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| <a href="_helpers_8inl.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2016-2019 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">#include "<a class="code" href="_error_8h.xhtml">arm_compute/core/Error.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include "<a class="code" href="_validate_8h.xhtml">arm_compute/core/Validate.h</a>"</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 <cmath></span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include <numeric></span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> {</div><div class="line"><a name="l00032"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#ab7b3af731907e85fcaf72555c446176b"> 32</a></span> <span class="keyword">inline</span> uint8_t <a class="code" href="namespacearm__compute.xhtml#ab7b3af731907e85fcaf72555c446176b">pixel_area_c1u8_clamp</a>(<span class="keyword">const</span> uint8_t *first_pixel_ptr, <span class="keywordtype">size_t</span> stride, <span class="keywordtype">size_t</span> width, <span class="keywordtype">size_t</span> height, <span class="keywordtype">float</span> wr, <span class="keywordtype">float</span> hr, <span class="keywordtype">int</span> x, <span class="keywordtype">int</span> y)</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>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(first_pixel_ptr == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="comment">// Calculate sampling position</span></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordtype">float</span> in_x = (x + 0.5f) * wr - 0.5f;</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordtype">float</span> in_y = (y + 0.5f) * hr - 0.5f;</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="comment">// Get bounding box offsets</span></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">int</span> x_from = std::floor(x * wr - 0.5f - in_x);</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordtype">int</span> y_from = std::floor(y * hr - 0.5f - in_y);</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="keywordtype">int</span> x_to = std::ceil((x + 1) * wr - 0.5f - in_x);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordtype">int</span> y_to = std::ceil((y + 1) * hr - 0.5f - in_y);</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="comment">// Clamp position to borders</span></div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  in_x = std::max(-1.f, std::min(in_x, static_cast<float>(width)));</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  in_y = std::max(-1.f, std::min(in_y, static_cast<float>(height)));</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="comment">// Clamp bounding box offsets to borders</span></div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  x_from = ((in_x + x_from) < -1) ? -1 : x_from;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  y_from = ((in_y + y_from) < -1) ? -1 : y_from;</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  x_to = ((in_x + x_to) > width) ? (width - in_x) : x_to;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  y_to = ((in_y + y_to) > height) ? (height - in_y) : y_to;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span> </div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">// Get pixel index</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> xi = std::floor(in_x);</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> yi = std::floor(in_y);</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="comment">// Bounding box elements in each dimension</span></div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> x_elements = (x_to - x_from + 1);</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> y_elements = (y_to - y_from + 1);</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(x_elements == 0 || y_elements == 0);</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="comment">// Sum pixels in area</span></div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordtype">int</span> <a class="code" href="reduction__operation_8cl.xhtml#ab0df00f5333da51860deb93deb44a782">sum</a> = 0;</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> j = yi + y_from, je = yi + y_to; j <= je; ++j)</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  {</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">const</span> uint8_t *ptr = first_pixel_ptr + j * stride + xi + x_from;</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <a class="code" href="reduction__operation_8cl.xhtml#ab0df00f5333da51860deb93deb44a782">sum</a> = <a class="code" href="accumulate_8cl.xhtml#a00e540076dd545ad59ac7482f8cdf514">std::accumulate</a>(ptr, ptr + x_elements, <a class="code" href="reduction__operation_8cl.xhtml#ab0df00f5333da51860deb93deb44a782">sum</a>);</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  }</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">// Return average</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordflow">return</span> <a class="code" href="reduction__operation_8cl.xhtml#ab0df00f5333da51860deb93deb44a782">sum</a> / (x_elements * y_elements);</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> }</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="keyword">template</span> <<span class="keywordtype">size_t</span> dimension></div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="keyword">struct </span>IncrementIterators</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> {</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> T, <span class="keyword">typename</span>... Ts></div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keyword">static</span> <span class="keywordtype">void</span> unroll(T &&it, Ts &&... iterators)</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  {</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keyword">auto</span> increment = [](T && it)</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  {</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  it.increment(dimension);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  };</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <a class="code" href="namespacearm__compute_1_1utility.xhtml#a067ebd28103d827b6ec17032e2344064">utility::for_each</a>(increment, std::forward<T>(it), std::forward<Ts>(iterators)...);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  }</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keyword">static</span> <span class="keywordtype">void</span> unroll()</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  {</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="comment">// End of recursion</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  }</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span> };</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span> </div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> <span class="keyword">template</span> <<span class="keywordtype">size_t</span> dim></div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="keyword">struct </span>ForEachDimension</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> {</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> L, <span class="keyword">typename</span>... Ts></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keyword">static</span> <span class="keywordtype">void</span> unroll(<span class="keyword">const</span> Window &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>, Coordinates &<span class="keywordtype">id</span>, L &&lambda_function, Ts &&... iterators)</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  {</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keyword">const</span> <span class="keyword">auto</span> &d = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>[dim - 1];</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordflow">for</span>(<span class="keyword">auto</span> v = d.start(); v < d.end(); v += d.step(), IncrementIterators < dim - 1 >::unroll(iterators...))