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| <a href="_n_e_crop_kernel_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) 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="_n_e_crop_kernel_8h.xhtml">arm_compute/core/NEON/kernels/NECropKernel.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="_c_p_p_2_validate_8h.xhtml">arm_compute/core/CPP/Validate.h</a>"</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="_i_access_window_8h.xhtml">arm_compute/core/IAccessWindow.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_i_tensor_8h.xhtml">arm_compute/core/ITensor.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_info_8h.xhtml">arm_compute/core/TensorInfo.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "<a class="code" href="_window_8h.xhtml">arm_compute/core/Window.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 "<a class="code" href="wrapper_8h.xhtml">arm_compute/core/NEON/wrapper/wrapper.h</a>"</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>"</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include "<a class="code" href="bit__ops_8h.xhtml">arm_compute/core/utils/helpers/bit_ops.h</a>"</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="preprocessor">#include "<a class="code" href="tensor__transform_8h.xhtml">arm_compute/core/utils/helpers/tensor_transform.h</a>"</span></div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="preprocessor">#include "<a class="code" href="_shape_calculator_8h.xhtml">arm_compute/core/utils/misc/ShapeCalculator.h</a>"</span></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> <span class="preprocessor">#include <map></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> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span> {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="keyword">namespace</span></div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> {</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">inline</span> float32x4_t load_as_f32(T *ptr)</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span> {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(ptr);</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Type not supported."</span>);</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> </div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="keyword">inline</span> float32x4_t load_as_f32(<span class="keywordtype">float</span> *ptr)</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> {</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">return</span> <a class="code" href="namespacearm__compute_1_1wrapper.xhtml#a77f54eded7fef436d3a4f21ad5a00da6">wrapper::vloadq</a>(ptr);</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> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="keyword">inline</span> float32x4_t load_as_f32(int32_t *ptr)</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="keywordflow">return</span> vcvtq_f32_s32(<a class="code" href="namespacearm__compute_1_1wrapper.xhtml#a77f54eded7fef436d3a4f21ad5a00da6">wrapper::vloadq</a>(ptr));</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> }</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="keyword">inline</span> float32x4_t load_as_f32(uint32_t *ptr)</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span> {</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keywordflow">return</span> vcvtq_f32_u32(<a class="code" href="namespacearm__compute_1_1wrapper.xhtml#a77f54eded7fef436d3a4f21ad5a00da6">wrapper::vloadq</a>(ptr));</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> }</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">template</span> <></div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="keyword">inline</span> float32x4_t load_as_f32(int16_t *ptr)</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>  <span class="keywordflow">return</span> vcvtq_f32_s32(vmovl_s16(<a class="code" href="namespacearm__compute_1_1wrapper.xhtml#ae1a6f6dde14fc3b0470cd0b08041ea9f">wrapper::vload</a>(ptr)));</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> </div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="keyword">inline</span> float32x4_t load_as_f32(uint16_t *ptr)</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="keywordflow">return</span> vcvtq_f32_u32(vmovl_u16(<a class="code" href="namespacearm__compute_1_1wrapper.xhtml#ae1a6f6dde14fc3b0470cd0b08041ea9f">wrapper::vload</a>(ptr)));</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> </div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="keyword">template</span> <></div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="keyword">inline</span> float32x4_t load_as_f32(float16_t *ptr)</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>  <span class="keywordflow">return</span> vcvt_f32_f16(<a class="code" href="namespacearm__compute_1_1wrapper.xhtml#ae1a6f6dde14fc3b0470cd0b08041ea9f">wrapper::vload</a>(ptr));</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> <span class="preprocessor">#endif </span><span class="comment">/* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */</span><span class="preprocessor"></span></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">template</span> <<span class="keyword">typename</span> T, <span class="keywordtype">bool</span> input_has_single_channel, <span class="keywordtype">bool</span> is_w<span class="keywordtype">id</span>th_flipped></div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> in_bounds_crop_window(<span class="keyword">const</span> ITensor *input, <span class="keyword">const</span> ITensor *output, <span class="keywordtype">float</span> *output_ptr, Coordinates input_offset,</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  int32_t window_step_x, int32_t output_width_start, int32_t output_width_limit)</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>  <span class="comment">// Reverse elements if width flipped.</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="keywordflow">if</span>(is_width_flipped)</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  {</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="comment">// Collapse first dimension if possible.