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<div id="projectname">ARM Compute Library
-  <span id="projectnumber">17.03.1</span>
+  <span id="projectnumber">17.04</span>
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<div class="title">TensorInfo.h</div> </div>
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<div class="contents">
-<a href="_tensor_info_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) 2016, 2017 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_TENSORINFO_H__</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define __ARM_COMPUTE_TENSORINFO_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="_coordinates_8h.xhtml">arm_compute/core/Coordinates.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_strides_8h.xhtml">arm_compute/core/Strides.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</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="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_types_8h.xhtml">arm_compute/core/Types.h</a>"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</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="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include <cstddef></span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="keyword">class </span>HOGInfo;</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml"> 40</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>();</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keyword">virtual</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a39cbe92494f53364366a6cddde0b5741">~TensorInfo</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#adcf156ba30ff118c28690671e83ea06b">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &&) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#adcf156ba30ff118c28690671e83ea06b">operator=</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &&) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0c875a3203d902e2ad6bc3045355e69e">format</a>);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#af3374fa8fcc6d226dc2b82317ab4d079">tensor_shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a330472af42b92ad18b93c06d5b510faa">num_channels</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a45cc7b9a37aa9f0e7d479248a27e1f58">data_type</a>, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">fixed_point_pos</a> = 0);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &hog_info, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0ae7d318c02e56a3daa9e5e4f9dab117">init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0ae7d318c02e56a3daa9e5e4f9dab117">init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a6b157a0e1ca25ef4d682d3bedfeae5f6">strides_in_bytes</a>, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad590b0e52b0574c9c2fce393ede1fa7a">offset_first_element_in_bytes</a>, <span class="keywordtype">size_t</span> total_size_in_bytes);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0ae7d318c02e56a3daa9e5e4f9dab117">init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <span class="keywordtype">size_t</span> num_channels, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> data_type, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">fixed_point_pos</a> = 0);</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0ae7d318c02e56a3daa9e5e4f9dab117">init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <span class="keywordtype">size_t</span> num_channels, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> data_type, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> &strides_in_bytes, <span class="keywordtype">size_t</span> offset_first_element_in_bytes,</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keywordtype">size_t</span> total_size_in_bytes, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">fixed_point_pos</a> = 0);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0ae7d318c02e56a3daa9e5e4f9dab117">init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &hog_info, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a4b7391b7025befbe44b743723feb4a9b">init_auto_padding</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format);</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a4b7391b7025befbe44b743723feb4a9b">init_auto_padding</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <span class="keywordtype">size_t</span> num_channels, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> data_type, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">fixed_point_pos</a> = 0);</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a4b7391b7025befbe44b743723feb4a9b">init_auto_padding</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &hog_info, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac7af0020334c69f249f5a2e267a5c4f4">auto_padding</a>();</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a8d37b60af520149481b2c7bbe1d829fd">extend_padding</a>(<span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> &padding);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a1f4481a2c496ef1d176f305c25f50202">set_format</a>(<a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format);</div><div class="line"><a name="l00190"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a6c223d48dcc4afd27b6f3932182622b6"> 190</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a6c223d48dcc4afd27b6f3932182622b6">dimension</a>(<span class="keywordtype">size_t</span> index)<span class="keyword"> const</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordflow">return</span> _tensor_shape[index];</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  }</div><div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a6b157a0e1ca25ef4d682d3bedfeae5f6"> 198</a></span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a6b157a0e1ca25ef4d682d3bedfeae5f6">strides_in_bytes</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keywordflow">return</span> _strides_in_bytes;</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  }</div><div class="line"><a name="l00207"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#ad590b0e52b0574c9c2fce393ede1fa7a"> 