</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  {</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  <span class="keywordtype">id</span>.set(dim - 1, v);</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  ForEachDimension < dim - 1 >::unroll(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>, <span class="keywordtype">id</span>, lambda_function, iterators...);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  }</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  }</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> };</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="keyword">struct </span>ForEachDimension<0></div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span> {</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> L, <span class="keyword">typename</span>... Ts></div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="keyword">static</span> <span class="keywordtype">void</span> unroll(<span class="keyword">const</span> Window &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>, Coordinates &<span class="keywordtype">id</span>, L &&lambda_function, Ts &&... iterators)</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  {</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  lambda_function(<span class="keywordtype">id</span>);</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  }</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span> };</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="keyword">template</span> <<span class="keyword">typename</span> L, <span class="keyword">typename</span>... Ts></div><div class="line"><a name="l00122"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#a5002bf7ec46d52971f9526e94172cfee"> 122</a></span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute.xhtml#a5002bf7ec46d52971f9526e94172cfee">execute_window_loop</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>, L &&lambda_function, Ts &&... iterators)</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> {</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>.validate();</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span> </div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classarm__compute_1_1_dimensions.xhtml#a1b67d5b720119d50faa286c774579ecc">Coordinates::num_max_dimensions</a>; ++i)</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  {</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>[i].<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a75b73e17c4ebe901e44af3b2b9846ab3">step</a>() == 0);</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  }</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span> </div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> id;</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  ForEachDimension<Coordinates::num_max_dimensions>::unroll(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>, <span class="keywordtype">id</span>, std::forward<L>(lambda_function), std::forward<Ts>(iterators)...);</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span> }</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span> </div><div class="line"><a name="l00135"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_iterator.xhtml#a45381773d6cba2ad9e9d2d04515fa40b"> 135</a></span> <span class="keyword">inline</span> constexpr <a class="code" href="classarm__compute_1_1_iterator.xhtml#a45381773d6cba2ad9e9d2d04515fa40b">Iterator::Iterator</a>()</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  : _ptr(nullptr), _dims()</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span> {</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> }</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span> </div><div class="line"><a name="l00140"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_iterator.xhtml#a92d6469b972ef1e52b55b1ad7da70b02"> 140</a></span> <span class="keyword">inline</span> <a class="code" href="classarm__compute_1_1_iterator.xhtml#a45381773d6cba2ad9e9d2d04515fa40b">Iterator::Iterator</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *tensor, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &win)</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  : <a class="code" href="classarm__compute_1_1_iterator.xhtml">Iterator</a>()</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span> {</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(tensor == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(tensor-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>() == <span class="keyword">nullptr</span>);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span> </div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a> = tensor-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>();</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_strides.xhtml">Strides</a> &strides = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>->strides_in_bytes();</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span> </div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  _ptr = tensor-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">buffer</a>() + <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>->offset_first_element_in_bytes();</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="comment">//Initialize the stride for each dimension and calculate the position of the first element of the iteration:</span></div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 0; n < <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>->num_dimensions(); ++n)</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  {</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  _dims[n]._stride = win[n].step() * strides[n];</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  std::get<0>(_dims)._dim_start += strides[n] * win[n].start();</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  }</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="comment">//Copy