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<div class="title">PadLayer.cpp</div> </div>
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<a href="reference_2_pad_layer_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno"> 2</span>&#160;<span class="comment"> * Copyright (c) 2018-2019 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_pad_layer_8h.xhtml">PadLayer.h</a>&quot;</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span>&#160;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>&quot;</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_shape_calculator_8h.xhtml">arm_compute/core/utils/misc/ShapeCalculator.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tests_2validation_2_helpers_8h.xhtml">tests/validation/Helpers.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span>&#160;<span class="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>&#160;{</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>&#160;<span class="keyword">namespace </span>test</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>&#160;{</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>&#160;<span class="keyword">namespace </span>validation</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>&#160;{</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>&#160;<span class="keyword">namespace </span>reference</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>&#160;{</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T&gt;</div><div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1"> 39</a></span>&#160;<a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1">pad_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> &amp;paddings, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> const_value, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">PaddingMode</a> mode)</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>&#160;{</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>&#160; <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> dst_data_type = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.data_type();</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>&#160;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> orig_shape = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>.shape();</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>&#160;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>&#160; std::vector&lt;PaddingInfo&gt; paddings_extended = paddings;</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>&#160;</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>&#160; <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = paddings.size(); i &lt; <a class="code" href="classarm__compute_1_1_dimensions.xhtml#a1b67d5b720119d50faa286c774579ecc">TensorShape::num_max_dimensions</a>; ++i)</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>&#160; {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>&#160; paddings_extended.emplace_back(<a class="code" href="namespacearm__compute.xhtml#a669b5d3c5994f9ae3be31df9a1014297">PaddingInfo</a>{ 0, 0 });</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>&#160; }</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> padded_shape = <a class="code" href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a4e7f3187350db69156c1026860ace4e5">misc::shape_calculator::compute_padded_shape</a>(orig_shape, paddings);</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>&#160;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>&#160; <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;T&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>(padded_shape, dst_data_type);</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>&#160;</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>&#160; <span class="comment">// Reference algorithm: loop over the different dimension of the input.</span></div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>&#160; <span class="keyword">const</span> uint32_t num_elements = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>.num_elements();</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>&#160; <span class="keywordflow">for</span>(uint32_t idx = 0; idx &lt; num_elements; ++idx)</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>&#160; {</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> coord = <a class="code" href="namespacearm__compute_1_1test.xhtml#a24d8c0391cfa38e78969b6ad97c0ff09">index2coord</a>(padded_shape, idx);</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>&#160;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> i = coord.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#aa87f8fc26981b0f3228a78c83b95b802">x</a>();</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> j = coord.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#ac4a1050be02b20b3f791b9a483f3abe2">y</a>();</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> k = coord.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#abb29a685080e999c2a0cb874d2f7bb5a">z</a>();</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> l = coord[3];</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> m = coord[4];</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> n = coord[5];</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>&#160;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>&#160; <span class="keyword">const</span> std::array&lt;size_t, TensorShape::num_max_dimensions&gt; dims = { { 0, 1, 2, 3, 4, 5 } };</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>&#160; <span class="keyword">const</span> std::array&lt;size_t, TensorShape::num_max_dimensions&gt; coords = { { i, j, k, l, m, n } };</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>&#160; <span class="keyword">auto</span> is_padding_area = [&amp;](<span class="keywordtype">size_t</span> i)</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>&#160; {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>&#160; <span class="keywordflow">return</span> (coords[i] &lt; paddings_extended[i].first || coords[i] &gt; orig_shape[i] + paddings_extended[i].first - 1);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>&#160; };</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>&#160;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>&#160; <span class="keyword">auto</span> orig_coord_reflect = [&amp;](<span class="keywordtype">size_t</span> i)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>&#160; {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>&#160; <span class="keywordflow">if</span>(is_padding_area(i))</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>&#160; {</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>&#160; <span class="keywordflow">if</span>(coords[i] &lt; paddings_extended[i].first)</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>&#160; {</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>&#160; <span