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| <a href="_pyramid_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> <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="_pyramid_8h.xhtml">arm_compute/runtime/Pyramid.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</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="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="_pyramid_info_8h.xhtml">arm_compute/core/PyramidInfo.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_tensor_info_8h.xhtml">arm_compute/core/TensorInfo.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="_tensor_shape_8h.xhtml">arm_compute/core/TensorShape.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_toolchain_support_8h.xhtml">support/ToolchainSupport.h</a>"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include <cmath></span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> </div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="keyword">using namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a>;</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_pyramid.xhtml#ae4e11cca76492d63009564d1ea466dff"> 36</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_pyramid.xhtml#ae4e11cca76492d63009564d1ea466dff">Pyramid::init</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pyramid_info.xhtml">PyramidInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>)</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  internal_init(<a class="code" href="classarm__compute_1_1_pyramid.xhtml#a7e9f724340af5b795b21a00d35eeb28e">info</a>, <span class="keyword">false</span>);</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> </div><div class="line"><a name="l00041"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_pyramid.xhtml#a0dd473fd109df68b4747ebf0f586a115"> 41</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_pyramid.xhtml#a0dd473fd109df68b4747ebf0f586a115">Pyramid::init_auto_padding</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pyramid_info.xhtml">PyramidInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>)</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> {</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  internal_init(<a class="code" href="classarm__compute_1_1_pyramid.xhtml#a7e9f724340af5b795b21a00d35eeb28e">info</a>, <span class="keyword">true</span>);</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> }</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="keywordtype">void</span> Pyramid::internal_init(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pyramid_info.xhtml">PyramidInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <span class="keywordtype">bool</span> auto_padding)</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span> {</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  _info = <a class="code" href="classarm__compute_1_1_pyramid.xhtml#a7e9f724340af5b795b21a00d35eeb28e">info</a>;</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  _pyramid.resize(_info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#aa2fea6640d2bd5de24d0e0c2433faab6">num_levels</a>());</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordtype">size_t</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a> = _info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#a9ce99f5dfa1514cb108665e3810b2c4c">width</a>();</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordtype">size_t</span> h = _info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#adc662cea5b05cd9852d5a4538586d662">height</a>();</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="keywordtype">size_t</span> ref_w = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordtype">size_t</span> ref_h = h;</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keywordtype">bool</span> is_orb_scale = (<a class="code" href="namespacearm__compute.xhtml#a2ebcd5423d5fba468e7debd2e1aabe91">SCALE_PYRAMID_ORB</a> == _info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#ade87abafbd6b200b22de988f32b66dea">scale</a>());</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> tensor_shape = _info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#a82c695f3a9ca51633ea8743d5c09f122">tensor_shape</a>();</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="comment">// Note: Look-up table used by the OpenVX sample implementation</span></div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">const</span> std::array<float, 4> c_orbscale = { 0.5f,</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <a class="code" href="namespacearm__compute.xhtml#a2ebcd5423d5fba468e7debd2e1aabe91">SCALE_PYRAMID_ORB</a>,</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="namespacearm__compute.xhtml#a2ebcd5423d5fba468e7debd2e1aabe91">SCALE_PYRAMID_ORB</a> * <a class="code" href="namespacearm__compute.xhtml#a2ebcd5423d5fba468e7debd2e1aabe91">SCALE_PYRAMID_ORB</a>,</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="namespacearm__compute.xhtml#a2ebcd5423d5fba468e7debd2e1aabe91">SCALE_PYRAMID_ORB</a> *<a class="code" href="namespacearm__compute.xhtml#a2ebcd5423d5fba468e7debd2e1aabe91">SCALE_PYRAMID_ORB</a> * <a class="code" href="namespacearm__compute.xhtml#a2ebcd5423d5fba468e7debd2e1aabe91">SCALE_PYRAMID_ORB</a></div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  };</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="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i < _info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#aa2fea6640d2bd5de24d0e0c2433faab6">num_levels</a>(); ++i)</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  {</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> tensor_info(tensor_shape, _info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#a7047a267776924cf166c301310f03a2c">format</a>());</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="keywordflow">if</span>(auto_padding)</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  {</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  tensor_info.