207</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad590b0e52b0574c9c2fce393ede1fa7a">offset_first_element_in_bytes</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordflow">return</span> _offset_first_element_in_bytes;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  }</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aaf5cc084e0feafccc97492d688f4e2e2">offset_element_in_bytes</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &pos) <span class="keyword">const</span>;</div><div class="line"><a name="l00223"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d"> 223</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">fixed_point_pos</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordflow">return</span> _fixed_point_pos;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  }</div><div class="line"><a name="l00231"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a448f57f9d6aec61b3d85b898affe4a2e"> 231</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a448f57f9d6aec61b3d85b898affe4a2e">element_size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#abb7e0f23a4f2e63f39433f158dad47ab">data_size_from_type</a>(_data_type) * _num_channels;</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  }</div><div class="line"><a name="l00239"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a38382dc1f04d28cab04d921b8324dc07"> 239</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a38382dc1f04d28cab04d921b8324dc07">num_dimensions</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keywordflow">return</span> _tensor_shape.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a0f59f175e7682c7ed5f4ea30ef687834">num_dimensions</a>();</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  }</div><div class="line"><a name="l00247"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a330472af42b92ad18b93c06d5b510faa"> 247</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a330472af42b92ad18b93c06d5b510faa">num_channels</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordflow">return</span> _num_channels;</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  }</div><div class="line"><a name="l00255"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#af3374fa8fcc6d226dc2b82317ab4d079"> 255</a></span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#af3374fa8fcc6d226dc2b82317ab4d079">tensor_shape</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keywordflow">return</span> _tensor_shape;</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  }</div><div class="line"><a name="l00263"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a45cc7b9a37aa9f0e7d479248a27e1f58"> 263</a></span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a45cc7b9a37aa9f0e7d479248a27e1f58">data_type</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keywordflow">return</span> _data_type;</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  }</div><div class="line"><a name="l00271"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a0c875a3203d902e2ad6bc3045355e69e"> 271</a></span>  <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0c875a3203d902e2ad6bc3045355e69e">format</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="keywordflow">return</span> _format;</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  }</div><div class="line"><a name="l00279"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a4eaec01ba2c12093db609d1034ad0bc1"> 279</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">total_size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keywordflow">return</span> _total_size;</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  }</div><div class="line"><a name="l00287"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a8e26c00bed00782a17b87f8afa5c96ab"> 287</a></span>  <span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a8e26c00bed00782a17b87f8afa5c96ab">has_padding</a>()</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  {</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keywordflow">return</span> (this-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">total_size</a>() != (this-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#af3374fa8fcc6d226dc2b82317ab4d079">tensor_shape</a>().<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">total_size</a>() * this-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a448f57f9d6aec61b3d85b898affe4a2e">element_size</a>()));</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  }</div><div class="line"><a name="l00295"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a61fd20903a4b595b3d33bc443d23957e"> 295</a></span>  <span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a61fd20903a4b595b3d33bc443d23957e">is_resizable</a>()</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  {</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keywordflow">return</span> _is_resizable;</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  }</div><div class="line"><a name="l00300"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a951c1a7a29e99b39d59ee44111291c76"> 300</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a951c1a7a29e99b39d59ee44111291c76">set_is_resizable</a>(<span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a61fd20903a4b595b3d33bc443d23957e">is_resizable</a>)</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  {</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  _is_resizable = <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a61fd20903a4b595b3d33bc443d23957e">is_resizable</a>;</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  }</div><div class="line"><a name="l00308"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#ac437ef0718add962a4059fb3b3084c34"> 308</a></span>  <a class="code" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac437ef0718add962a4059fb3b3084c34">valid_region</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordflow">return</span> _valid_region;</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  }</div><div class="line"><a name="l00313"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a6922a99119f324abe0e16c9678f71922"> 