</span></div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="keywordflow">if</span>(input_has_single_channel)</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>  int32_t x = output_width_start;</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  Coordinates negative_offset(input_offset);</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  negative_offset.set(1, negative_offset[1] - window_step_x + 1);</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordflow">for</span>(; x <= output_width_limit - window_step_x; x += window_step_x, negative_offset[1] -= window_step_x)</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>  <span class="keyword">auto</span> in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(negative_offset)));</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>  in = <a class="code" href="namespacearm__compute_1_1wrapper.xhtml#aa7a641703a9c98932d775d915bf7a3e5">wrapper::vrev64</a>(in);</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  in = <a class="code" href="namespacearm__compute_1_1wrapper.xhtml#a1598e7eb12a58fc53559332cd0c3ab6f">wrapper::vcombine</a>(<a class="code" href="namespacearm__compute_1_1wrapper.xhtml#a95ee388aa7c5bccab918235dc538a6b3">wrapper::vgethigh</a>(in), <a class="code" href="namespacearm__compute_1_1wrapper.xhtml#a2902775707bc7bf7d6da1bda1cc15783">wrapper::vgetlow</a>(in));</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>  <a class="code" href="namespacearm__compute_1_1wrapper.xhtml#ae7943ea9c1f74dc72c62d4cc3966a459">wrapper::vstore</a>(output_ptr + x, in);</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>  input_offset[1] = negative_offset[1] + window_step_x - 1;</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordflow">for</span>(; x < output_width_limit; ++x, --input_offset[1])</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>  *(output_ptr + x) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  }</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">else</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>  <span class="keywordflow">for</span>(int32_t x = output_width_start; x < output_width_limit; ++x, --input_offset[1])</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>  input_offset.set(0, 0);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  int32_t c = 0;</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  <span class="keywordflow">for</span>(; c <= static_cast<int32_t>(input->info()->dimension(0)) - window_step_x; c += window_step_x, input_offset[0] += window_step_x)</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  {</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <span class="keyword">auto</span> in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(input_offset)));</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <a class="code" href="namespacearm__compute_1_1wrapper.xhtml#ae7943ea9c1f74dc72c62d4cc3966a459">wrapper::vstore</a>(output_ptr + x * output->info()->dimension(0) + c, in);</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>  <span class="keywordflow">for</span>(; c < static_cast<int32_t>(input->info()->dimension(0)); ++c, ++input_offset[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>  *(output_ptr + x * output->info()->dimension(0) + c) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  }</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  }</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"> 135</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  {</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="comment">// Use memcpy if the elements don't need converting to float.</span></div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  <span class="keywordflow">if</span>(std::is_same<T, float>::value)</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  {</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  memcpy(static_cast<void *>(output_ptr + output_width_start * output->info()->dimension(0)),</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  reinterpret_cast<const void *>(input->ptr_to_element(input_offset)),</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  (output_width_limit - output_width_start) * output->info()->dimension(0) * output->info()->element_size());</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  }</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordflow">else</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>  int32_t x = 0;</div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  int32_t limit = (output_width_limit - output_width_start) * static_cast<int32_t>(output->info()->dimension(0));</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <span class="keywordtype">float</span> *output_start_ptr = output_ptr + output_width_start * output->info()->dimension(0);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">for</span>(; x <= limit - window_step_x; x += window_step_x, input_offset[0] += window_step_x)</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="keyword">auto</span> in = load_as_f32(reinterpret_cast<T *>(input->ptr_to_element(input_offset)));</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <a class="code" href="namespacearm__compute_1_1wrapper.xhtml#ae7943ea9c1f74dc72c62d4cc3966a459">wrapper::vstore</a>(output_start_ptr + x, in);</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>  <span class="keywordflow">for</span>(; x < limit; ++x, ++input_offset[0])</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  {</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  *(output_start_ptr + x) = static_cast<float>(*reinterpret_cast<T *>(input->ptr_to_element(input_offset)));</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>  }</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  }</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> </div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> out_of_bounds_crop_window(<span class="keyword">const</span> ITensor *output, <span class="keywordtype">float</span> *output_ptr, <span class="keywordtype">float</span> extrapolation_value,</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  int32_t window_step_x, int32_t output_width_start, int32_t output_width_limit)</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span> {</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">auto</span> in = <a class="code" href="namespacearm__compute_1_1wrapper.xhtml#a39e87435be178fba49b76f49426ef873">wrapper::vdup_n</a>(extrapolation_value, wrapper::traits::vector_128_tag());</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  int32_t x = 0;</div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  int32_t limit = (output_width_limit - output_width_start) * static_cast<int32_t>(output->info()->dimension(0));</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="keywordtype">float</span> *output_start_ptr = output_ptr + output_width_start * output->info()->dimension(0);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">for</span>(; x <= limit - window_step_x; x += window_step_x)</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>  <a