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| <a href="_simple_tensor_8h.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2017-2019 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> * of this software and associated documentation files (the "Software"), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#ifndef ARM_COMPUTE_TEST_SIMPLE_TENSOR_H</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#define ARM_COMPUTE_TEST_SIMPLE_TENSOR_H</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> </div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="_tensor_shape_8h.xhtml">arm_compute/core/TensorShape.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="arm__compute_2core_2_utils_8h.xhtml">arm_compute/core/Utils.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_toolchain_support_8h.xhtml">support/ToolchainSupport.h</a>"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="_i_accessor_8h.xhtml">tests/IAccessor.h</a>"</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="tests_2_utils_8h.xhtml">tests/Utils.h</a>"</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include <algorithm></span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include <array></span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include <cstddef></span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="preprocessor">#include <cstdint></span></div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="preprocessor">#include <functional></span></div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#include <memory></span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="preprocessor">#include <stdexcept></span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="preprocessor">#include <utility></span></div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> {</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">namespace </span>test</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="keyword">class </span>RawTensor;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="comment"></span></div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="comment">/** Simple tensor object that stores elements in a consecutive chunk of memory.</span></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="comment"> *</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"> * It can be created by either loading an image from a file which also</span></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment"> * initialises the content of the tensor or by explcitly specifying the size.</span></div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"> * The latter leaves the content uninitialised.</span></div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="comment"> *</span></div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="comment"> * Furthermore, the class provides methods to convert the tensor's values into</span></div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"> * different image format.</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> */</span></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00059"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml"> 59</a></span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1test_1_1_i_accessor.xhtml">IAccessor</a></div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> {</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="keyword">public</span>:<span class="comment"></span></div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="comment"> /** Create an uninitialised tensor. */</span></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment"></span></div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="comment"> /** Create an uninitialised tensor of the given @p shape and @p format.</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="comment"> *</span></div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="comment"> * @param[in] shape Shape of the new raw tensor.</span></div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="comment"> * @param[in] format Format of the new raw tensor.</span></div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="comment"> */</span></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">format</a>);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="comment"></span></div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> <span class="comment"> /** Create an uninitialised tensor of the given @p shape and @p data type.</span></div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="comment"> *</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="comment"> * @param[in] shape Shape of the new raw tensor.</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="comment"> * @param[in] data_type Data type of the new raw tensor.</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="comment"> * @param[in] num_channels (Optional) Number of channels (default = 1).</span></div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="comment"> * @param[in] quantization_info (Optional) Quantization info for asymmetric quantization (default = empty).</span></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="comment"> * @param[in] data_layout (Optional) Data layout of the tensor (default = NCHW).</span></div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="comment"> */</span></div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>,</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a> = 1,</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a> = <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a>(),</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a> = <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>);</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="comment"></span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="comment"> /** Create a deep copy of the given @p tensor.</span></div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="comment"> *</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="comment"> * @param[in] tensor To be copied tensor.</span></div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="comment"> */</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &tensor);</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="comment"></span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="comment"> /** Create a deep copy of the given @p tensor.</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="comment"> *</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> <span class="comment"> * @param[in] tensor To be copied tensor.</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> <span class="comment"> *</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="comment"> * @return a copy of the given tensor.