313</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a6922a99119f324abe0e16c9678f71922">set_valid_region</a>(<a class="code" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac437ef0718add962a4059fb3b3084c34">valid_region</a>)</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  {</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  _valid_region = std::move(valid_region);</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">private</span>:</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  std::tuple<Strides, size_t, size_t> calculate_padding_requirements(<span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> &padding);</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="keywordtype">size_t</span> _total_size;</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keywordtype">size_t</span> _fixed_point_pos;</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keywordtype">size_t</span> _offset_first_element_in_bytes;</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> _strides_in_bytes;</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordtype">size_t</span> _num_channels;</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> _tensor_shape;</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> _data_type;</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> _format;</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordtype">bool</span> _is_resizable;</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <a class="code" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a> _valid_region;</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> }</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> <span class="preprocessor">#endif </span><span class="comment">/*__ARM_COMPUTE_TENSORINFO_H__ */</span><span class="preprocessor"></span></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#l00038">TensorShape.h:38</a></div></div>
+<a href="_tensor_info_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) 2016, 2017 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_TENSORINFO_H__</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define __ARM_COMPUTE_TENSORINFO_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="_coordinates_8h.xhtml">arm_compute/core/Coordinates.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_strides_8h.xhtml">arm_compute/core/Strides.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</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="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_types_8h.xhtml">arm_compute/core/Types.h</a>"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</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="l00032"></a><span class="lineno"> 32</span> </div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include <cstddef></span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> {</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="keyword">class </span>HOGInfo;</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml"> 40</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="keyword">public</span>:</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>();</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keyword">virtual</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a39cbe92494f53364366a6cddde0b5741">~TensorInfo</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#adcf156ba30ff118c28690671e83ea06b">operator=</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &&) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#adcf156ba30ff118c28690671e83ea06b">operator=</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> &&) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0c875a3203d902e2ad6bc3045355e69e">format</a>);</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#af3374fa8fcc6d226dc2b82317ab4d079">tensor_shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format);</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a330472af42b92ad18b93c06d5b510faa">num_channels</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a45cc7b9a37aa9f0e7d479248a27e1f58">data_type</a>, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">fixed_point_pos</a> = 0);</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">TensorInfo</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &hog_info, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0ae7d318c02e56a3daa9e5e4f9dab117">init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0ae7d318c02e56a3daa9e5e4f9dab117">init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a6b157a0e1ca25ef4d682d3bedfeae5f6">strides_in_bytes</a>, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad590b0e52b0574c9c2fce393ede1fa7a">offset_first_element_in_bytes</a>, <span class="keywordtype">size_t</span> total_size_in_bytes);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0ae7d318c02e56a3daa9e5e4f9dab117">init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <span class="keywordtype">size_t</span> num_channels, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> data_type, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">fixed_point_pos</a> = 0);</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0ae7d318c02e56a3daa9e5e4f9dab117">init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <span class="keywordtype">size_t</span> num_channels, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> data_type, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> &strides_in_bytes, <span class="keywordtype">size_t</span> offset_first_element_in_bytes,</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <span class="keywordtype">size_t</span> total_size_in_bytes, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">fixed_point_pos</a> = 0);</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0ae7d318c02e56a3daa9e5e4f9dab117">init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &hog_info, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height);</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a4b7391b7025befbe44b743723feb4a9b">init_auto_padding</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format);</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a4b7391b7025befbe44b743723feb4a9b">init_auto_padding</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &tensor_shape, <span