the starting point to all the dimensions:</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 1; n < <a class="code" href="classarm__compute_1_1_dimensions.xhtml#a1b67d5b720119d50faa286c774579ecc">Coordinates::num_max_dimensions</a>; ++n)</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  {</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  _dims[n]._dim_start = std::get<0>(_dims)._dim_start;</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  }</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span> </div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <a class="code" href="_validate_8h.xhtml#af5084ef537306d09b1ef82aed5d1f63f">ARM_COMPUTE_ERROR_ON_WINDOW_DIMENSIONS_GTE</a>(win, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>->num_dimensions());</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> }</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_iterator.xhtml#a6e507a84d19ad08bb0f7fc1558ec429a"> 167</a></span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_iterator.xhtml#a6e507a84d19ad08bb0f7fc1558ec429a">Iterator::increment</a>(<span class="keyword">const</span> <span class="keywordtype">size_t</span> dimension)</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> {</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(dimension >= <a class="code" href="classarm__compute_1_1_dimensions.xhtml#a1b67d5b720119d50faa286c774579ecc">Coordinates::num_max_dimensions</a>);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  _dims[dimension]._dim_start += _dims[dimension]._stride;</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span> </div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 0; n < dimension; ++n)</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  {</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  _dims[n]._dim_start = _dims[dimension]._dim_start;</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  }</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span> }</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div><div class="line"><a name="l00179"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_iterator.xhtml#a7d48061a9abb9959505f167fb02e53e1"> 179</a></span> <span class="keyword">inline</span> constexpr <span class="keywordtype">int</span> <a class="code" href="classarm__compute_1_1_iterator.xhtml#a7d48061a9abb9959505f167fb02e53e1">Iterator::offset</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> <span class="keyword"></span>{</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keywordflow">return</span> _dims.at(0)._dim_start;</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> }</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> </div><div class="line"><a name="l00184"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_iterator.xhtml#ab260e292b1df3944bc1d55a9b2301e41"> 184</a></span> <span class="keyword">inline</span> constexpr uint8_t *<a class="code" href="classarm__compute_1_1_iterator.xhtml#ab260e292b1df3944bc1d55a9b2301e41">Iterator::ptr</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> <span class="keyword"></span>{</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="keywordflow">return</span> _ptr + _dims.at(0)._dim_start;</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> }</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div><div class="line"><a name="l00189"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_iterator.xhtml#a599f5025b7e6b8bfead740a88e56d5bc"> 189</a></span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_iterator.xhtml#a599f5025b7e6b8bfead740a88e56d5bc">Iterator::reset</a>(<span class="keyword">const</span> <span class="keywordtype">size_t</span> dimension)</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span> {</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(dimension >= <a class="code" href="classarm__compute_1_1_dimensions.xhtml#a1b67d5b720119d50faa286c774579ecc">Coordinates::num_max_dimensions</a> - 1);</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> </div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  _dims[dimension]._dim_start = _dims[dimension + 1]._dim_start;</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span> </div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> n = 0; n < dimension; ++n)</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  {</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  _dims[n]._dim_start = _dims[dimension]._dim_start;</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  }</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span> }</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div><div class="line"><a name="l00201"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce"> 201</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>,</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keyword">const</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">shape</a>,</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keywordtype">int</span> num_channels,</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <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>,</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> quantization_info)</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span> {</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.tensor_shape().total_size() == 0)</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  {</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.set_data_type(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>);</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.set_num_channels(num_channels);</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.set_tensor_shape(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.set_quantization_info(quantization_info);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  }</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span> }</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span> </div><div class="line"><a name="l00219"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#a5844c8e025388ddd8c3afc5c3f7a3256"> 219</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> &info_sink, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> &info_source)</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span> {</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <span class="keywordflow">if</span>(info_sink.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>().<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a0fdcb923dfd4c74858cc2bc326321efb">total_size</a>() == 0)</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>  info_sink.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a9ebcdce876b4cd07736afa47d50154de">set_data_type</a>(info_source.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>());</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  info_sink.