class="code" href="namespacearm__compute_1_1wrapper.xhtml#ae7943ea9c1f74dc72c62d4cc3966a459">wrapper::vstore</a>(output_start_ptr + x, in);</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>(; x < limit; ++x)</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>  *(output_start_ptr + x) = extrapolation_value;</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"> 179</span> <span class="keyword">template</span> <<span class="keywordtype">bool</span> is_height_flipped, <span class="keywordtype">bool</span> has_cols_in_bounds, <span class="keywordtype">bool</span> has_cols_out_of_bounds_before, <span class="keywordtype">bool</span> has_cols_out_of_bounds_after></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> execute_window(<span class="keyword">const</span> ITensor *input, <span class="keyword">const</span> ITensor *output, Coordinates input_offset, <span class="keywordtype">float</span> extrapolation_value,</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keyword">const</span> std::array<uint32_t, 2> &rows_out_of_bounds, <span class="keyword">const</span> std::array<uint32_t, 2> &cols_out_of_bounds, <a class="code" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a54afc81e82afa5ab200b81f536b8453a">NECropKernel::InBoundsCropFunction</a> *in_bounds_crop_function)</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>  <span class="comment">// Output is always float.</span></div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> window_step_x = 16 / <span class="keyword">sizeof</span>(float);</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="keyword">auto</span> *output_ptr = reinterpret_cast<float *>(output->buffer());</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="comment">// Output window:</span></div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="comment">// --------------------------------</span></div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="comment">// | Out of bounds |</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="comment">// | rows before |</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="comment">// |------------------------------|</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="comment">// | Out of | In | Out of |</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="comment">// | bounds | bounds | bounds |</span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="comment">// | cols | elements | cols |</span></div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="comment">// | before | copied | after |</span></div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <span class="comment">// | | from input | |</span></div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="comment">// --------------------------------</span></div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// | Out of bounds |</span></div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="comment">// | rows after |</span></div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="comment">// |------------------------------|</span></div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <span class="comment">// Fill all output rows that have no elements that are within the input bounds with the extrapolation value.</span></div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="comment">// First for the rows before the in bounds rows.</span></div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, 0, rows_out_of_bounds[0] * output->info()->dimension(1));</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  output_ptr += rows_out_of_bounds[0] * output->info()->dimension(1) * output->info()->dimension(0);</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="comment">// Iterate through each row that has any elements within the input bounds.</span></div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordflow">for</span>(uint32_t row = rows_out_of_bounds[0]; static_cast<int32_t>(row) < static_cast<int32_t>(output->info()->dimension(2) - rows_out_of_bounds[1]);</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  ++row, is_height_flipped ? --input_offset[2] : ++input_offset[2])</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  {</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="comment">// Fill all elements in the row that are out of bounds with the extrapolation value.</span></div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="comment">// First for the elements before the in bounds elements.</span></div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">if</span>(has_cols_out_of_bounds_before)</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  {</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, 0, cols_out_of_bounds[0]);</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  }</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="comment">// Copy all elements within the input bounds from the input tensor.</span></div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <span class="keywordflow">if</span>(has_cols_in_bounds)</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  {</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  (*in_bounds_crop_function)(input, output, output_ptr, input_offset, window_step_x, cols_out_of_bounds[0], output->info()->dimension(1) - cols_out_of_bounds[1]);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  }</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="comment">// Fill all elements after the in bounds elements with the extrapolation value.</span></div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="keywordflow">if</span>(has_cols_out_of_bounds_after)</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  {</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, output->info()->dimension(1) - cols_out_of_bounds[1], output->info()->dimension(1));</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  }</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  output_ptr += output->info()->dimension(1) * output->info()->dimension(0);</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  }</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="comment">// Fill all rows after the in bounds elements with the extrapolation value.