class="keywordtype">size_t</span> num_channels, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> data_type, <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">fixed_point_pos</a> = 0);</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a4b7391b7025befbe44b743723feb4a9b">init_auto_padding</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_h_o_g_info.xhtml">HOGInfo</a> &hog_info, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height);</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac7af0020334c69f249f5a2e267a5c4f4">auto_padding</a>();</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a8d37b60af520149481b2c7bbe1d829fd">extend_padding</a>(<span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad13a67d4dbc337c707a76401dc103ff3">padding</a>);</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a1f4481a2c496ef1d176f305c25f50202">set_format</a>(<a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format);</div><div class="line"><a name="l00190"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a6c223d48dcc4afd27b6f3932182622b6"> 190</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a6c223d48dcc4afd27b6f3932182622b6">dimension</a>(<span class="keywordtype">size_t</span> index)<span class="keyword"> const</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordflow">return</span> _tensor_shape[index];</div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  }</div><div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a6b157a0e1ca25ef4d682d3bedfeae5f6"> 198</a></span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a6b157a0e1ca25ef4d682d3bedfeae5f6">strides_in_bytes</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="keywordflow">return</span> _strides_in_bytes;</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  }</div><div class="line"><a name="l00207"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#ad590b0e52b0574c9c2fce393ede1fa7a"> 207</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad590b0e52b0574c9c2fce393ede1fa7a">offset_first_element_in_bytes</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keywordflow">return</span> _offset_first_element_in_bytes;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  }</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aaf5cc084e0feafccc97492d688f4e2e2">offset_element_in_bytes</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &pos) <span class="keyword">const</span>;</div><div class="line"><a name="l00223"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d"> 223</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">fixed_point_pos</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordflow">return</span> _fixed_point_pos;</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  }</div><div class="line"><a name="l00231"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a448f57f9d6aec61b3d85b898affe4a2e"> 231</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a448f57f9d6aec61b3d85b898affe4a2e">element_size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#abb7e0f23a4f2e63f39433f158dad47ab">data_size_from_type</a>(_data_type) * _num_channels;</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  }</div><div class="line"><a name="l00239"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a38382dc1f04d28cab04d921b8324dc07"> 239</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a38382dc1f04d28cab04d921b8324dc07">num_dimensions</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="keywordflow">return</span> _tensor_shape.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a0f59f175e7682c7ed5f4ea30ef687834">num_dimensions</a>();</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  }</div><div class="line"><a name="l00247"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a330472af42b92ad18b93c06d5b510faa"> 247</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a330472af42b92ad18b93c06d5b510faa">num_channels</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keywordflow">return</span> _num_channels;</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  }</div><div class="line"><a name="l00255"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#af3374fa8fcc6d226dc2b82317ab4d079"> 255</a></span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#af3374fa8fcc6d226dc2b82317ab4d079">tensor_shape</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="keywordflow">return</span> _tensor_shape;</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  }</div><div class="line"><a name="l00263"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a45cc7b9a37aa9f0e7d479248a27e1f58"> 263</a></span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a45cc7b9a37aa9f0e7d479248a27e1f58">data_type</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <span class="keywordflow">return</span> _data_type;</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  }</div><div class="line"><a name="l00271"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a0c875a3203d902e2ad6bc3045355e69e"> 271</a></span>  <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0c875a3203d902e2ad6bc3045355e69e">format</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="keywordflow">return</span> _format;</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  }</div><div class="line"><a name="l00279"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a4eaec01ba2c12093db609d1034ad0bc1"> 279</a></span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">total_size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keywordflow">return</span> _total_size;</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  }</div><div class="line"><a name="l00287"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#ad13a67d4dbc337c707a76401dc103ff3"> 287</a></span>  <a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ad13a67d4dbc337c707a76401dc103ff3">padding</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keywordflow">return</span> _padding;</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  }</div><div class="line"><a name="l00295"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a9f7c904411f0871ed5b37eecb1c03de2"> 295</a></span>  <span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a9f7c904411f0871ed5b37eecb1c03de2">has_padding</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keywordflow">return</span> !