:4:4 sampled Y, U, V planes. </div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a79e20eacb1e963e24a21ebd7369effd7"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a79e20eacb1e963e24a21ebd7369effd7">arm_compute::test::SimpleTensor::padding</a></div><div class="ttdeci">PaddingSize padding() const override</div><div class="ttdoc">Available padding around the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00374">SimpleTensor.h:374</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a5f63b63606dbbbe54474e6e970a6738c"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">arm_compute::test::SimpleTensor::data_layout</a></div><div class="ttdeci">DataLayout data_layout() const override</div><div class="ttdoc">Data layout of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00313">SimpleTensor.h:313</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a4467b302fc9ec312c40580336ab783da"><div class="ttname"><a href="namespacearm__compute.xhtml#a4467b302fc9ec312c40580336ab783da">arm_compute::PaddingSize</a></div><div class="ttdeci">BorderSize PaddingSize</div><div class="ttdoc">Container for 2D padding size. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00376">Types.h:376</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::Format::S16</a></div><div class="ttdoc">1 channel, 1 S16 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</a></div><div class="ttdoc">Num samples, channels, height, width. </div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a011bb65bd16aaf66b8efb3929692b2ce"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">arm_compute::test::SimpleTensor::SimpleTensor</a></div><div class="ttdeci">SimpleTensor()=default</div><div class="ttdoc">Create an uninitialised tensor. </div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a39537b09ccc3ce3d17922f4ef49a123f"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">arm_compute::test::SimpleTensor::operator()</a></div><div class="ttdeci">const void * operator()(const Coordinates &coord) const override</div><div class="ttdoc">Read only access to the specified element. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00392">SimpleTensor.h:392</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a59846ef5ca75cd81cdb7e8a1ce08f9db"><div class="ttname"><a href="namespacearm__compute.xhtml#a59846ef5ca75cd81cdb7e8a1ce08f9db">arm_compute::data_type_from_format</a></div><div class="ttdeci">DataType data_type_from_format(Format format)</div><div class="ttdoc">Return the data type used by a given single-planar pixel format. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00207">Utils.h:207</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_acf18a24d1f21176e811e88cee2a70f1f"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f">arm_compute::test::SimpleTensor< uint8_t >::Buffer</a></div><div class="ttdeci">std::unique_ptr< value_type[]> Buffer</div><div class="ttdoc">Tensor buffer pointer type. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00106">SimpleTensor.h:106</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ab08f0cb36474118c5bbc03b3a172a778"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ab08f0cb36474118c5bbc03b3a172a778">arm_compute::Format::IYUV</a></div><div class="ttdoc">A 3 plane of 8-bit 4:2:0 sampled Y, U, V planes. </div></div> |
| <div class="ttc" id="tests_2_utils_8h_xhtml"><div class="ttname"><a href="tests_2_utils_8h.xhtml">Utils.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</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="classarm__compute_1_1test_1_1_simple_tensor_xhtml_abdd3637f2bbde9d7d0cc0b7bbd8400bb"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">arm_compute::test::SimpleTensor::num_channels</a></div><div class="ttdeci">int num_channels() const override</div><div class="ttdoc">Number of channels of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00332">SimpleTensor.h:332</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a165f06116e7b8d9b2481dfc805db4619"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a165f06116e7b8d9b2481dfc805db4619">arm_compute::Format::RGBA8888</a></div><div class="ttdoc">4 channels, 1 U8 per channel </div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ad4622eda610d53fb6852209f0213aeed"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad4622eda610d53fb6852209f0213aeed">arm_compute::test::SimpleTensor::operator=</a></div><div class="ttdeci">SimpleTensor & operator=(SimpleTensor tensor)</div><div class="ttdoc">Create a deep copy of the given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00262">SimpleTensor.h:262</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3"><div class="ttname"><a href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">arm_compute::CLVersion::UNKNOWN</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_i_accessor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_i_accessor.xhtml">arm_compute::test::IAccessor</a></div><div class="ttdoc">Common interface to provide information and access to tensor like structures. </div><div class="ttdef"><b>Definition:</b> <a href="_i_accessor_8h_source.xhtml#l00037">IAccessor.h:37</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a079eb95759d2ad31254f659d63651825"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a079eb95759d2ad31254f659d63651825">arm_compute::Format::UV88</a></div><div class="ttdoc">2 channel, 1 U8 per channel </div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_aedcfdd4c3b92fe0d63b5463c7ad1d21e"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">arm_compute::test::SimpleTensor::num_elements</a></div><div class="ttdeci">int num_elements() const override</div><div class="ttdoc">Number of elements of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00368">SimpleTensor.h:368</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_a4eaec01ba2c12093db609d1034ad0bc1"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">arm_compute::TensorShape::total_size</a></div><div class="ttdeci">size_t total_size() const </div><div class="ttdoc">Collapses all dimensions to a single linear total size. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00171">TensorShape.h:171</a></div></div> |
| <div class="ttc" id="accumulate_8cl_xhtml_a00e540076dd545ad59ac7482f8cdf514"><div class="ttname"><a href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">accumulate</a></div><div class="ttdeci">__kernel void accumulate(__global uchar *input_ptr, uint input_stride_x, uint input_step_x, uint input_stride_y, uint input_step_y, uint input_offset_first_element_in_bytes, __global uchar *accu_ptr, uint accu_stride_x, uint accu_step_x, uint accu_stride_y, uint accu_step_y, uint accu_offset_first_element_in_bytes)</div><div class="ttdoc">This function accumulates an input image into output image. </div><div class="ttdef"><b>Definition:</b> <a href="accumulate_8cl_source.xhtml#l00041">accumulate.cl:41</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_quantization_info_xhtml"><div class="ttname"><a href="structarm__compute_1_1_quantization_info.xhtml">arm_compute::QuantizationInfo</a></div><div class="ttdoc">Quantization settings (used for QASYMM8 data type) </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00124">Types.h:124</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ac74736e3863207232a23b7181c1d0f44"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">arm_compute::test::SimpleTensor::quantization_info</a></div><div class="ttdeci">QuantizationInfo quantization_info() const override</div><div class="ttdoc">Quantization info in case of asymmetric quantized type. </div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00294">SimpleTensor.h:294</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a481e7a6945eb9f23e87f2de780b2e164"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a481e7a6945eb9f23e87f2de780b2e164">arm_compute::Format::YUYV422</a></div><div class="ttdoc">A single plane of 32-bit macro pixel of Y0, U0, Y1, V0 bytes. </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="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#l00072">Types.h:72</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdoc">Supported tensor data layouts. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00107">Types.h:107</a></div></div> |
| <div class="ttc" id="_tensor_shape_8h_xhtml"><div class="ttname"><a href="_tensor_shape_8h.xhtml">TensorShape.h</a></div></div> |
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