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#aaf74be25e2392705f29352ffaa4b1f9d">set_num_channels</a>(info_source.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#ad7829ae79223ab87f9da4c0bd7d229ba">num_channels</a>());</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  info_sink.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a12a4f1190952613e36b44846962e26bb">set_tensor_shape</a>(info_source.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>());</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  info_sink.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a575d37eaf8a905c8ca3c0250757c2b81">set_quantization_info</a>(info_source.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>());</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  info_sink.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#abb9481fe056b9749f9b4c08db101cc15">set_data_layout</a>(info_source.<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>());</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  }</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> </div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> }</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> </div><div class="line"><a name="l00234"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#a9d1a839c51134b2ae171a2264c541b6f"> 234</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute.xhtml#a9d1a839c51134b2ae171a2264c541b6f">set_shape_if_empty</a>(<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <span class="keyword">const</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">shape</a>)</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>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.tensor_shape().total_size() == 0)</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  {</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.set_tensor_shape(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>);</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  }</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> </div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> }</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span> </div><div class="line"><a name="l00245"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#a8076ba239b6681067b6cfea7f773a39f"> 245</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute.xhtml#a8076ba239b6681067b6cfea7f773a39f">set_format_if_unknown</a>(<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format)</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> {</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.data_type() == <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataType::UNKNOWN</a>)</div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  {</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.set_format(format);</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  }</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span> </div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> }</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span> </div><div class="line"><a name="l00256"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#ad19446be52c2c162fa678b9ae236f445"> 256</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute.xhtml#ad19446be52c2c162fa678b9ae236f445">set_data_type_if_unknown</a>(<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</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>)</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span> {</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.data_type() == <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataType::UNKNOWN</a>)</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  {</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.set_data_type(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>);</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  }</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span> </div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span> }</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> </div><div class="line"><a name="l00267"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#aafd98bfd4651f36d691ddd2631a6e5a0"> 267</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute.xhtml#aafd98bfd4651f36d691ddd2631a6e5a0">set_data_layout_if_unknown</a>(<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <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="l00268"></a><span class="lineno"> 268</span> {</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.data_layout() == <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataLayout::UNKNOWN</a>)</div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  {</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.set_data_layout(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a>);</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keywordflow">return</span> <span class="keyword">true</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> </div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span> }</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span> </div><div class="line"><a name="l00278"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#a75509469ec2689ec143f4a37bbcb4437"> 278</a></span> <span class="keyword">inline</span> <span class="keywordtype">bool</span> <a class="code" href="namespacearm__compute.xhtml#a75509469ec2689ec143f4a37bbcb4437">set_quantization_info_if_empty</a>(<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> quantization_info)</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> {</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.quantization_info().empty() && (<a class="code" href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">is_data_type_quantized_asymmetric</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.data_type())))</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  {</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.set_quantization_info(quantization_info);</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</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="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span> }</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> </div><div class="line"><a name="l00289"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#ad34f2150f1c9f8a3ecb7298162124e5d"> 289</a></span> <span class="keyword">inline</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> <a class="code" href="namespacearm__compute.xhtml#ad34f2150f1c9f8a3ecb7298162124e5d">index2coords</a>(<span class="keyword">const</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">shape</a>, <span class="keywordtype">int</span> index)</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span> {</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keywordtype">int</span> num_elements = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.total_size();</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> </div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(index < 0 || index >= num_elements, <span class="stringliteral">"Index has to be in [0, num_elements]!"