_padding.<a class="code" href="structarm__compute_1_1_border_size.xhtml#adffbf97e7b8b64e7cf32f0254cddf3c4">empty</a>();</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  }</div><div class="line"><a name="l00303"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#aa29d70e3b3c82e0857a6be5280b70ee0"> 303</a></span>  <span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aa29d70e3b3c82e0857a6be5280b70ee0">is_resizable</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">return</span> _is_resizable;</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  }</div><div class="line"><a name="l00308"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a951c1a7a29e99b39d59ee44111291c76"> 308</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a951c1a7a29e99b39d59ee44111291c76">set_is_resizable</a>(<span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aa29d70e3b3c82e0857a6be5280b70ee0">is_resizable</a>)</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  {</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  _is_resizable = <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#aa29d70e3b3c82e0857a6be5280b70ee0">is_resizable</a>;</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  }</div><div class="line"><a name="l00316"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#ac437ef0718add962a4059fb3b3084c34"> 316</a></span>  <a class="code" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac437ef0718add962a4059fb3b3084c34">valid_region</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> <span class="keyword"> </span>{</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="keywordflow">return</span> _valid_region;</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  }</div><div class="line"><a name="l00321"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_tensor_info.xhtml#a6922a99119f324abe0e16c9678f71922"> 321</a></span>  <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a6922a99119f324abe0e16c9678f71922">set_valid_region</a>(<a class="code" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a> <a class="code" href="classarm__compute_1_1_tensor_info.xhtml#ac437ef0718add962a4059fb3b3084c34">valid_region</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>  _valid_region = std::move(valid_region);</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> </div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span> <span class="keyword">private</span>:</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  std::tuple<Strides, size_t, size_t> calculate_padding_requirements(<span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> &padding);</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> </div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordtype">size_t</span> _total_size;</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordtype">size_t</span> _fixed_point_pos;</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordtype">size_t</span> _offset_first_element_in_bytes;</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> _strides_in_bytes;</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="keywordtype">size_t</span> _num_channels;</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> _tensor_shape;</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> _data_type;</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> _format;</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keywordtype">bool</span> _is_resizable;</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <a class="code" href="structarm__compute_1_1_valid_region.xhtml">ValidRegion</a> _valid_region;</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> _padding;</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span> };</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> }</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span> <span class="preprocessor">#endif </span><span class="comment">/*__ARM_COMPUTE_TENSORINFO_H__ */</span><span class="preprocessor"></span></div><div class="ttc" id="structarm__compute_1_1_border_size_xhtml_adffbf97e7b8b64e7cf32f0254cddf3c4"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml#adffbf97e7b8b64e7cf32f0254cddf3c4">arm_compute::BorderSize::empty</a></div><div class="ttdeci">constexpr bool empty() const </div><div class="ttdoc">Check if the entire border is zero. </div><div class="ttdef"><b>Definition:</b> <a href="_types_8h_source.xhtml#l00143">Types.h:143</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#l00038">TensorShape.h:38</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a4b7391b7025befbe44b743723feb4a9b"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a4b7391b7025befbe44b743723feb4a9b">arm_compute::TensorInfo::init_auto_padding</a></div><div class="ttdeci">size_t init_auto_padding(const TensorShape &tensor_shape, Format format)</div><div class="ttdoc">Initialize the metadata structure for the given tensor shape and single-plane format, (Padding is automatically calculated) </div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a45cc7b9a37aa9f0e7d479248a27e1f58"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a45cc7b9a37aa9f0e7d479248a27e1f58">arm_compute::TensorInfo::data_type</a></div><div class="ttdeci">DataType data_type() const </div><div class="ttdoc">Data type used for each element of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00263">TensorInfo.h:263</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_ac7af0020334c69f249f5a2e267a5c4f4"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#ac7af0020334c69f249f5a2e267a5c4f4">arm_compute::TensorInfo::auto_padding</a></div><div class="ttdeci">bool auto_padding()</div><div class="ttdoc">Update the offset to the first element and the strides to automatically computed values. </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="_types_8h_source.xhtml#l00116">Types.h:116</a></div></div>