</span></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="comment"> */</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad4622eda610d53fb6852209f0213aeed">operator=</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> tensor);<span class="comment"></span></div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> <span class="comment"> /** Allow instances of this class to be move constructed */</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &&) = <span class="keywordflow">default</span>;<span class="comment"></span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="comment"> /** Default destructor. */</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a16d7ecd97f89cf9dc40b3fc7c9abe2cd">~SimpleTensor</a>() = <span class="keywordflow">default</span>;</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="comment"></span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="comment"> /** Tensor value type */</span></div><div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#afb9ded5f49336ae503bb9f2035ea902b"> 104</a></span>  <span class="keyword">using</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#afb9ded5f49336ae503bb9f2035ea902b">value_type</a> = T;<span class="comment"></span></div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="comment"> /** Tensor buffer pointer type */</span></div><div class="line"><a name="l00106"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f"> 106</a></span>  <span class="keyword">using</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f">Buffer</a> = std::unique_ptr<value_type[]>;</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00108"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a467ad6d14558452f498777a7823fa252"> 108</a></span>  <span class="keyword">friend</span> <span class="keyword">class </span><a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a>;</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="comment"></span></div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="comment"> /** Return value at @p offset in the buffer.</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="comment"> *</span></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="comment"> * @param[in] offset Offset within the buffer.</span></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="comment"> *</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="comment"> * @return value in the buffer.</span></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment"> */</span></div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  T &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="comment"></span></div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="comment"> /** Return constant value at @p offset in the buffer.</span></div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="comment"> *</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="comment"> * @param[in] offset Offset within the buffer.</span></div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="comment"> *</span></div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="comment"> * @return constant value in the buffer.</span></div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="comment"> */</span></div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">const</span> T &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>) <span class="keyword">const</span>;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="comment"></span></div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="comment"> /** Shape of the tensor.</span></div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="comment"> *</span></div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="comment"> * @return the shape of the tensor.</span></div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="comment"> */</span></div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>() <span class="keyword">const override</span>;<span class="comment"></span></div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="comment"> /** Size of each element in the tensor in bytes.</span></div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span> <span class="comment"> *</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="comment"> * @return the size of each element in the tensor in bytes.</span></div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="comment"> */</span></div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">element_size</a>() <span class="keyword">const override</span>;<span class="comment"></span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="comment"> /** Total size of the tensor in bytes.</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="comment"> *</span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> <span class="comment"> * @return the total size of the tensor in bytes.</span></div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="comment"> */</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">size</a>() <span class="keyword">const override</span>;<span class="comment"></span></div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="comment"> /** Image format of the tensor.</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment"> *</span></div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment"> * @return the format of the tensor.</span></div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="comment"> */</span></div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">format</a>() <span class="keyword">const override</span>;<span class="comment"></span></div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="comment"> /** Data layout of the tensor.</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="comment"> *</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="comment"> * @return the data layout of the tensor.</span></div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="comment"> */</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a>() <span class="keyword">const override</span>;<span class="comment"></span></div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span> <span class="comment"> /** Data type of the tensor.</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> <span class="comment"> *</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span> <span class="comment"> * @return the data type of the tensor.</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span> <span class="comment"> */</span></div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>() <span class="keyword">const override</span>;<span class="comment"></span></div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span> <span class="comment"> /** Number of channels of the tensor.</span></div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> <span class="comment"> *</span></div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span> <span class="comment"> * @return the number of channels of the tensor.</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span> <span class="comment"> */</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>() <span class="keyword">const override</span>;<span class="comment"></span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="comment"> /** Number of elements of the tensor.</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="comment"> *</span></div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> <span class="comment"> * @return the number of elements of the tensor.</span></div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> <span class="comment"> */</span></div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">num_elements</a>() <span class="keyword">const override</span>;<span class="comment"></span></div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> <span class="comment"> /** Available padding around the tensor.</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span> <span class="comment"> *</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> <span class="comment"> * @return the available padding around the tensor.