</span>);</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(num_elements == 0, <span class="stringliteral">"Cannot create coordinate from empty shape!"</span>);</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>  <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> coord{ 0 };</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> </div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> d = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.num_dimensions() - 1; d >= 0; --d)</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>  num_elements /= <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>[d];</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  coord.set(d, index / num_elements);</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  index %= num_elements;</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  }</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> coord;</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"><a class="line" href="namespacearm__compute.xhtml#ad95e1c14c3007ca18950bf8f4c5a5c93"> 308</a></span> <span class="keyword">inline</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute.xhtml#ad95e1c14c3007ca18950bf8f4c5a5c93">coords2index</a>(<span class="keyword">const</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">shape</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="l00309"></a><span class="lineno"> 309</span> {</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordtype">int</span> num_elements = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>.total_size();</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(num_elements);</div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(num_elements == 0, <span class="stringliteral">"Cannot create linear index from empty shape!"</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="keywordtype">int</span> index = 0;</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="keywordtype">int</span> stride = 1;</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> </div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> d = 0; d < coord.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>(); ++d)</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>  index += coord[d] * stride;</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  stride *= <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>[d];</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  }</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span> </div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keywordflow">return</span> index;</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"><a class="line" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db"> 326</a></span> <span class="keyword">inline</span> <span class="keywordtype">size_t</span> <a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(<span class="keyword">const</span> <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>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02">DataLayoutDimension</a> data_layout_dimension)</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> {</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataLayout::UNKNOWN</a>, <span class="stringliteral">"Cannot retrieve the dimension index for an unknown layout!"</span>);</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="comment">/* Return the index based on the data layout</span></div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> <span class="comment"> * [N C H W]</span></div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> <span class="comment"> * [3 2 1 0]</span></div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span> <span class="comment"> * [N H W C]</span></div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> <span class="comment"> */</span></div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordflow">switch</span>(data_layout_dimension)</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  {</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">DataLayoutDimension::CHANNEL</a>:</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordflow">return</span> (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? 2 : 0;</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>:</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keywordflow">return</span> (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? 1 : 2;</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>:</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <span class="keywordflow">return</span> (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? 0 : 1;</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a628bcf7e10fc1c2a984f379a1ec3393a">DataLayoutDimension::BATCHES</a>:</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="keywordflow">return</span> 3;</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Data layout index not supported!"</span>);</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  }</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> }</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span> </div><div class="line"><a name="l00355"></a><span class="lineno"><a class="line" href="namespacearm__compute.xhtml#ab86b0b430468cbf4a5e6e093088024c9"> 355</a></span> <span class="keyword">inline</span> <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02">DataLayoutDimension</a> <a class="code" href="namespacearm__compute.xhtml#ab86b0b430468cbf4a5e6e093088024c9">get_index_data_layout_dimension</a>(<span class="keyword">const</span> <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>, <span class="keyword">const</span> <span class="keywordtype">size_t</span> index)</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>  <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#a3a440b3893fa10608d4428958be1c52ea696b031073e74bf2cb98e5ef201d4aa3">DataLayout::UNKNOWN</a>, <span class="stringliteral">"Cannot retrieve the dimension index for an unknown layout!"