class="keywordflow">return</span> paddings_extended[i].first - coords[i];</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>&#160; }</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>&#160; {</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>&#160; <span class="keywordflow">return</span> 2 * orig_shape[i] + paddings_extended[i].first - 2 - coords[i];</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>&#160; }</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>&#160; }</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>&#160; <span class="keywordflow">return</span> coords[i] - paddings_extended[i].first;</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>&#160; };</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160;</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; <span class="keyword">auto</span> orig_coord_symm = [&amp;](<span class="keywordtype">size_t</span> i)</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; {</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; <span class="keywordflow">if</span>(is_padding_area(i))</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; {</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; <span class="keywordflow">if</span>(coords[i] &lt; paddings_extended[i].first)</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; {</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; <span class="keywordflow">return</span> paddings_extended[i].first - coords[i] - 1;</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; }</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; {</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; <span class="keywordflow">return</span> 2 * orig_shape[i] + paddings_extended[i].first - 1 - coords[i];</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; }</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; }</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160; <span class="keywordflow">return</span> coords[i] - paddings_extended[i].first;</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>&#160; };</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>&#160;</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>&#160; <span class="comment">// If the tuple [i,j,k,l,m] is in the padding area, then simply set the value</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>&#160; <span class="keywordflow">if</span>(std::any_of(dims.begin(), dims.end(), is_padding_area))</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>&#160; {</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>&#160; <span class="keywordflow">switch</span>(mode)</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>&#160; {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">PaddingMode::CONSTANT</a>:</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>&#160; const_value.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a66c4c1f8b1962d71162d7ac0b3ef65bc">get</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>[idx]);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91ae4f6a05f82ed398f984f4bc1a55838df">PaddingMode::REFLECT</a>:</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>&#160; {</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> orig_coords{ orig_coord_reflect(0),</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>&#160; orig_coord_reflect(1),</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>&#160; orig_coord_reflect(2),</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>&#160; orig_coord_reflect(3),</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>&#160; orig_coord_reflect(4),</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>&#160; orig_coord_reflect(5) };</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>&#160;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_src = <a class="code" href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">coord2index</a>(orig_shape, orig_coords);</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>[idx] = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>[idx_src];</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>&#160; }</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>&#160; <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a161b3d9016563aba9ac190fc02ada9bb">PaddingMode::SYMMETRIC</a>:</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>&#160; {</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> orig_coords{ orig_coord_symm(0),</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>&#160; orig_coord_symm(1),</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>&#160; orig_coord_symm(2),</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>&#160; orig_coord_symm(3),</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>&#160; orig_coord_symm(4),</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>&#160; orig_coord_symm(5) };</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_src = <a class="code" href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">coord2index</a>(orig_shape, orig_coords);</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>[idx] = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>[idx_src];</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>&#160; }</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>&#160; <span class="keywordflow">default</span>:</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>&#160; <a class="code" href="_error_8h.xhtml#a7cf8d8b669b8f7b05680230be30d60f4">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;Padding mode not supported.&quot;</span>);</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>&#160; <span class="keywordflow">break</span>;</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>&#160; }</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>&#160; }</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>&#160; <span class="keywordflow">else</span></div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>&#160; {</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>&#160; <span class="comment">// If the tuple[i,j,k,l,m] is not in the padding area, then copy the input into the output</span></div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>&#160;</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>&#160; <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> orig_coords</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>&#160; {</div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>&#160; i - paddings_extended[0].first,</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>&#160; j - paddings_extended[1].first,</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>&#160; k - paddings_extended[2].first,</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>&#160; l - paddings_extended[3].first,</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>&#160; m - paddings_extended[4].first,</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>&#160; n - paddings_extended[5].first</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>&#160; };</div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>&#160;</div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>&#160; <span class="keyword">const</span> <span class="keywordtype">size_t</span> idx_src = <a class="code" href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">coord2index</a>(orig_shape, orig_coords);</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>&#160; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>[idx] = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>[idx_src];</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>&#160; }</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>&#160; }</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>&#160;</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>&#160; <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">dst</a>;</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>&#160;}</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>&#160;</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1">pad_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;float&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> &amp;paddings, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> const_value = <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(), <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">PaddingMode</a> mode);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;half&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1">pad_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;half&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> &amp;paddings, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> const_value = <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(), <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">PaddingMode</a> mode);</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint8_t&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1">pad_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint8_t&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> &amp;paddings, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> const_value = <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(), <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">PaddingMode</a> mode);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;int8_t&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1">pad_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;int8_t&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> &amp;paddings, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> const_value = <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(), <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">PaddingMode</a> mode);</div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint16_t&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1">pad_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint16_t&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> &amp;paddings, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> const_value = <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(), <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">PaddingMode</a> mode);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;int16_t&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1">pad_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;int16_t&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> &amp;paddings, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> const_value = <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(), <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">PaddingMode</a> mode);</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint32_t&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1">pad_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;uint32_t&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> &amp;paddings, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> const_value = <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(), <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">PaddingMode</a> mode);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>&#160;<span class="keyword">template</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;int32_t&gt;</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1">pad_layer</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor&lt;int32_t&gt;</a> &amp;<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">src</a>, <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a> &amp;paddings, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> const_value = <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a>(), <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">PaddingMode</a> mode);</div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>&#160;} <span class="comment">// namespace reference</span></div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>&#160;} <span class="comment">// namespace validation</span></div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span>&#160;} <span class="comment">// namespace test</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>&#160;} <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1reference_xhtml_ab5901f29f666658b04856010acaeb0b1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1reference.xhtml#ab5901f29f666658b04856010acaeb0b1">arm_compute::test::validation::reference::pad_layer</a></div><div class="ttdeci">SimpleTensor&lt; T &gt; pad_layer(const SimpleTensor&lt; T &gt; &amp;src, const PaddingList &amp;paddings, const PixelValue const_value, const PaddingMode mode)</div><div class="ttdoc">Reference function to pad an ND tensor.</div><div class="ttdef"><b>Definition:</b> <a href="reference_2_pad_layer_8cpp_source.xhtml#l00039">PadLayer.cpp:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_pixel_value_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pixel_value.xhtml">arm_compute::PixelValue</a></div><div class="ttdoc">Class describing the value of a pixel for any image format.</div><div class="ttdef"><b>Definition:</b> <a href="_pixel_value_8h_source.xhtml#l00034">PixelValue.h:34</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_xhtml_ac1a1b012674e0f1de071a611391828ad"><div class="ttname"><a href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">arm_compute::PaddingList</a></div><div class="ttdeci">std::vector&lt; PaddingInfo &gt; PaddingList</div><div class="ttdoc">List of padding information.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00455">Types.h:455</a></div></div>