</span></div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span> <span class="comment"> */</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a79e20eacb1e963e24a21ebd7369effd7">padding</a>() <span class="keyword">const override</span>;<span class="comment"></span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> <span class="comment"> /** Quantization info in case of asymmetric quantized type</span></div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> <span class="comment"> *</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span> <span class="comment"> * @return</span></div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span> <span class="comment"> */</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>() <span class="keyword">const override</span>;</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="comment"></span></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> <span class="comment"> /** Constant pointer to the underlying buffer.</span></div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> <span class="comment"> *</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> <span class="comment"> * @return a constant pointer to the data.</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> <span class="comment"> */</span></div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keyword">const</span> T *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">data</a>() <span class="keyword">const</span>;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> <span class="comment"></span></div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> <span class="comment"> /** Pointer to the underlying buffer.</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> <span class="comment"> *</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> <span class="comment"> * @return a pointer to the data.</span></div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span> <span class="comment"> */</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  T *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">data</a>();</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> <span class="comment"></span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span> <span class="comment"> /** Read only access to the specified element.</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> <span class="comment"> *</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> <span class="comment"> * @param[in] coord Coordinates of the desired element.</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> <span class="comment"> *</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span> <span class="comment"> * @return A pointer to the desired element.</span></div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> <span class="comment"> */</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keyword">const</span> <span class="keywordtype">void</span> *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &coord) <span class="keyword">const override</span>;</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span> <span class="comment"></span></div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span> <span class="comment"> /** Access to the specified element.</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span> <span class="comment"> *</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> <span class="comment"> * @param[in] coord Coordinates of the desired element.</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> <span class="comment"> *</span></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> <span class="comment"> * @return A pointer to the desired element.</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span> <span class="comment"> */</span></div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordtype">void</span> *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &coord) <span class="keyword">override</span>;</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span> <span class="comment"></span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span> <span class="comment"> /** Swaps the content of the provided tensors.</span></div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> <span class="comment"> *</span></div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span> <span class="comment"> * @param[in, out] tensor1 Tensor to be swapped.</span></div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> <span class="comment"> * @param[in, out] tensor2 Tensor to be swapped.</span></div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span> <span class="comment"> */</span></div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> U></div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keyword">friend</span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">swap</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<U></a> &tensor1, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<U></a> &tensor2);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span> <span class="keyword">protected</span>:</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f">Buffer</a> _buffer{ <span class="keyword">nullptr</span> };</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> _shape{};</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> _format{ <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">Format::UNKNOWN</a> };</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> _data_type{ <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataType::UNKNOWN</a> };</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keywordtype">int</span> _num_channels{ 0 };</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  QuantizationInfo _quantization_info{};</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> _data_layout{ <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataLayout::UNKNOWN</a> };</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> };</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> </div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T1, <span class="keyword">typename</span> T2></div><div class="line"><a name="l00224"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test.xhtml#a30aaea1825f3464f073e1d1bce82e420"> 224</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T1></a> <a class="code" href="namespacearm__compute_1_1test.xhtml#a30aaea1825f3464f073e1d1bce82e420">copy_tensor</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T2></a> &tensor)</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span> {</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T1></a> st(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>(), tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>(),</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>(),</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>(),</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a>());</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> n = 0; n < size_t(st.num_elements()); n++)</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  {</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  st.