</span>);</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> </div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="comment">/* Return the index based on the data layout</span></div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span> <span class="comment"> * [N C H W]</span></div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span> <span class="comment"> * [3 2 1 0]</span></div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span> <span class="comment"> * [N H W C]</span></div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> <span class="comment"> */</span></div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="keywordflow">switch</span>(index)</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">case</span> 0:</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="keywordflow">return</span> (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a> : <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">DataLayoutDimension::CHANNEL</a>;</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keywordflow">case</span> 1:</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="keywordflow">return</span> (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a> : <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>;</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keywordflow">case</span> 2:</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keywordflow">return</span> (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acf5f12bbab64dd614bd8220c97fe484f">data_layout</a> == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>) ? <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">DataLayoutDimension::CHANNEL</a> : <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>;</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordflow">case</span> 3:</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a628bcf7e10fc1c2a984f379a1ec3393a">DataLayoutDimension::BATCHES</a>;</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Index value not supported!"</span>);</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  }</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span> }</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> } <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00261">Error.h:261</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_aaf74be25e2392705f29352ffaa4b1f9d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#aaf74be25e2392705f29352ffaa4b1f9d">arm_compute::ITensorInfo::set_num_channels</a></div><div class="ttdeci">virtual ITensorInfo & set_num_channels(int num_channels)=0</div><div class="ttdoc">Set the number of channels to the specified value.</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="namespacearm__compute_1_1test_1_1validation_xhtml_a1a367830ae09bf6138df822888ec1d71"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">arm_compute::test::validation::w</a></div><div class="ttdeci">SimpleTensor< float > w</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_2_d_f_t_8cpp_source.xhtml#l00156">DFT.cpp:156</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="namespacearm__compute_xhtml_ad34f2150f1c9f8a3ecb7298162124e5d"><div class="ttname"><a href="namespacearm__compute.xhtml#ad34f2150f1c9f8a3ecb7298162124e5d">arm_compute::index2coords</a></div><div class="ttdeci">Coordinates index2coords(const TensorShape &shape, int index)</div><div class="ttdoc">Convert a linear index into n-dimensional coordinates.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00289">Helpers.inl:289</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_iterator_xhtml_a6e507a84d19ad08bb0f7fc1558ec429a"><div class="ttname"><a href="classarm__compute_1_1_iterator.xhtml#a6e507a84d19ad08bb0f7fc1558ec429a">arm_compute::Iterator::increment</a></div><div class="ttdeci">void increment(size_t dimension)</div><div class="ttdoc">Increment the iterator along the specified dimension of the step value associated to the dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00167">Helpers.inl:167</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a12a4f1190952613e36b44846962e26bb"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a12a4f1190952613e36b44846962e26bb">arm_compute::ITensorInfo::set_tensor_shape</a></div><div class="ttdeci">virtual ITensorInfo & set_tensor_shape(const TensorShape &shape)=0</div><div class="ttdoc">Set the shape of an already initialized tensor.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02">arm_compute::DataLayoutDimension</a></div><div class="ttdeci">DataLayoutDimension</div><div class="ttdoc">[DataLayout enum definition]</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00123">Types.h:123</a></div></div> |
| <div class="ttc" id="reduction__operation_8cl_xhtml_ab0df00f5333da51860deb93deb44a782"><div class="ttname"><a href="reduction__operation_8cl.xhtml#ab0df00f5333da51860deb93deb44a782">sum</a></div><div class="ttdeci">DATA_TYPE sum(__global const DATA_TYPE *input)</div><div class="ttdoc">Calculate sum of a vector.</div><div class="ttdef"><b>Definition:</b> <a href="reduction__operation_8cl_source.xhtml#l00065">reduction_operation.cl:65</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">arm_compute::DataLayoutDimension::HEIGHT</a></div><div class="ttdoc">height</div></div> |
| <div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00337">Error.h:337</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml">arm_compute::ITensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_info_8h_source.xhtml#l00040">ITensorInfo.h:40</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_aafd98bfd4651f36d691ddd2631a6e5a0"><div class="ttname"><a href="namespacearm__compute.xhtml#aafd98bfd4651f36d691ddd2631a6e5a0">arm_compute::set_data_layout_if_unknown</a></div><div class="ttdeci">bool set_data_layout_if_unknown(ITensorInfo &info, DataLayout data_layout)</div><div class="ttdoc">Set the data layout to the specified value if the current data layout is unknown.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00267">Helpers.inl:267</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml">arm_compute::ITensor</a></div><div class="ttdoc">Interface for NEON tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00036">ITensor.h:36</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad19446be52c2c162fa678b9ae236f445"><div class="ttname"><a href="namespacearm__compute.xhtml#ad19446be52c2c162fa678b9ae236f445">arm_compute::set_data_type_if_unknown</a></div><div class="ttdeci">bool set_data_type_if_unknown(ITensorInfo &info, DataType data_type)</div><div class="ttdoc">Set the data type and number of channels to the specified value if the current data type is unknown.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00256">Helpers.inl:256</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) 2017-2018 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a47be6fa38308d0003c25b60b7dbc45ce"><div class="ttname"><a href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">arm_compute::auto_init_if_empty</a></div><div class="ttdeci">bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())</div><div class="ttdoc">Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00201">Helpers.inl:201</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a75b73e17c4ebe901e44af3b2b9846ab3"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a75b73e17c4ebe901e44af3b2b9846ab3">arm_compute::test::validation::step</a></div><div class="ttdeci">const int step</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_select_8cpp_source.xhtml#l00172">Select.cpp:172</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#l00066">QuantizationInfo.h:66</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a6dc630a6ae9cc063b3924bcea8dee9d6"><div class="ttname"><a href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(...)