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<div class="title">RawTensor.h</div> </div>
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<a href="_raw_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>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment"> * Copyright (c) 2017 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="preprocessor">#ifndef __ARM_COMPUTE_TEST_RAW_TENSOR_H__</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;<span class="preprocessor">#define __ARM_COMPUTE_TEST_RAW_TENSOR_H__</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_tensor_shape_8h.xhtml">arm_compute/core/TensorShape.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="preprocessor">#include &lt;cstddef&gt;</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>&#160;<span class="preprocessor">#include &lt;cstdint&gt;</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="preprocessor">#include &lt;memory&gt;</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;{</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;<span class="keyword">namespace </span>test</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;{</div><div class="line"><a name="l00047"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml"> 47</a></span>&#160;<span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> final</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160;{</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#ad5f076c202d054557fde207a7e3b3b41">RawTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a13761831550669f43f4edee978181c46">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a0c875a3203d902e2ad6bc3045355e69e">format</a>, <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a16bb8940c9d6aff998db9bd0ba011ffe">fixed_point_position</a> = 0);</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#ad5f076c202d054557fde207a7e3b3b41">RawTensor</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_raw_tensor.xhtml#a45cc7b9a37aa9f0e7d479248a27e1f58">data_type</a>, <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#abd107d6e8ccfc38f781be8683d8141c2">num_channels</a> = 1, <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a16bb8940c9d6aff998db9bd0ba011ffe">fixed_point_position</a> = 0);</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#ad5f076c202d054557fde207a7e3b3b41">RawTensor</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> &amp;tensor);</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160;</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> &amp;<a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#abf951228abf3337929f26f7c0feedcac">operator =</a>(<a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> tensor);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#ad5f076c202d054557fde207a7e3b3b41">RawTensor</a>(<a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> &amp;&amp;) = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a1ab8156de913df911b4ad1ad46f51313">~RawTensor</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160;</div><div class="line"><a name="l00081"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5"> 81</a></span>&#160; <span class="keyword">using</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">BufferType</a> = uint8_t;</div><div class="line"><a name="l00082"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a0507d380866a3466b88018d5553e6dad"> 82</a></span>&#160; <span class="keyword">using</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a0507d380866a3466b88018d5553e6dad">Buffer</a> = std::unique_ptr&lt;BufferType[]&gt;;</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160;</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">BufferType</a> &amp;<a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a0914d4c14c88792d8fd2197c612b927e">operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>);</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">BufferType</a> &amp;<a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a0914d4c14c88792d8fd2197c612b927e">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="l00095"></a><span class="lineno"> 95</span>&#160;</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a13761831550669f43f4edee978181c46">shape</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a448f57f9d6aec61b3d85b898affe4a2e">element_size</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160;</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#aac782da1f912bceb5d8ad00c8dc892ac">size</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a0c875a3203d902e2ad6bc3045355e69e">format</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a45cc7b9a37aa9f0e7d479248a27e1f58">data_type</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#abd107d6e8ccfc38f781be8683d8141c2">num_channels</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160;</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#ab5fe769d05a0f7dfee63972bdbd54261">num_elements</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160;</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a16bb8940c9d6aff998db9bd0ba011ffe">fixed_point_position</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160;</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">BufferType</a> *<a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a7b53deaf986aa58ffa0090cc241dec64">data</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160;</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">BufferType</a> *<a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a7b53deaf986aa58ffa0090cc241dec64">data</a>();</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">BufferType</a> *<a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#af53a404b9a0d663c5d60b199799ba185">operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp;coord) <span class="keyword">const</span>;</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">BufferType</a> *<a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#af53a404b9a0d663c5d60b199799ba185">operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp;coord);</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; <span class="keyword">friend</span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a3d880156c78661ccfe9d3b706d260d56">swap</a>(<a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> &amp;tensor1, <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> &amp;tensor2);</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160;</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a0507d380866a3466b88018d5553e6dad">Buffer</a> _buffer{ <span class="keyword">nullptr</span> };</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> _shape{};</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> _format{ <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a696b031073e74bf2cb98e5ef201d4aa3">Format::UNKNOWN</a> };</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> _data_type{ <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a696b031073e74bf2cb98e5ef201d4aa3">DataType::UNKNOWN</a> };</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; <span class="keywordtype">int</span> _num_channels{ 0 };</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; <span class="keywordtype">int</span> _fixed_point_position{ 0 };</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160;};</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160;} <span class="comment">// namespace test</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160;<span class="preprocessor">#endif</span></div><div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_abd107d6e8ccfc38f781be8683d8141c2"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#abd107d6e8ccfc38f781be8683d8141c2">arm_compute::test::RawTensor::num_channels</a></div><div class="ttdeci">int num_channels() const </div><div class="ttdoc">Number of channels of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00124">RawTensor.cpp:124</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a1ab8156de913df911b4ad1ad46f51313"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a1ab8156de913df911b4ad1ad46f51313">arm_compute::test::RawTensor::~RawTensor</a></div><div class="ttdeci">~RawTensor()=default</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">Simple tensor object that stores elements in a consecutive chunk of memory. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8h_source.xhtml#l00047">RawTensor.h:47</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_1test_1_1_raw_tensor_xhtml_a448f57f9d6aec61b3d85b898affe4a2e"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a448f57f9d6aec61b3d85b898affe4a2e">arm_compute::test::RawTensor::element_size</a></div><div class="ttdeci">size_t element_size() const </div><div class="ttdoc">Size of each element in the tensor in bytes. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00091">RawTensor.cpp:91</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_abf951228abf3337929f26f7c0feedcac"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#abf951228abf3337929f26f7c0feedcac">arm_compute::test::RawTensor::operator=</a></div><div class="ttdeci">RawTensor &amp; operator=(RawTensor tensor)</div><div class="ttdoc">Create a deep copy of the given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00069">RawTensor.cpp:69</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a16bb8940c9d6aff998db9bd0ba011ffe"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a16bb8940c9d6aff998db9bd0ba011ffe">arm_compute::test::RawTensor::fixed_point_position</a></div><div class="ttdeci">int fixed_point_position() const </div><div class="ttdoc">The number of bits for the fractional part of the fixed point numbers. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00096">RawTensor.cpp:96</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a13761831550669f43f4edee978181c46"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a13761831550669f43f4edee978181c46">arm_compute::test::RawTensor::shape</a></div><div class="ttdeci">TensorShape shape() const </div><div class="ttdoc">Shape of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00086">RawTensor.cpp:86</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a0507d380866a3466b88018d5553e6dad"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a0507d380866a3466b88018d5553e6dad">arm_compute::test::RawTensor::Buffer</a></div><div class="ttdeci">std::unique_ptr&lt; BufferType[]&gt; Buffer</div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8h_source.xhtml#l00082">RawTensor.h:82</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a696b031073e74bf2cb98e5ef201d4aa3"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a696b031073e74bf2cb98e5ef201d4aa3">arm_compute::Format::UNKNOWN</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a0914d4c14c88792d8fd2197c612b927e"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a0914d4c14c88792d8fd2197c612b927e">arm_compute::test::RawTensor::operator[]</a></div><div class="ttdeci">BufferType &amp; operator[](size_t offset)</div><div class="ttdoc">Return value at offset in the buffer. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00076">RawTensor.cpp:76</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#l00201">helpers.h:201</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_aac782da1f912bceb5d8ad00c8dc892ac"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#aac782da1f912bceb5d8ad00c8dc892ac">arm_compute::test::RawTensor::size</a></div><div class="ttdeci">size_t size() const </div><div class="ttdoc">Total size of the tensor in bytes. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00101">RawTensor.cpp:101</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a0c875a3203d902e2ad6bc3045355e69e"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a0c875a3203d902e2ad6bc3045355e69e">arm_compute::test::RawTensor::format</a></div><div class="ttdeci">Format format() const </div><div class="ttdoc">Image format of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00107">RawTensor.cpp:107</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a3d880156c78661ccfe9d3b706d260d56"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a3d880156c78661ccfe9d3b706d260d56">arm_compute::test::RawTensor::swap</a></div><div class="ttdeci">friend void swap(RawTensor &amp;tensor1, RawTensor &amp;tensor2)</div><div class="ttdoc">Swaps the content of the provided tensors. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00168">RawTensor.cpp:168</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdef"><b>Definition:</b> <a href="01__library_8dox_source.xhtml#l00001">01_library.dox:1</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a9c3b791dba4a4cff3785264b9260e9d5"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">arm_compute::test::RawTensor::BufferType</a></div><div class="ttdeci">uint8_t BufferType</div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8h_source.xhtml#l00081">RawTensor.h:81</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_af53a404b9a0d663c5d60b199799ba185"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#af53a404b9a0d663c5d60b199799ba185">arm_compute::test::RawTensor::operator()</a></div><div class="ttdeci">const BufferType * operator()(const Coordinates &amp;coord) const </div><div class="ttdoc">Read only access to the specified element. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00158">RawTensor.cpp:158</a></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#l00038">Types.h:38</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="classarm__compute_1_1test_1_1_raw_tensor_xhtml_ad5f076c202d054557fde207a7e3b3b41"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#ad5f076c202d054557fde207a7e3b3b41">arm_compute::test::RawTensor::RawTensor</a></div><div class="ttdeci">RawTensor(TensorShape shape, Format format, int fixed_point_position=0)</div><div class="ttdoc">Create an uninitialised tensor of the given shape and format. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00040">RawTensor.cpp:40</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a7b53deaf986aa58ffa0090cc241dec64"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a7b53deaf986aa58ffa0090cc241dec64">arm_compute::test::RawTensor::data</a></div><div class="ttdeci">const BufferType * data() const </div><div class="ttdoc">Constant pointer to the underlying buffer. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00148">RawTensor.cpp:148</a></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#l00060">Types.h:60</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_ab5fe769d05a0f7dfee63972bdbd54261"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#ab5fe769d05a0f7dfee63972bdbd54261">arm_compute::test::RawTensor::num_elements</a></div><div class="ttdeci">int num_elements() const </div><div class="ttdoc">Number of elements of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00143">RawTensor.cpp:143</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_1test_1_1_raw_tensor_xhtml_a45cc7b9a37aa9f0e7d479248a27e1f58"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a45cc7b9a37aa9f0e7d479248a27e1f58">arm_compute::test::RawTensor::data_type</a></div><div class="ttdeci">DataType data_type() const </div><div class="ttdoc">Data type of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8cpp_source.xhtml#l00112">RawTensor.cpp:112</a></div></div>
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