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">data</a>()[n] = static_cast<T1>(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">data</a>()[n]);</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  }</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <span class="keywordflow">return</span> st;</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> }</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> template <typename T1, typename T2, typename std::enable_if<std::is_same<T1, T2>::value, <span class="keywordtype">int</span>><a class="code" href="namespace_gemm_tuner.xhtml#a7aead736a07eaf25623ad7bfa1f0ee2d">::type</a> = 0></div><div class="line"><a name="l00238"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test.xhtml#aafd2a1bcbb2f4dd73e6f6f322e9014c7"> 238</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T1></a> <a class="code" href="namespacearm__compute_1_1test.xhtml#a30aaea1825f3464f073e1d1bce82e420">copy_tensor</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<half></a> &tensor)</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span> {</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T1></a> st(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">shape</a>(), tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">data_type</a>(),</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">num_channels</a>(),</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">quantization_info</a>(),</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">data_layout</a>());</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  memcpy((<span class="keywordtype">void</span> *)st.data(), (<span class="keyword">const</span> <span class="keywordtype">void</span> *)tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">data</a>(), size_t(st.num_elements() * <span class="keyword">sizeof</span>(T1)));</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <span class="keywordflow">return</span> st;</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> }</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> </div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="keyword">template</span> < <span class="keyword">typename</span> T1, <span class="keyword">typename</span> T2, <span class="keyword">typename</span> std::enable_if < (std::is_same<T1, half>::value || std::is_same<T2, half>::value), <span class="keywordtype">int</span> >::type = 0 ></div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> SimpleTensor<T1> <a class="code" href="namespacearm__compute_1_1test.xhtml#a30aaea1825f3464f073e1d1bce82e420">copy_tensor</a>(<span class="keyword">const</span> SimpleTensor<half> &tensor)</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span> {</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  SimpleTensor<T1> st(tensor.shape(), tensor.data_type(),</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  tensor.num_channels(),</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  tensor.quantization_info(),</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  tensor.data_layout());</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> n = 0; n < size_t(st.num_elements()); n++)</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  {</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  st.data()[n] = half_float::detail::half_cast<T1, T2>(tensor.data()[n]);</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  }</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <span class="keywordflow">return</span> st;</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span> }</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> </div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00263"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a057b52c2d0c51f410da5e48f47706c4e"> 263</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">SimpleTensor<T>::SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format)</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  : _buffer(nullptr),</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  _shape(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>),</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  _format(format),</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  _quantization_info(),</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  _data_layout(<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a>::<a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">NCHW</a>)</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> {</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  _num_channels = num_channels();</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  _buffer = support::cpp14::make_unique<T[]>(num_elements() * _num_channels);</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span> }</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> </div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00275"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad2a966c334c9bb65621f891ff5e2b5bb"> 275</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::SimpleTensor</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, <span class="keywordtype">int</span> num_channels, <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> quantization_info, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>)</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  : _buffer(nullptr),</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  _shape(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>),</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  _data_type(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>),</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  _num_channels(num_channels),</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  _quantization_info(quantization_info),</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  _data_layout(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>)</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span> {</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  _buffer = support::cpp14::make_unique<T[]>(this->_shape.total_size() * _num_channels);</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> }</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span> </div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00287"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ae1769959044a4356fdc93cac2b03a5f6"> 287</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::SimpleTensor</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> &tensor)</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  : _buffer(nullptr),</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  _shape(tensor.<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>()),</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  _format(tensor.format()),</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  _data_type(tensor.<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>()),</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  _num_channels(tensor.num_channels()),</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  _quantization_info(tensor.quantization_info()),</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  _data_layout(tensor.<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>())</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span> {</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  _buffer = support::cpp14::make_unique<T[]>(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">num_elements</a>() * _num_channels);</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  std::copy_n(tensor.