<div class="ttc" id="_types_8h_xhtml"><div class="ttname"><a href="_types_8h.xhtml">Types.h</a></div></div>
-<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a951c1a7a29e99b39d59ee44111291c76"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a951c1a7a29e99b39d59ee44111291c76">arm_compute::TensorInfo::set_is_resizable</a></div><div class="ttdeci">void set_is_resizable(bool is_resizable)</div><div class="ttdoc">Set the flag whether the tensor size can be changed. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00300">TensorInfo.h:300</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a951c1a7a29e99b39d59ee44111291c76"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a951c1a7a29e99b39d59ee44111291c76">arm_compute::TensorInfo::set_is_resizable</a></div><div class="ttdeci">void set_is_resizable(bool is_resizable)</div><div class="ttdoc">Set the flag whether the tensor size can be changed. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00308">TensorInfo.h:308</a></div></div>
<div class="ttc" id="classarm__compute_1_1_h_o_g_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_h_o_g_info.xhtml">arm_compute::HOGInfo</a></div><div class="ttdoc">Store the HOG&#39;s metadata. </div><div class="ttdef"><b>Definition:</b> <a href="_h_o_g_info_8h_source.xhtml#l00035">HOGInfo.h:35</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a448f57f9d6aec61b3d85b898affe4a2e"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a448f57f9d6aec61b3d85b898affe4a2e">arm_compute::TensorInfo::element_size</a></div><div class="ttdeci">size_t element_size() const </div><div class="ttdoc">Element size in bytes calculated as data_size() * num_channels. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00231">TensorInfo.h:231</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_aaf5cc084e0feafccc97492d688f4e2e2"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#aaf5cc084e0feafccc97492d688f4e2e2">arm_compute::TensorInfo::offset_element_in_bytes</a></div><div class="ttdeci">size_t offset_element_in_bytes(const Coordinates &pos) const </div><div class="ttdoc">The offset in bytes from the beginning of the memory allocation to access the element at position (x...</div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_af3374fa8fcc6d226dc2b82317ab4d079"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#af3374fa8fcc6d226dc2b82317ab4d079">arm_compute::TensorInfo::tensor_shape</a></div><div class="ttdeci">const TensorShape & tensor_shape() const </div><div class="ttdoc">Size for each dimension of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00255">TensorInfo.h:255</a></div></div>
<div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item. </div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_abb7e0f23a4f2e63f39433f158dad47ab"><div class="ttname"><a href="namespacearm__compute.xhtml#abb7e0f23a4f2e63f39433f158dad47ab">arm_compute::data_size_from_type</a></div><div class="ttdeci">size_t data_size_from_type(DataType data_type)</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#l00098">Utils.h:98</a></div></div>
-<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a6922a99119f324abe0e16c9678f71922"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a6922a99119f324abe0e16c9678f71922">arm_compute::TensorInfo::set_valid_region</a></div><div class="ttdeci">void set_valid_region(ValidRegion valid_region)</div><div class="ttdoc">Set the valid region of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00313">TensorInfo.h:313</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a6922a99119f324abe0e16c9678f71922"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a6922a99119f324abe0e16c9678f71922">arm_compute::TensorInfo::set_valid_region</a></div><div class="ttdeci">void set_valid_region(ValidRegion valid_region)</div><div class="ttdoc">Set the valid region of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00321">TensorInfo.h:321</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a4eaec01ba2c12093db609d1034ad0bc1"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a4eaec01ba2c12093db609d1034ad0bc1">arm_compute::TensorInfo::total_size</a></div><div class="ttdeci">size_t total_size() const </div><div class="ttdoc">Returns the total size of the tensor in bytes. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00279">TensorInfo.h:279</a></div></div>
<div class="ttc" id="classarm__compute_1_1_strides_xhtml"><div class="ttname"><a href="classarm__compute_1_1_strides.xhtml">arm_compute::Strides</a></div><div class="ttdoc">Strides of an item in bytes. </div><div class="ttdef"><b>Definition:</b> <a href="_strides_8h_source.xhtml#l00038">Strides.h:38</a></div></div>
<div class="ttc" id="_strides_8h_xhtml"><div class="ttname"><a href="_strides_8h.xhtml">Strides.h</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_aa29d70e3b3c82e0857a6be5280b70ee0"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#aa29d70e3b3c82e0857a6be5280b70ee0">arm_compute::TensorInfo::is_resizable</a></div><div class="ttdeci">bool is_resizable() const </div><div class="ttdoc">Flag indicating whether the size of the tensor can be changed. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00303">TensorInfo.h:303</a></div></div>
<div class="ttc" id="_coordinates_8h_xhtml"><div class="ttname"><a href="_coordinates_8h.xhtml">Coordinates.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a1f4481a2c496ef1d176f305c25f50202"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a1f4481a2c496ef1d176f305c25f50202">arm_compute::TensorInfo::set_format</a></div><div class="ttdeci">void set_format(Format format)</div><div class="ttdoc">Set the format of an already initialized tensor. </div></div>