</div><div class="ttdoc">To avoid unused variables warnings.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00160">Error.h:160</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape & tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_abb9481fe056b9749f9b4c08db101cc15"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#abb9481fe056b9749f9b4c08db101cc15">arm_compute::ITensorInfo::set_data_layout</a></div><div class="ttdeci">virtual ITensorInfo & set_data_layout(const DataLayout &data_layout)=0</div><div class="ttdoc">Set the data layout of the tensor.</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#l00052">Types.h:52</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_iterator_xhtml_a7d48061a9abb9959505f167fb02e53e1"><div class="ttname"><a href="classarm__compute_1_1_iterator.xhtml#a7d48061a9abb9959505f167fb02e53e1">arm_compute::Iterator::offset</a></div><div class="ttdeci">constexpr int offset() const</div><div class="ttdoc">Return the offset in bytes from the first element to the current position of the iterator.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00179">Helpers.inl:179</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item.</div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_ab988210662dbd3bf32fd563c7dd1bdbf"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">arm_compute::ITensor::buffer</a></div><div class="ttdeci">virtual uint8_t * buffer() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return a pointer to CPU memory.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_a0fdcb923dfd4c74858cc2bc326321efb"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a0fdcb923dfd4c74858cc2bc326321efb">arm_compute::TensorShape::total_size</a></div><div class="ttdeci">size_t total_size() const</div><div class="ttdoc">Collapses all dimensions to a single linear total size.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00171">TensorShape.h:171</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad95e1c14c3007ca18950bf8f4c5a5c93"><div class="ttname"><a href="namespacearm__compute.xhtml#ad95e1c14c3007ca18950bf8f4c5a5c93">arm_compute::coords2index</a></div><div class="ttdeci">int coords2index(const TensorShape &shape, const Coordinates &coord)</div><div class="ttdoc">Convert n-dimensional coordinates into a linear index.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00308">Helpers.inl:308</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_iterator_xhtml_ab260e292b1df3944bc1d55a9b2301e41"><div class="ttname"><a href="classarm__compute_1_1_iterator.xhtml#ab260e292b1df3944bc1d55a9b2301e41">arm_compute::Iterator::ptr</a></div><div class="ttdeci">constexpr uint8_t * ptr() const</div><div class="ttdoc">Return a pointer to the current pixel.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00184">Helpers.inl:184</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a575d37eaf8a905c8ca3c0250757c2b81"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a575d37eaf8a905c8ca3c0250757c2b81">arm_compute::ITensorInfo::set_quantization_info</a></div><div class="ttdeci">virtual ITensorInfo & set_quantization_info(const QuantizationInfo &quantization_info)=0</div><div class="ttdoc">Set the quantization settings (scale and offset) of the tensor.</div></div> |
| <div class="ttc" id="_error_8h_xhtml"><div class="ttname"><a href="_error_8h.xhtml">Error.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">arm_compute::DataLayoutDimension::CHANNEL</a></div><div class="ttdoc">channel</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab86b0b430468cbf4a5e6e093088024c9"><div class="ttname"><a href="namespacearm__compute.xhtml#ab86b0b430468cbf4a5e6e093088024c9">arm_compute::get_index_data_layout_dimension</a></div><div class="ttdeci">DataLayoutDimension get_index_data_layout_dimension(const DataLayout data_layout, const size_t index)</div><div class="ttdoc">Get the DataLayoutDimension of a given index and layout.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00355">Helpers.inl:355</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a9ebcdce876b4cd07736afa47d50154de"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a9ebcdce876b4cd07736afa47d50154de">arm_compute::ITensorInfo::set_data_type</a></div><div class="ttdeci">virtual ITensorInfo & set_data_type(DataType data_type)=0</div><div class="ttdoc">Set the data type to the specified value.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a3f3e1a3200223e6a304a533b1016e749"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">arm_compute::ITensorInfo::quantization_info</a></div><div class="ttdeci">virtual QuantizationInfo quantization_info() const =0</div><div class="ttdoc">Get the quantization settings (scale and offset) of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_iterator_xhtml_a45381773d6cba2ad9e9d2d04515fa40b"><div class="ttname"><a href="classarm__compute_1_1_iterator.xhtml#a45381773d6cba2ad9e9d2d04515fa40b">arm_compute::Iterator::Iterator</a></div><div class="ttdeci">constexpr Iterator()</div><div class="ttdoc">Default constructor to create an empty iterator.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00135">Helpers.inl:135</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02a628bcf7e10fc1c2a984f379a1ec3393a"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a628bcf7e10fc1c2a984f379a1ec3393a">arm_compute::DataLayoutDimension::BATCHES</a></div><div class="ttdoc">batches</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="_validate_8h_xhtml_af5084ef537306d09b1ef82aed5d1f63f"><div class="ttname"><a href="_validate_8h.xhtml#af5084ef537306d09b1ef82aed5d1f63f">ARM_COMPUTE_ERROR_ON_WINDOW_DIMENSIONS_GTE</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_WINDOW_DIMENSIONS_GTE(w, md)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00263">Validate.h:263</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1utility_xhtml_a067ebd28103d827b6ec17032e2344064"><div class="ttname"><a href="namespacearm__compute_1_1utility.xhtml#a067ebd28103d827b6ec17032e2344064">arm_compute::utility::for_each</a></div><div class="ttdeci">void for_each(F &&)</div><div class="ttdoc">Base case of for_each.</div><div class="ttdef"><b>Definition:</b> <a href="_utility_8h_source.xhtml#l00093">Utility.h:93</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a14f46283f316e7f0fad301d5c1507e9f"><div class="ttname"><a href="namespacearm__compute.xhtml#a14f46283f316e7f0fad301d5c1507e9f">arm_compute::is_data_type_quantized_asymmetric</a></div><div class="ttdeci">bool is_data_type_quantized_asymmetric(DataType dt)</div><div class="ttdoc">Check if a given data type is of asymmetric quantized type.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_utils_8h_source.xhtml#l01030">Utils.h:1030</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_strides_xhtml"><div class="ttname"><a href="classarm__compute_1_1_strides.xhtml">arm_compute::Strides</a></div><div class="ttdoc">Strides of an item in bytes.