<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">data</a>(), this->_shape.total_size() * _num_channels, _buffer.get());</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> }</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span> </div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00301"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad4622eda610d53fb6852209f0213aeed"> 301</a></span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T></a> &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::operator=</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor</a> tensor)</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span> {</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(*<span class="keyword">this</span>, tensor);</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">return</span> *<span class="keyword">this</span>;</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> }</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span> </div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00309"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52"> 309</a></span> T &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>)</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> {</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordflow">return</span> _buffer[<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>];</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span> }</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span> </div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00315"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#adb16bab00d690a7952ca2f3d3d66bfa2"> 315</a></span> <span class="keyword">const</span> T &<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::operator[]</a>(<span class="keywordtype">size_t</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>)<span class="keyword"> const</span></div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> <span class="keyword"></span>{</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="keywordflow">return</span> _buffer[<a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>];</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> }</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> </div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00321"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba"> 321</a></span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">SimpleTensor<T>::shape</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span> <span class="keyword"></span>{</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keywordflow">return</span> _shape;</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">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00327"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23"> 327</a></span> <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::element_size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span> <span class="keyword"></span>{</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordflow">return</span> num_channels() * <a class="code" href="namespacearm__compute.xhtml#a34b06c0cd94808a77b697e79880b84b0">element_size_from_data_type</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>());</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span> }</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> </div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00333"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44"> 333</a></span> <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::quantization_info</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> <span class="keyword"></span>{</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordflow">return</span> _quantization_info;</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> </div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00339"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16"> 339</a></span> <span class="keywordtype">size_t</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::size</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span> <span class="keyword"></span>{</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> size = <a class="code" href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">std::accumulate</a>(_shape.cbegin(), _shape.cend(), 1, std::multiplies<size_t>());</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">return</span> size * element_size();</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span> }</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> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00346"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db"> 346</a></span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::format</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> <span class="keyword"></span>{</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordflow">return</span> _format;</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> }</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span> </div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00352"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c"> 352</a></span> <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">DataLayout</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">SimpleTensor<T>::data_layout</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> <span class="keyword"></span>{</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="keywordflow">return</span> _data_layout;</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> }</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span> </div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00358"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881"> 358</a></span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">SimpleTensor<T>::data_type</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span> <span class="keyword"></span>{</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="keywordflow">if</span>(_format != Format::UNKNOWN)</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  {</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a59846ef5ca75cd81cdb7e8a1ce08f9db">data_type_from_format</a>(_format);</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  }</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  {</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="keywordflow">return</span> _data_type;</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  }</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> }</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span> </div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00371"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb"> 371</a></span> <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::num_channels</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> <span class="keyword"></span>{</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keywordflow">switch</span>(_format)</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  {</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordflow">case</span> Format::U8:</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordflow">case</span> Format::U16:</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="keywordflow">case</span> Format::S16:</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="keywordflow">case</span> Format::U32:</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="keywordflow">case</span> Format::S32:</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keywordflow">case</span> Format::F16:</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keywordflow">case</span> Format::F32:</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <span class="keywordflow">return</span> 1;</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="comment">// Because the U and V channels are subsampled</span></div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="comment">// these formats appear like having only 2 channels:</span></div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keywordflow">case</span> Format::YUYV422:</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="keywordflow">case</span> Format::UYVY422:</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordflow">return</span> 