<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a907f837b924945ad1981c8fe8eca61e4">auto_padding</a>();</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> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  _pyramid[i].allocator()->init(tensor_info);</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>  <span class="keywordflow">if</span>(is_orb_scale)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordtype">float</span> orb_scale = c_orbscale[(i + 1) % 4];</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a> = static_cast<int>(std::ceil(static_cast<float>(ref_w) * orb_scale));</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  h = static_cast<int>(std::ceil(static_cast<float>(ref_h) * orb_scale));</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordflow">if</span>(0 == ((i + 1) % 4))</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  {</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  ref_w = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  ref_h = h;</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>  }</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  {</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a> = (<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a> + 1) * _info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#ade87abafbd6b200b22de988f32b66dea">scale</a>();</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  h = (h + 1) * _info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#ade87abafbd6b200b22de988f32b66dea">scale</a>();</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>  <span class="comment">// Update tensor_shape</span></div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  tensor_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">set</a>(0, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1a367830ae09bf6138df822888ec1d71">w</a>);</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  tensor_shape.<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">set</a>(1, h);</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> }</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> </div><div class="line"><a name="l00100"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_pyramid.xhtml#acaefe811b78a2fdc4a0dba0c4029c3ef"> 100</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_pyramid.xhtml#acaefe811b78a2fdc4a0dba0c4029c3ef">Pyramid::allocate</a>()</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span> {</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i < _info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#aa2fea6640d2bd5de24d0e0c2433faab6">num_levels</a>(); ++i)</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  {</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  _pyramid[i].allocator()->allocate();</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  }</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> }</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span> </div><div class="line"><a name="l00108"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_pyramid.xhtml#a7e9f724340af5b795b21a00d35eeb28e"> 108</a></span> <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_pyramid_info.xhtml">PyramidInfo</a> *<a class="code" href="classarm__compute_1_1_pyramid.xhtml#a7e9f724340af5b795b21a00d35eeb28e">Pyramid::info</a>()<span class="keyword"> const</span></div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="keyword"></span>{</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="keywordflow">return</span> &_info;</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> }</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> </div><div class="line"><a name="l00113"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_pyramid.xhtml#a62c986dcfc8a16c2fbdc8bf33c77a7b3"> 113</a></span> <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a> *<a class="code" href="classarm__compute_1_1_pyramid.xhtml#a62c986dcfc8a16c2fbdc8bf33c77a7b3">Pyramid::get_pyramid_level</a>(<span class="keywordtype">size_t</span> index)<span class="keyword"> const</span></div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="keyword"></span>{</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(index >= _info.<a class="code" href="classarm__compute_1_1_pyramid_info.xhtml#aa2fea6640d2bd5de24d0e0c2433faab6">num_levels</a>());</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>  <span class="keywordflow">return</span> &_pyramid[index];</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span> }</div><div class="ttc" id="namespacearm__compute_xhtml_a2ebcd5423d5fba468e7debd2e1aabe91"><div class="ttname"><a href="namespacearm__compute.xhtml#a2ebcd5423d5fba468e7debd2e1aabe91">arm_compute::SCALE_PYRAMID_ORB</a></div><div class="ttdeci">constexpr float SCALE_PYRAMID_ORB</div><div class="ttdoc">Constant value used to indicate a ORB scaled pyramid.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00112">Types.h:112</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pyramid_info_xhtml_a82c695f3a9ca51633ea8743d5c09f122"><div class="ttname"><a href="classarm__compute_1_1_pyramid_info.xhtml#a82c695f3a9ca51633ea8743d5c09f122">arm_compute::PyramidInfo::tensor_shape</a></div><div class="ttdeci">const TensorShape & tensor_shape() const</div><div class="ttdoc">Return the TensorShape of the o-th level tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_info_8cpp_source.xhtml#l00092">PyramidInfo.cpp:92</a></div></div> |
| <div class="ttc" id="_pyramid_info_8h_xhtml"><div class="ttname"><a href="_pyramid_info_8h.xhtml">PyramidInfo.h</a></div></div> |
| <div class="ttc" id="_pyramid_8h_xhtml"><div class="ttname"><a href="_pyramid_8h.xhtml">Pyramid.h</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="_toolchain_support_8h_xhtml"><div class="ttname"><a href="_toolchain_support_8h.xhtml">ToolchainSupport.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pyramid_xhtml_a62c986dcfc8a16c2fbdc8bf33c77a7b3"><div class="ttname"><a href="classarm__compute_1_1_pyramid.xhtml#a62c986dcfc8a16c2fbdc8bf33c77a7b3">arm_compute::Pyramid::get_pyramid_level</a></div><div class="ttdeci">Tensor * get_pyramid_level(size_t index) const override</div><div class="ttdoc">Retrieves a level of the pyramid as a ITensor pointer.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_8cpp_source.xhtml#l00113">Pyramid.cpp:113</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pyramid_info_xhtml_a7047a267776924cf166c301310f03a2c"><div class="ttname"><a href="classarm__compute_1_1_pyramid_info.xhtml#a7047a267776924cf166c301310f03a2c">arm_compute::PyramidInfo::format</a></div><div class="ttdeci">Format format() const</div><div class="ttdoc">Return the image format of all tensor in the pyramid.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_info_8cpp_source.xhtml#l00097">PyramidInfo.cpp:97</a></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#l00466">Error.h:466</a></div></div> |