</div><div class="ttdef"><b>Definition:</b> <a href="_strides_8h_source.xhtml#l00037">Strides.h:37</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab7b3af731907e85fcaf72555c446176b"><div class="ttname"><a href="namespacearm__compute.xhtml#ab7b3af731907e85fcaf72555c446176b">arm_compute::pixel_area_c1u8_clamp</a></div><div class="ttdeci">uint8_t pixel_area_c1u8_clamp(const uint8_t *first_pixel_ptr, size_t stride, size_t width, size_t height, float wr, float hr, int x, int y)</div><div class="ttdoc">Return the pixel at (x,y) using area interpolation by clamping when out of borders.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00032">Helpers.inl:32</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_iterator_xhtml_a599f5025b7e6b8bfead740a88e56d5bc"><div class="ttname"><a href="classarm__compute_1_1_iterator.xhtml#a599f5025b7e6b8bfead740a88e56d5bc">arm_compute::Iterator::reset</a></div><div class="ttdeci">void reset(size_t dimension)</div><div class="ttdoc">Move the iterator back to the beginning of the specified dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00189">Helpers.inl:189</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_1_dimensions_xhtml_a80a5f2d6e3a697c9aad893a3b4242615"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">arm_compute::Dimensions::num_dimensions</a></div><div class="ttdeci">unsigned int num_dimensions() const</div><div class="ttdoc">Returns the effective dimensionality of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00122">Dimensions.h:122</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a9d1a839c51134b2ae171a2264c541b6f"><div class="ttname"><a href="namespacearm__compute.xhtml#a9d1a839c51134b2ae171a2264c541b6f">arm_compute::set_shape_if_empty</a></div><div class="ttdeci">bool set_shape_if_empty(ITensorInfo &info, const TensorShape &shape)</div><div class="ttdoc">Set the shape to the specified value if the current assignment is empty.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00234">Helpers.inl:234</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_xhtml_a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">arm_compute::DataLayoutDimension::WIDTH</a></div><div class="ttdoc">width</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a5002bf7ec46d52971f9526e94172cfee"><div class="ttname"><a href="namespacearm__compute.xhtml#a5002bf7ec46d52971f9526e94172cfee">arm_compute::execute_window_loop</a></div><div class="ttdeci">void execute_window_loop(const Window &w, L &&lambda_function, Ts &&... iterators)</div><div class="ttdoc">Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00122">Helpers.inl:122</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a8076ba239b6681067b6cfea7f773a39f"><div class="ttname"><a href="namespacearm__compute.xhtml#a8076ba239b6681067b6cfea7f773a39f">arm_compute::set_format_if_unknown</a></div><div class="ttdeci">bool set_format_if_unknown(ITensorInfo &info, Format format)</div><div class="ttdoc">Set the format, data type and number of channels to the specified value if the current data type is u...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00245">Helpers.inl:245</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#l00135">ArithmeticAddition.cpp:135</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a46e938020a3ac8c926d0590b7fe957db"><div class="ttname"><a href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">arm_compute::get_data_layout_dimension_index</a></div><div class="ttdeci">size_t get_data_layout_dimension_index(const DataLayout data_layout, const DataLayoutDimension data_layout_dimension)</div><div class="ttdoc">Get the index of the given dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00326">Helpers.inl:326</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a4f4125dba5283887b34f889b1c615c0c"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">arm_compute::test::validation::info</a></div><div class="ttdeci">info</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_convolution_layer_8cpp_source.xhtml#l00174">ConvolutionLayer.cpp:174</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a1b67d5b720119d50faa286c774579ecc"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a1b67d5b720119d50faa286c774579ecc">arm_compute::Dimensions< int >::num_max_dimensions</a></div><div class="ttdeci">static constexpr size_t num_max_dimensions</div><div class="ttdoc">Number of dimensions the tensor has.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00045">Dimensions.h:45</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_iterator_xhtml"><div class="ttname"><a href="classarm__compute_1_1_iterator.xhtml">arm_compute::Iterator</a></div><div class="ttdoc">Iterator updated by execute_window_loop for each window element.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00318">Helpers.h:318</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#l00074">Types.h:74</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#l00114">Types.h:114</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a75509469ec2689ec143f4a37bbcb4437"><div class="ttname"><a href="namespacearm__compute.xhtml#a75509469ec2689ec143f4a37bbcb4437">arm_compute::set_quantization_info_if_empty</a></div><div class="ttdeci">bool set_quantization_info_if_empty(ITensorInfo &info, QuantizationInfo quantization_info)</div><div class="ttdoc">Set the quantization info to the specified value if the current quantization info is empty and the da...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00278">Helpers.inl:278</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_window_xhtml"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml">arm_compute::Window</a></div><div class="ttdoc">Describe a multidimensional execution window.</div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00039">Window.h:39</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_ad7829ae79223ab87f9da4c0bd7d229ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#ad7829ae79223ab87f9da4c0bd7d229ba">arm_compute::ITensorInfo::num_channels</a></div><div class="ttdeci">virtual size_t num_channels() const =0</div><div class="ttdoc">The number of channels for each tensor element.</div></div> |
| <div class="ttc" id="_validate_8h_xhtml"><div class="ttname"><a href="_validate_8h.xhtml">Validate.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a367b5090ab432bc7de2c32369e087ab1"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">arm_compute::ITensorInfo::data_layout</a></div><div class="ttdeci">virtual DataLayout data_layout() const =0</div><div class="ttdoc">Get the data layout of the tensor.</div></div> |
| <div class="ttc" id="_error_8h_xhtml_a5bbdcf574d3f5e412fa6a1117911e67b"><div class="ttname"><a href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond,...)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00328">Error.h:328</a></div></div> |
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