2;</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordflow">case</span> Format::UV88:</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="keywordflow">return</span> 2;</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="keywordflow">case</span> Format::RGB888:</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="keywordflow">return</span> 3;</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="keywordflow">case</span> Format::RGBA8888:</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="keywordflow">return</span> 4;</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="keywordflow">case</span> Format::UNKNOWN:</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="keywordflow">return</span> _num_channels;</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="comment">//Doesn't make sense for planar formats:</span></div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keywordflow">case</span> Format::NV12:</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keywordflow">case</span> Format::NV21:</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keywordflow">case</span> Format::IYUV:</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keywordflow">case</span> Format::YUV444:</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keywordflow">return</span> 0;</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  }</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> }</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span> </div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00407"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e"> 407</a></span> <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::num_elements</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span> <span class="keyword"></span>{</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  <span class="keywordflow">return</span> _shape.total_size();</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span> }</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span> </div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00413"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a79e20eacb1e963e24a21ebd7369effd7"> 413</a></span> <a class="code" href="structarm__compute_1_1_border_size.xhtml">PaddingSize</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a735a025fce26c1ef147b54426df18181">SimpleTensor<T>::padding</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> <span class="keyword"></span>{</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a4467b302fc9ec312c40580336ab783da">PaddingSize</a>(0);</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span> }</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> </div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00419"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19"> 419</a></span> <span class="keyword">const</span> T *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::data</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span> <span class="keyword"></span>{</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="keywordflow">return</span> _buffer.get();</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span> }</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span> </div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00425"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#adc1e16b293a89a9ccc9541058b5ca560"> 425</a></span> T *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::data</a>()</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> {</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <span class="keywordflow">return</span> _buffer.get();</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span> }</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span> </div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00431"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f"> 431</a></span> <span class="keyword">const</span> <span class="keywordtype">void</span> *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &coord)<span class="keyword"> const</span></div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span> <span class="keyword"></span>{</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="keywordflow">return</span> _buffer.get() + <a class="code" href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">coord2index</a>(_shape, coord) * _num_channels;</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span> }</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span> </div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00437"></a><span class="lineno"><a class="line" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a2df95f7046b81e69a1265a42202ea068"> 437</a></span> <span class="keywordtype">void</span> *<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<T>::operator()</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &coord)</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> {</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="keywordflow">return</span> _buffer.get() + <a class="code" href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">coord2index</a>(_shape, coord) * _num_channels;</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span> }</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span> </div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span> <span class="keyword">template</span> <<span class="keyword">typename</span> U></div><div class="line"><a name="l00443"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3"> 443</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<U></a> &tensor1, <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<U></a> &tensor2)</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span> {</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="comment">// Use unqualified call to swap to enable ADL. But make std::swap available</span></div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <span class="comment">// as backup.</span></div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <span class="keyword">using</span> <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">std::swap</a>;</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._shape, tensor2._shape);</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._format, tensor2._format);</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._data_type, tensor2._data_type);</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._num_channels, tensor2._num_channels);</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._quantization_info, tensor2._quantization_info);</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">swap</a>(tensor1._buffer, tensor2._buffer);</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span> }</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span> } <span class="comment">// namespace test</span></div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> } <span class="comment">// namespace arm_compute</span></div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span> <span class="preprocessor">#endif </span><span class="comment">/* ARM_COMPUTE_TEST_SIMPLE_TENSOR_H */</span><span class="preprocessor"></span></div><div class="ttc" id="_i_accessor_8h_xhtml"><div class="ttname"><a href="_i_accessor_8h.xhtml">IAccessor.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a51920d34b0fa5415e84891ad8e755224"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a51920d34b0fa5415e84891ad8e755224">arm_compute::test::SimpleTensor::swap</a></div><div class="ttdeci">friend void swap(SimpleTensor< U > &tensor1, SimpleTensor< U > &tensor2)</div><div class="ttdoc">Swaps the content of the provided tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00443">SimpleTensor.h:443</a></div></div> |