</span></div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  out_of_bounds_crop_window(output, output_ptr, extrapolation_value, window_step_x, 0, rows_out_of_bounds[1] * output->info()->dimension(1));</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span> }</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span> } <span class="comment">// namespace</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"><a class="line" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#ad8887523c29f0065e3557ca800c4b042"> 231</a></span> <a class="code" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#ad8887523c29f0065e3557ca800c4b042">NECropKernel::NECropKernel</a>()</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  : _input(nullptr), _crop_boxes(nullptr), _box_ind(nullptr), _output(nullptr), _start(), _end(), _crop_box_ind(0), _extrapolation_value(0), _rows_out_of_bounds(), _cols_out_of_bounds(),</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  _in_bounds_crop_functions(), _in_bounds_crop_function(nullptr), _crop_function(nullptr)</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span> {</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> }</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div><div class="line"><a name="l00237"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#af4bfea161972c091109e4bd1c8245f2c"> 237</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#af4bfea161972c091109e4bd1c8245f2c">NECropKernel::configure</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *input, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *crop_boxes, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *box_ind, <a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> *output, uint32_t crop_box_ind, <span class="keywordtype">float</span> extrapolation_value)</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> {</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(input, output);</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(<a class="code" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a0b1369db011f9d5603d2f6ab4bab8548">validate</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), crop_boxes-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), box_ind-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), crop_box_ind, extrapolation_value));</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>  _input = input;</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  _crop_boxes = crop_boxes;</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  _box_ind = box_ind;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  _output = output;</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  _crop_box_ind = crop_box_ind;</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  _extrapolation_value = extrapolation_value;</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>  <span class="keyword">const</span> <span class="keyword">static</span> std::map<std::pair<DataType, bool>, std::pair<NECropKernel::InBoundsCropFunction *, NECropKernel::InBoundsCropFunction *>> in_map_function =</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  {</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, <span class="keyword">false</span> }, { &in_bounds_crop_window<float, false, false>, &in_bounds_crop_window<float, false, true> } },</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, <span class="keyword">true</span> }, { &in_bounds_crop_window<float, true, false>, &in_bounds_crop_window<float, true, true> } },</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">DataType::U16</a>, <span class="keyword">false</span> }, { &in_bounds_crop_window<uint16_t, false, false>, &in_bounds_crop_window<uint16_t, false, true> } },</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">DataType::U16</a>, <span class="keyword">true</span> }, { &in_bounds_crop_window<uint16_t, true, false>, &in_bounds_crop_window<uint16_t, true, true> } },</div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">DataType::S16</a>, <span class="keyword">false</span> }, { &in_bounds_crop_window<int16_t, false, false>, &in_bounds_crop_window<int16_t, false, true> } },</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">DataType::S16</a>, <span class="keyword">true</span> }, { &in_bounds_crop_window<int16_t, true, false>, &in_bounds_crop_window<int16_t, true, true> } },</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>, <span class="keyword">false</span> }, { &in_bounds_crop_window<uint32_t, false, false>, &in_bounds_crop_window<uint32_t, false, true> } },</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>, <span class="keyword">true</span> }, { &in_bounds_crop_window<uint32_t, true, false>, &in_bounds_crop_window<uint32_t, true, true> } },</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>, <span class="keyword">false</span> }, { &in_bounds_crop_window<int32_t, false, false>, &in_bounds_crop_window<int32_t, false, true> } },</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>, <span class="keyword">true</span> }, { &in_bounds_crop_window<int32_t, true, false>, &in_bounds_crop_window<int32_t, true, true> } },</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span> <span class="preprocessor">#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC</span></div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <span class="keyword">false</span> }, { &in_bounds_crop_window<float16_t, false, false>, &in_bounds_crop_window<float16_t, false, true> } },</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  { { <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <span class="keyword">false</span> }, { &in_bounds_crop_window<float16_t, true, false>, &in_bounds_crop_window<float16_t, true, true> } }</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span> <span class="preprocessor">#endif </span><span class="comment">/* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */</span><span class="preprocessor"></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"> 267</span>  <span class="keyword">auto</span> in_it = in_map_function.find({ input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>(), input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0) == 1 });</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>(in_it != in_map_function.end())</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>  _in_bounds_crop_functions = in_it->second;</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  }</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> }</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span> </div><div class="line"><a name="l00275"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a0b1369db011f9d5603d2f6ab4bab8548"> 275</a></span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a0b1369db011f9d5603d2f6ab4bab8548">NECropKernel::validate</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *input, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *crop_boxes, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *box_ind, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *output, uint32_t crop_box_ind, <span class="keywordtype">float</span> extrapolation_value)</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>  <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(extrapolation_value);</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <a class="code" href="_c_p_p_2_validate_8h.xhtml#ad2633f3560322e1f8d926949dec1b730">ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED</a>(input);</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(input, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">DataType::U16</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">DataType::S16</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <a class="code" href="_validate_8h.xhtml#a7e906bfc9e333e3f967d8ee9353ce001">ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN</a>(input, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(input-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>().