<div class="ttc" id="_error_8h_xhtml_a7cf8d8b669b8f7b05680230be30d60f4"><div class="ttname"><a href="_error_8h.xhtml#a7cf8d8b669b8f7b05680230be30d60f4">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(msg)</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#l00352">Error.h:352</a></div></div>
<div class="ttc" id="classarm__compute_1_1_pixel_value_xhtml_a66c4c1f8b1962d71162d7ac0b3ef65bc"><div class="ttname"><a href="classarm__compute_1_1_pixel_value.xhtml#a66c4c1f8b1962d71162d7ac0b3ef65bc">arm_compute::PixelValue::get</a></div><div class="ttdeci">void get(uint8_t &amp;v) const</div><div class="ttdoc">Interpret the pixel value as a U8.</div><div class="ttdef"><b>Definition:</b> <a href="_pixel_value_8h_source.xhtml#l00230">PixelValue.h:230</a></div></div>
<div class="ttc" id="tests_2validation_2_helpers_8h_xhtml"><div class="ttname"><a href="tests_2validation_2_helpers_8h.xhtml">Helpers.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a14d24d90ab4ba2956e92e27890ba4c91a161b3d9016563aba9ac190fc02ada9bb"><div class="ttname"><a href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a161b3d9016563aba9ac190fc02ada9bb">arm_compute::PaddingMode::SYMMETRIC</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2020 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a9be4cb7e6ee20063a4a10bc3abb750b9"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a9be4cb7e6ee20063a4a10bc3abb750b9">arm_compute::test::coord2index</a></div><div class="ttdeci">int coord2index(const TensorShape &amp;shape, const Coordinates &amp;coord)</div><div class="ttdoc">Linearise the given coordinate.</div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00485">Utils.h:485</a></div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_aa87f8fc26981b0f3228a78c83b95b802"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#aa87f8fc26981b0f3228a78c83b95b802">arm_compute::Dimensions::x</a></div><div class="ttdeci">T x() const</div><div class="ttdoc">Alias to access the size of the first dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00081">Dimensions.h:81</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a14d24d90ab4ba2956e92e27890ba4c91"><div class="ttname"><a href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91">arm_compute::PaddingMode</a></div><div class="ttdeci">PaddingMode</div><div class="ttdoc">Padding mode to use for PadLayer.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00165">Types.h:165</a></div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_abb29a685080e999c2a0cb874d2f7bb5a"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#abb29a685080e999c2a0cb874d2f7bb5a">arm_compute::Dimensions::z</a></div><div class="ttdeci">T z() const</div><div class="ttdoc">Alias to access the size of the third dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00091">Dimensions.h:91</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="_pad_layer_8h_xhtml"><div class="ttname"><a href="_pad_layer_8h.xhtml">PadLayer.h</a></div></div>
<div class="ttc" id="_shape_calculator_8h_xhtml"><div class="ttname"><a href="_shape_calculator_8h.xhtml">ShapeCalculator.h</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_adbf67dcee294e673cf796f1ed8aeb6a4"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#adbf67dcee294e673cf796f1ed8aeb6a4">arm_compute::test::validation::dst</a></div><div class="ttdeci">CLTensor dst</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_absolute_difference_8cpp_source.xhtml#l00102">AbsoluteDifference.cpp:102</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a24d8c0391cfa38e78969b6ad97c0ff09"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a24d8c0391cfa38e78969b6ad97c0ff09">arm_compute::test::index2coord</a></div><div class="ttdeci">Coordinates index2coord(const TensorShape &amp;shape, int index)</div><div class="ttdoc">Convert a linear index into n-dimensional coordinates.</div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00456">Utils.h:456</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1misc_1_1shape__calculator_xhtml_a4e7f3187350db69156c1026860ace4e5"><div class="ttname"><a href="namespacearm__compute_1_1misc_1_1shape__calculator.xhtml#a4e7f3187350db69156c1026860ace4e5">arm_compute::misc::shape_calculator::compute_padded_shape</a></div><div class="ttdeci">TensorShape compute_padded_shape(const TensorShape &amp;input_shape, const PaddingList &amp;padding)</div><div class="ttdoc">Calculate the padded shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_shape_calculator_8h_source.xhtml#l01187">ShapeCalculator.h:1187</a></div></div>
<div class="ttc" id="classarm__compute_1_1test_1_1_simple_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">arm_compute::test::SimpleTensor</a></div><div class="ttdoc">Simple tensor object that stores elements in a consecutive chunk of memory.</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00059">SimpleTensor.h:59</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a669b5d3c5994f9ae3be31df9a1014297"><div class="ttname"><a href="namespacearm__compute.xhtml#a669b5d3c5994f9ae3be31df9a1014297">arm_compute::PaddingInfo</a></div><div class="ttdeci">std::pair&lt; uint32_t, uint32_t &gt; PaddingInfo</div><div class="ttdoc">Padding information as a pair of unsigned int start/end.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00452">Types.h:452</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92"><div class="ttname"><a href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91a8d6b5cada83510220f59e00ce86d4d92">arm_compute::PaddingMode::CONSTANT</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a14d24d90ab4ba2956e92e27890ba4c91ae4f6a05f82ed398f984f4bc1a55838df"><div class="ttname"><a href="namespacearm__compute.xhtml#a14d24d90ab4ba2956e92e27890ba4c91ae4f6a05f82ed398f984f4bc1a55838df">arm_compute::PaddingMode::REFLECT</a></div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_ac4a1050be02b20b3f791b9a483f3abe2"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#ac4a1050be02b20b3f791b9a483f3abe2">arm_compute::Dimensions::y</a></div><div class="ttdeci">T y() const</div><div class="ttdoc">Alias to access the size of the second dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00086">Dimensions.h:86</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&lt; uint32_t &gt;::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="arm__compute_2core_2_types_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_types_8h.xhtml">Types.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00075">Types.h:75</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a989ab3e96426615bb98e04e0235088ca"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a989ab3e96426615bb98e04e0235088ca">arm_compute::test::validation::src</a></div><div class="ttdeci">cast configure &amp; src</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_cast_8cpp_source.xhtml#l00169">Cast.cpp:169</a></div></div>
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