| <div class="ttc" id="src_2core_2_c_l_2cl__kernels_2_helpers_8h_xhtml_a009469e4d9b8fce3b6d5e97d2077827d"><div class="ttname"><a href="src_2core_2_c_l_2cl__kernels_2_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="src_2core_2_c_l_2cl__kernels_2_helpers_8h_source.xhtml#l00510">helpers.h:510</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00097">AbsoluteDifference.cpp:97</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a62b67b578f684c4d516843c9dea86a23"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a62b67b578f684c4d516843c9dea86a23">arm_compute::test::SimpleTensor::element_size</a></div><div class="ttdeci">size_t element_size() const override</div><div class="ttdoc">Size of each element in the tensor in bytes.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00327">SimpleTensor.h:327</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">arm_compute::test::RawTensor</a></div><div class="ttdoc">Subclass of SimpleTensor using uint8_t as value type.</div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8h_source.xhtml#l00038">RawTensor.h:38</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_acf5f12bbab64dd614bd8220c97fe484f"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">arm_compute::test::validation::data_layout</a></div><div class="ttdeci">const DataLayout data_layout</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_o_n_2_im2_col_8cpp_source.xhtml#l00146">Im2Col.cpp:146</a></div></div> |
| <div class="ttc" id="_toolchain_support_8h_xhtml"><div class="ttname"><a href="_toolchain_support_8h.xhtml">ToolchainSupport.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ad7701a09a964eab360a8e51fa7ad2c16"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad7701a09a964eab360a8e51fa7ad2c16">arm_compute::test::SimpleTensor::size</a></div><div class="ttdeci">size_t size() const override</div><div class="ttdoc">Total size of the tensor in bytes.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00339">SimpleTensor.h:339</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_af6124c81d1e81f182d64ae76caa3fa52"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#af6124c81d1e81f182d64ae76caa3fa52">arm_compute::test::SimpleTensor::operator[]</a></div><div class="ttdeci">T & operator[](size_t offset)</div><div class="ttdoc">Return value at offset in the buffer.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00309">SimpleTensor.h:309</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_border_size_xhtml"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml">arm_compute::BorderSize</a></div><div class="ttdoc">Container for 2D border size.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00269">Types.h:269</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a34b06c0cd94808a77b697e79880b84b0"><div class="ttname"><a href="namespacearm__compute.xhtml#a34b06c0cd94808a77b697e79880b84b0">arm_compute::element_size_from_data_type</a></div><div class="ttdeci">size_t element_size_from_data_type(DataType dt)</div><div class="ttdoc">The size in bytes of the data type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00186">Utils.h:186</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ac4b36cc1e56b0b7e579bb4b7196490db"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac4b36cc1e56b0b7e579bb4b7196490db">arm_compute::test::SimpleTensor::format</a></div><div class="ttdeci">Format format() const override</div><div class="ttdoc">Image format of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00346">SimpleTensor.h:346</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a9a3e72153aeb3ed212e9c3698774e881"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a9a3e72153aeb3ed212e9c3698774e881">arm_compute::test::SimpleTensor::data_type</a></div><div class="ttdeci">DataType data_type() const override</div><div class="ttdoc">Data type of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00358">SimpleTensor.h:358</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a28edc8880596d14c099f3c2509efc8b3"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">arm_compute::test::swap</a></div><div class="ttdeci">void swap(SimpleTensor< U > &tensor1, SimpleTensor< U > &tensor2)</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00443">SimpleTensor.h:443</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_aba5871b3e4a65d057ec1c28fce8b00ba"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aba5871b3e4a65d057ec1c28fce8b00ba">arm_compute::test::SimpleTensor::shape</a></div><div class="ttdeci">TensorShape shape() const override</div><div class="ttdoc">Shape of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00321">SimpleTensor.h:321</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a30aaea1825f3464f073e1d1bce82e420"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a30aaea1825f3464f073e1d1bce82e420">arm_compute::test::copy_tensor</a></div><div class="ttdeci">SimpleTensor< T1 > copy_tensor(const SimpleTensor< T2 > &tensor)</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00224">SimpleTensor.h:224</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2020 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a9be4cb7e6ee20063a4a10bc3abb750b9"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">arm_compute::test::coord2index</a></div><div class="ttdeci">int coord2index(const TensorShape &shape, const Coordinates &coord)</div><div class="ttdoc">Linearise the given coordinate.</div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00485">Utils.h:485</a></div></div> |
| <div class="ttc" id="arm__compute_2core_2_utils_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_utils_8h.xhtml">Utils.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_quantization_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_quantization_info.xhtml">arm_compute::QuantizationInfo</a></div><div class="ttdoc">Quantization information.</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00069">QuantizationInfo.h:69</a></div></div> |
| <div class="ttc" id="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#l00053">Types.h:53</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a16d7ecd97f89cf9dc40b3fc7c9abe2cd"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a16d7ecd97f89cf9dc40b3fc7c9abe2cd">arm_compute::test::SimpleTensor::~SimpleTensor</a></div><div class="ttdeci">~SimpleTensor()=default</div><div class="ttdoc">Default destructor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item.</div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_afb9ded5f49336ae503bb9f2035ea902b"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#afb9ded5f49336ae503bb9f2035ea902b">arm_compute::test::SimpleTensor< uint8_t >::value_type</a></div><div class="ttdeci">uint8_t value_type</div><div class="ttdoc">Tensor value type.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00104">SimpleTensor.h:104</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a79e20eacb1e963e24a21ebd7369effd7"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a79e20eacb1e963e24a21ebd7369effd7">arm_compute::test::SimpleTensor::padding</a></div><div class="ttdeci">PaddingSize padding() const override</div><div class="ttdoc">Available padding around the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00413">SimpleTensor.h:413</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a5f63b63606dbbbe54474e6e970a6738c"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a5f63b63606dbbbe54474e6e970a6738c">arm_compute::test::SimpleTensor::data_layout</a></div><div class="ttdeci">DataLayout data_layout() const override</div><div class="ttdoc">Data layout of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00352">SimpleTensor.h:352</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a4467b302fc9ec312c40580336ab783da"><div class="ttname"><a href="namespacearm__compute.xhtml#a4467b302fc9ec312c40580336ab783da">arm_compute::PaddingSize</a></div><div class="ttdeci">BorderSize PaddingSize</div><div class="ttdoc">Container for 2D padding size.