-<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_ac437ef0718add962a4059fb3b3084c34"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#ac437ef0718add962a4059fb3b3084c34">arm_compute::TensorInfo::valid_region</a></div><div class="ttdeci">ValidRegion valid_region() const </div><div class="ttdoc">Valid region of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00308">TensorInfo.h:308</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_ac437ef0718add962a4059fb3b3084c34"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#ac437ef0718add962a4059fb3b3084c34">arm_compute::TensorInfo::valid_region</a></div><div class="ttdeci">ValidRegion valid_region() const </div><div class="ttdoc">Valid region of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00316">TensorInfo.h:316</a></div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a0f59f175e7682c7ed5f4ea30ef687834"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a0f59f175e7682c7ed5f4ea30ef687834">arm_compute::Dimensions::num_dimensions</a></div><div class="ttdeci">unsigned int num_dimensions() const </div><div class="ttdoc">Returns the effective dimensionality of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00108">Dimensions.h:108</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a8d37b60af520149481b2c7bbe1d829fd"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a8d37b60af520149481b2c7bbe1d829fd">arm_compute::TensorInfo::extend_padding</a></div><div class="ttdeci">bool extend_padding(const PaddingSize &padding)</div><div class="ttdoc">Update the offset to the first element, the strides and the total size. </div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_ad590b0e52b0574c9c2fce393ede1fa7a"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#ad590b0e52b0574c9c2fce393ede1fa7a">arm_compute::TensorInfo::offset_first_element_in_bytes</a></div><div class="ttdeci">size_t offset_first_element_in_bytes() const </div><div class="ttdoc">The offset from the beginning of the memory allocation to the first element of the tensor...</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00207">TensorInfo.h:207</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a9f7c904411f0871ed5b37eecb1c03de2"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a9f7c904411f0871ed5b37eecb1c03de2">arm_compute::TensorInfo::has_padding</a></div><div class="ttdeci">bool has_padding() const </div><div class="ttdoc">Checks if the tensor has been allocated with padding or not. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00295">TensorInfo.h:295</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a0c875a3203d902e2ad6bc3045355e69e"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a0c875a3203d902e2ad6bc3045355e69e">arm_compute::TensorInfo::format</a></div><div class="ttdeci">Format format() const </div><div class="ttdoc">Colour format of the image. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00271">TensorInfo.h:271</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&#39;s metadata. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00040">TensorInfo.h:40</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a21c2ae9fa438faf42669dadda628080c"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a21c2ae9fa438faf42669dadda628080c">arm_compute::TensorInfo::TensorInfo</a></div><div class="ttdeci">TensorInfo()</div><div class="ttdoc">Default constructor. </div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a6b157a0e1ca25ef4d682d3bedfeae5f6"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a6b157a0e1ca25ef4d682d3bedfeae5f6">arm_compute::TensorInfo::strides_in_bytes</a></div><div class="ttdeci">const Strides & strides_in_bytes() const </div><div class="ttdoc">The strides in bytes for accessing each dimension of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00198">TensorInfo.h:198</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="_types_8h_source.xhtml#l00059">Types.h:59</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_aac568c9183b365ddb66417b54ab8bf3d"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#aac568c9183b365ddb66417b54ab8bf3d">arm_compute::TensorInfo::fixed_point_pos</a></div><div class="ttdeci">size_t fixed_point_pos() const </div><div class="ttdoc">Fixed point position used when the tensor data type is S8, S16 or S32. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00223">TensorInfo.h:223</a></div></div>
-<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a
8e26c00bed00782a17b87f8afa5c96ab"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a8e26c00bed00782a17b87f8afa5c96ab">arm_compute::TensorInfo::has_padding</a></div><div class="ttdeci">bool has_padding()</div><div class="ttdoc">Checks if the tensor has been allocated with padding or not. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00287">TensorInfo.h:287</a></div></div>
+<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a
d13a67d4dbc337c707a76401dc103ff3"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#ad13a67d4dbc337c707a76401dc103ff3">arm_compute::TensorInfo::padding</a></div><div class="ttdeci">PaddingSize padding() const </div><div class="ttdoc">Padding of tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00287">TensorInfo.h:287</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>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a38382dc1f04d28cab04d921b8324dc07"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a38382dc1f04d28cab04d921b8324dc07">arm_compute::TensorInfo::num_dimensions</a></div><div class="ttdeci">size_t num_dimensions() const </div><div class="ttdoc">The number of dimensions of the tensor (rank) </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00239">TensorInfo.h:239</a></div></div>
-<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a61fd20903a4b595b3d33bc443d23957e"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a61fd20903a4b595b3d33bc443d23957e">arm_compute::TensorInfo::is_resizable</a></div><div class="ttdeci">bool is_resizable()</div><div class="ttdoc">Flag indicating whether the size of the tensor can be changed. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00295">TensorInfo.h:295</a></div></div>
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<li class="navelem"><a class="el" href="dir_214608ef36d61442cb2b0c1c4e9a7def.xhtml">arm_compute</a></li><li class="navelem"><a class="el" href="dir_1fb090f0c6070330bfaccc4236d3ca0d.xhtml">core</a></li><li class="navelem"><a class="el" href="_tensor_info_8h.xhtml">TensorInfo.h</a></li>
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