| <div class="ttc" id="_tensor_info_8h_xhtml"><div class="ttname"><a href="_tensor_info_8h.xhtml">TensorInfo.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a907f837b924945ad1981c8fe8eca61e4"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a907f837b924945ad1981c8fe8eca61e4">arm_compute::TensorInfo::auto_padding</a></div><div class="ttdeci">bool auto_padding() override</div><div class="ttdoc">Update the offset to the first element and the strides to automatically computed values.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_tensor_info_8cpp_source.xhtml#l00222">TensorInfo.cpp:222</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="classarm__compute_1_1_pyramid_xhtml_ae4e11cca76492d63009564d1ea466dff"><div class="ttname"><a href="classarm__compute_1_1_pyramid.xhtml#ae4e11cca76492d63009564d1ea466dff">arm_compute::Pyramid::init</a></div><div class="ttdeci">void init(const PyramidInfo &info)</div><div class="ttdoc">Initialize pyramid data-object using the given Pyramid's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_8cpp_source.xhtml#l00036">Pyramid.cpp:36</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pyramid_xhtml_a0dd473fd109df68b4747ebf0f586a115"><div class="ttname"><a href="classarm__compute_1_1_pyramid.xhtml#a0dd473fd109df68b4747ebf0f586a115">arm_compute::Pyramid::init_auto_padding</a></div><div class="ttdeci">void init_auto_padding(const PyramidInfo &info)</div><div class="ttdoc">Initialize pyramid data-object using the given Pyramid's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_8cpp_source.xhtml#l00041">Pyramid.cpp:41</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml">arm_compute::Tensor</a></div><div class="ttdoc">Basic implementation of the tensor interface.</div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8h_source.xhtml#l00037">Tensor.h:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pyramid_info_xhtml_ade87abafbd6b200b22de988f32b66dea"><div class="ttname"><a href="classarm__compute_1_1_pyramid_info.xhtml#ade87abafbd6b200b22de988f32b66dea">arm_compute::PyramidInfo::scale</a></div><div class="ttdeci">float scale() const</div><div class="ttdoc">Return the scale factor of the pyramid.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_info_8cpp_source.xhtml#l00102">PyramidInfo.cpp:102</a></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="classarm__compute_1_1_pyramid_xhtml_acaefe811b78a2fdc4a0dba0c4029c3ef"><div class="ttname"><a href="classarm__compute_1_1_pyramid.xhtml#acaefe811b78a2fdc4a0dba0c4029c3ef">arm_compute::Pyramid::allocate</a></div><div class="ttdeci">void allocate()</div><div class="ttdoc">Allocate the planes in the pyramid.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_8cpp_source.xhtml#l00100">Pyramid.cpp:100</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pyramid_xhtml_a7e9f724340af5b795b21a00d35eeb28e"><div class="ttname"><a href="classarm__compute_1_1_pyramid.xhtml#a7e9f724340af5b795b21a00d35eeb28e">arm_compute::Pyramid::info</a></div><div class="ttdeci">const PyramidInfo * info() const override</div><div class="ttdoc">Interface to be implemented by the child class to return the Pyramid's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_8cpp_source.xhtml#l00108">Pyramid.cpp:108</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pyramid_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pyramid_info.xhtml">arm_compute::PyramidInfo</a></div><div class="ttdoc">Store the Pyramid's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_info_8h_source.xhtml#l00035">PyramidInfo.h:35</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml_a9c54fb6cea3557692fe7c00c40bb40ad"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml#a9c54fb6cea3557692fe7c00c40bb40ad">arm_compute::TensorShape::set</a></div><div class="ttdeci">TensorShape & set(size_t dimension, size_t value, bool apply_dim_correction=true)</div><div class="ttdoc">Accessor to set the value of one of the dimensions.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00078">TensorShape.h:78</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pyramid_info_xhtml_a9ce99f5dfa1514cb108665e3810b2c4c"><div class="ttname"><a href="classarm__compute_1_1_pyramid_info.xhtml#a9ce99f5dfa1514cb108665e3810b2c4c">arm_compute::PyramidInfo::width</a></div><div class="ttdeci">size_t width() const</div><div class="ttdoc">Return the width of the 0th level tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_info_8cpp_source.xhtml#l00082">PyramidInfo.cpp:82</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pyramid_info_xhtml_aa2fea6640d2bd5de24d0e0c2433faab6"><div class="ttname"><a href="classarm__compute_1_1_pyramid_info.xhtml#aa2fea6640d2bd5de24d0e0c2433faab6">arm_compute::PyramidInfo::num_levels</a></div><div class="ttdeci">size_t num_levels() const</div><div class="ttdoc">Return the number of the pyramid levels.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_info_8cpp_source.xhtml#l00077">PyramidInfo.cpp:77</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="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">ConvolutionLayer.cpp:182</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_pyramid_info_xhtml_adc662cea5b05cd9852d5a4538586d662"><div class="ttname"><a href="classarm__compute_1_1_pyramid_info.xhtml#adc662cea5b05cd9852d5a4538586d662">arm_compute::PyramidInfo::height</a></div><div class="ttdeci">size_t height() const</div><div class="ttdoc">Return the height of the 0th level tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_pyramid_info_8cpp_source.xhtml#l00087">PyramidInfo.cpp:87</a></div></div> |
| <div class="ttc" id="_tensor_shape_8h_xhtml"><div class="ttname"><a href="_tensor_shape_8h.xhtml">TensorShape.h</a></div></div> |
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