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00356">Types.h:356</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</a></div><div class="ttdoc">Num samples, channels, height, width.</div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a011bb65bd16aaf66b8efb3929692b2ce"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a011bb65bd16aaf66b8efb3929692b2ce">arm_compute::test::SimpleTensor::SimpleTensor</a></div><div class="ttdeci">SimpleTensor()=default</div><div class="ttdoc">Create an uninitialised tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_a39537b09ccc3ce3d17922f4ef49a123f"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a39537b09ccc3ce3d17922f4ef49a123f">arm_compute::test::SimpleTensor::operator()</a></div><div class="ttdeci">const void * operator()(const Coordinates &coord) const override</div><div class="ttdoc">Read only access to the specified element.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00431">SimpleTensor.h:431</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a59846ef5ca75cd81cdb7e8a1ce08f9db"><div class="ttname"><a href="namespacearm__compute.xhtml#a59846ef5ca75cd81cdb7e8a1ce08f9db">arm_compute::data_type_from_format</a></div><div class="ttdeci">DataType data_type_from_format(Format format)</div><div class="ttdoc">Return the data type used by a given single-planar pixel format.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l00219">Utils.h:219</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_acf18a24d1f21176e811e88cee2a70f1f"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#acf18a24d1f21176e811e88cee2a70f1f">arm_compute::test::SimpleTensor< uint8_t >::Buffer</a></div><div class="ttdeci">std::unique_ptr< value_type[]> Buffer</div><div class="ttdoc">Tensor buffer pointer type.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00106">SimpleTensor.h:106</a></div></div> |
| <div class="ttc" id="tests_2_utils_8h_xhtml"><div class="ttname"><a href="tests_2_utils_8h.xhtml">Utils.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">arm_compute::test::SimpleTensor</a></div><div class="ttdoc">Simple tensor object that stores elements in a consecutive chunk of memory.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00059">SimpleTensor.h:59</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_abdd3637f2bbde9d7d0cc0b7bbd8400bb"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#abdd3637f2bbde9d7d0cc0b7bbd8400bb">arm_compute::test::SimpleTensor::num_channels</a></div><div class="ttdeci">int num_channels() const override</div><div class="ttdoc">Number of channels of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00371">SimpleTensor.h:371</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ad4622eda610d53fb6852209f0213aeed"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ad4622eda610d53fb6852209f0213aeed">arm_compute::test::SimpleTensor::operator=</a></div><div class="ttdeci">SimpleTensor & operator=(SimpleTensor tensor)</div><div class="ttdoc">Create a deep copy of the given tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00301">SimpleTensor.h:301</a></div></div> |
| <div class="ttc" id="namespace_gemm_tuner_xhtml_a7aead736a07eaf25623ad7bfa1f0ee2d"><div class="ttname"><a href="namespace_gemm_tuner.xhtml#a7aead736a07eaf25623ad7bfa1f0ee2d">GemmTuner.type</a></div><div class="ttdeci">type</div><div class="ttdef"><b>Definition:</b> <a href="_gemm_tuner_8py_source.xhtml#l00527">GemmTuner.py:527</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3"><div class="ttname"><a href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">arm_compute::CLVersion::UNKNOWN</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_i_accessor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_i_accessor.xhtml">arm_compute::test::IAccessor</a></div><div class="ttdoc">Common interface to provide information and access to tensor like structures.</div><div class="ttdef"><b>Definition:</b> <a href="_i_accessor_8h_source.xhtml#l00037">IAccessor.h:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_aedcfdd4c3b92fe0d63b5463c7ad1d21e"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#aedcfdd4c3b92fe0d63b5463c7ad1d21e">arm_compute::test::SimpleTensor::num_elements</a></div><div class="ttdeci">int num_elements() const override</div><div class="ttdoc">Number of elements of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00407">SimpleTensor.h:407</a></div></div> |
| <div class="ttc" id="accumulate_8cl_xhtml_a00e540076dd545ad59ac7482f8cdf514"><div class="ttname"><a href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">accumulate</a></div><div class="ttdeci">__kernel void accumulate(__global uchar *input_ptr, uint input_stride_x, uint input_step_x, uint input_stride_y, uint input_step_y, uint input_offset_first_element_in_bytes, __global uchar *accu_ptr, uint accu_stride_x, uint accu_step_x, uint accu_stride_y, uint accu_step_y, uint accu_offset_first_element_in_bytes)</div><div class="ttdoc">This function accumulates an input image into output image.</div><div class="ttdef"><b>Definition:</b> <a href="accumulate_8cl_source.xhtml#l00041">accumulate.cl:41</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a5f5b6c4337eac9e2e0046ca2304d80dc"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">arm_compute::test::validation::data_type</a></div><div class="ttdeci">data_type</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_arithmetic_addition_8cpp_source.xhtml#l00138">ArithmeticAddition.cpp:138</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml_ac74736e3863207232a23b7181c1d0f44"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#ac74736e3863207232a23b7181c1d0f44">arm_compute::test::SimpleTensor::quantization_info</a></div><div class="ttdeci">QuantizationInfo quantization_info() const override</div><div class="ttdoc">Quantization info in case of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00333">SimpleTensor.h:333</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#l00075">Types.h:75</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a735a025fce26c1ef147b54426df18181"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a735a025fce26c1ef147b54426df18181">arm_compute::test::validation::padding</a></div><div class="ttdeci">const PaddingSize padding</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00113">AbsoluteDifference.cpp:113</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0">arm_compute::DataLayout</a></div><div class="ttdeci">DataLayout</div><div class="ttdoc">[DataLayout enum definition]</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00117">Types.h:117</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_simple_tensor_xhtml_a4ae7e1f6885eb47c11062cc74e6a6e19"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml#a4ae7e1f6885eb47c11062cc74e6a6e19">arm_compute::test::SimpleTensor::data</a></div><div class="ttdeci">const T * data() const</div><div class="ttdoc">Constant pointer to the underlying buffer.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00419">SimpleTensor.h:419</a></div></div> |
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