<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a80a5f2d6e3a697c9aad893a3b4242615">num_dimensions</a>() > 4);</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(crop_boxes-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[0] != 4);</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(crop_boxes-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[1] != box_ind-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[0]);</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(crop_boxes-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[1] <= crop_box_ind);</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(box_ind-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[0] <= crop_box_ind);</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <span class="keywordflow">if</span>(output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>() > 0)</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>  <a class="code" href="_validate_8h.xhtml#aef783de4ec01874dbec6054a5868aea2">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN</a>(output, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <a class="code" href="_validate_8h.xhtml#abdb9168800c70e5e2c4c020a3b905738">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT</a>(input, output);</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() != 3);</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(output-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#ac394d6570ab3325810a3532d39091a52">has_padding</a>());</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>  <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</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"><a class="line" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a0da66c75715e5f334da280799a55c923"> 296</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a0da66c75715e5f334da280799a55c923">NECropKernel::configure_output_shape</a>()</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="comment">// _crop_box_ind is used to index _crop_boxes and retrieve the appropriate crop box.</span></div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="comment">// The crop box is specified by normalized coordinates [y0, x0, y1, x1].</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> x0 = *reinterpret_cast<const float *>(_crop_boxes-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(<a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(1, _crop_box_ind)));</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> y0 = *reinterpret_cast<const float *>(_crop_boxes-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(<a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(0, _crop_box_ind)));</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> x1 = *reinterpret_cast<const float *>(_crop_boxes-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(<a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(3, _crop_box_ind)));</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> y1 = *reinterpret_cast<const float *>(_crop_boxes-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(<a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(2, _crop_box_ind)));</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="comment">// The normalized coordiantes are scaled to retrieve the floating point image coordinates which are rounded to integers.</span></div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  _start = <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(std::floor(x0 * (_input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[1] - 1) + 0.5f),</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  std::floor(y0 * (_input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[2] - 1) + 0.5f));</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  _end = <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(std::floor(x1 * (_input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[1] - 1) + 0.5f),</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  std::floor(y1 * (_input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[2] - 1) + 0.5f));</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> out_shape(_input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>()[0], abs(_end[0] - _start[0]) + 1, abs(_end[1] - _start[1]) + 1);</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  _output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a12a4f1190952613e36b44846962e26bb">set_tensor_shape</a>(out_shape);</div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span> </div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  _in_bounds_crop_function = _start[0] <= _end[0] ? _in_bounds_crop_functions.first : _in_bounds_crop_functions.second;</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">bool</span> is_width_flipped = _end[0] < _start[0];</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="keywordtype">bool</span> is_height_flipped = _end[1] < _start[1];</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordflow">if</span>(is_height_flipped)</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  {</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  _rows_out_of_bounds[0] = _start[1] >= static_cast<int32_t>(_input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2)) ? std::min(static_cast<uint32_t>(_start[1] - _input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2) + 1),</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  static_cast<uint32_t>(_output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2))) :</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  0;</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  _rows_out_of_bounds[1] = _end[1] < 0 ? std::min(static_cast<uint32_t>(-_end[1]),</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  static_cast<uint32_t>(_output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2))) :</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  0;</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>  <span class="keywordflow">else</span></div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  {</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  _rows_out_of_bounds[0] = _start[1] < 0 ? std::min(static_cast<uint32_t>(-_start[1]),</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  static_cast<uint32_t>(_output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2))) :</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  0;</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  _rows_out_of_bounds[1] = _end[1] >= static_cast<int32_t>(_input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2)) ? std::min(static_cast<uint32_t>(_end[1] - _input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2) + 1),</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  static_cast<uint32_t>(_output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(2))) :</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  0;</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  }</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">if</span>(is_width_flipped)</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  {</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  _cols_out_of_bounds[0] = _start[0] >= static_cast<int32_t>(_input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1)) ? std::min(static_cast<uint32_t>(_start[0] - _input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1) + 1),</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  static_cast<uint32_t>(_output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1))) :</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  0;</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  _cols_out_of_bounds[1] = _end[0] < 0 ? std::min(static_cast<uint32_t>(-_end[0]),</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  static_cast<uint32_t>(_output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1))) :</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  0;</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  }</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  {</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  _cols_out_of_bounds[0] = _start[0] < 0 ? std::min(static_cast<uint32_t>(-_start[0]),</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  static_cast<uint32_t>(_output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1))) :</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  0;</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  _cols_out_of_bounds[1] = _end[0] >= static_cast<int32_t>(_input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1)) ? std::min(static_cast<uint32_t>(_end[0] - _input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1) + 1),</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  static_cast<uint32_t>(_output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1))) :</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  0;</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</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>  <span class="keyword">const</span> <span class="keyword">static</span> std::map<std::tuple<bool, bool, bool, bool>, NECropKernel::CropFunction *> map_function =</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  {</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  { std::make_tuple(<span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>), &execute_window<false, false, false, false> },</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  { std::make_tuple(<span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">true</span>), &execute_window<false, false, false, true> },</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  { std::make_tuple(<span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">true</span>, <span class="keyword">false</span>), &execute_window<false, false, true, false> },</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  { std::make_tuple(<span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">true</span>, <span class="keyword">true</span>), &execute_window<false, false, true, true> },</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  { std::make_tuple(<span class="keyword">false</span>, <span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">false</span>), &execute_window<false, true, false, false> },</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  { std::make_tuple(<span class="keyword">false</span>, <span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">true</span>), &execute_window<false, true, false, true> },</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  { std::make_tuple(<span class="keyword">false</span>, <span class="keyword">true</span>, <span class="keyword">true</span>, <span class="keyword">false</span>), &execute_window<false, true, true, false> },</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  { std::make_tuple(<span class="keyword">false</span>, <span class="keyword">true</span>, <span class="keyword">true</span>, <span class="keyword">true</span>), &execute_window<false, true, true, true> },</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  { std::make_tuple(<span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>), &execute_window<true, false, false, false> },</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  { std::make_tuple(<span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">true</span>), &execute_window<true, false, false, true> },</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  { std::make_tuple(<span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">true</span>, <span class="keyword">false</span>), &execute_window<true, false, true, false> },</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  { std::make_tuple(<span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">true</span>, <span class="keyword">true</span>), &execute_window<true, false, true, true> },</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  { std::make_tuple(<span class="keyword">true</span>, <span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">false</span>), &execute_window<true, true, false, false> },</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  { std::make_tuple(<span class="keyword">true</span>, <span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">true</span>), &execute_window<true, true, false, true> },</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  { std::make_tuple(<span class="keyword">true</span>, <span class="keyword">true</span>, <span class="keyword">true</span>, <span class="keyword">false</span>), &execute_window<true, true, true, false> },</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  { std::make_tuple(<span class="keyword">true</span>, <span class="keyword">true</span>, <span class="keyword">true</span>, <span class="keyword">true</span>), &execute_window<true, true, true, true> },</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  };</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span> </div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keyword">auto</span> it = map_function.find(std::make_tuple(is_height_flipped,</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  _cols_out_of_bounds[0] + _cols_out_of_bounds[1] < _output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1),</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  _cols_out_of_bounds[0] > 0,</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  _cols_out_of_bounds[1] > 0));</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="keywordflow">if</span>(it != map_function.end())</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  {</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  _crop_function = it->second;</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>  INEKernel::configure(<a class="code" href="namespacearm__compute.xhtml#ab7980fa5ee693e3282a76da047a1c3b5">calculate_max_window</a>(*_output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()));</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span> }</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> </div><div class="line"><a name="l00386"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a112b35dd205c62ea6ed1447ef226da82"> 386</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a112b35dd205c62ea6ed1447ef226da82">NECropKernel::run</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> &window, <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_thread_info.xhtml">ThreadInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>)</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> {</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <a class="code" href="_error_8h.xhtml#a6dc630a6ae9cc063b3924bcea8dee9d6">ARM_COMPUTE_UNUSED</a>(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>);</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <a class="code" href="_validate_8h.xhtml#a1b35b0d258183cf9ef36adf684d0b88c">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a>(<span class="keyword">this</span>);</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <a class="code" href="_validate_8h.xhtml#a6eb9ce82815fe429250189da7592ba75">ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW</a>(<a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">INEKernel::window</a>(), <a class="code" href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">window</a>);</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> </div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(_input-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#ac394d6570ab3325810a3532d39091a52">has_padding</a>());</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(_output-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#ac394d6570ab3325810a3532d39091a52">has_padding</a>());</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span> </div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  uint32_t batch_index = *(reinterpret_cast<int32_t *>(_box_ind-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">ptr_to_element</a>(<a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a>(_crop_box_ind))));</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> input_offset(0, _end[0] < _start[0] ? _start[0] - _cols_out_of_bounds[0] : _start[0] + _cols_out_of_bounds[0],</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  _end[1] < _start[1] ? _start[1] - _rows_out_of_bounds[0] : _start[1] + _rows_out_of_bounds[0], batch_index);</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  (*_crop_function)(_input, _output, input_offset, _extrapolation_value, _rows_out_of_bounds, _cols_out_of_bounds, _in_bounds_crop_function);</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span> }</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</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_a1f4e725b8e1ea36b30e09dc08ae6961d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">arm_compute::ITensorInfo::num_dimensions</a></div><div class="ttdeci">virtual size_t num_dimensions() const =0</div><div class="ttdoc">The number of dimensions of the tensor (rank)</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_kernel_xhtml_ad34a46f53686c12a5c5e717cc9617fb6"><div class="ttname"><a href="classarm__compute_1_1_i_kernel.xhtml#ad34a46f53686c12a5c5e717cc9617fb6">arm_compute::IKernel::window</a></div><div class="ttdeci">const Window & window() const</div><div class="ttdoc">The maximum window the kernel can be executed on.</div><div class="ttdef"><b>Definition:</b> <a href="_i_kernel_8cpp_source.xhtml#l00028">IKernel.cpp:28</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_adbd73147d41e8a640bc299d12613c31e"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#adbd73147d41e8a640bc299d12613c31e">arm_compute::ITensor::ptr_to_element</a></div><div class="ttdeci">uint8_t * ptr_to_element(const Coordinates &id) const</div><div class="ttdoc">Return a pointer to the element at the passed coordinates.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00063">ITensor.h:63</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="_i_tensor_8h_xhtml"><div class="ttname"><a href="_i_tensor_8h.xhtml">ITensor.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a178f0d3d87f959e00a743328d95359d2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">arm_compute::ITensorInfo::dimension</a></div><div class="ttdeci">virtual size_t dimension(size_t index) const =0</div><div class="ttdoc">Return the size of the requested dimension.</div></div> |
| <div class="ttc" id="_validate_8h_xhtml_abdb9168800c70e5e2c4c020a3b905738"><div class="ttname"><a href="_validate_8h.xhtml#abdb9168800c70e5e2c4c020a3b905738">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00494">Validate.h:494</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_1_1wrapper_xhtml_a77f54eded7fef436d3a4f21ad5a00da6"><div class="ttname"><a href="namespacearm__compute_1_1wrapper.xhtml#a77f54eded7fef436d3a4f21ad5a00da6">arm_compute::wrapper::vloadq</a></div><div class="ttdeci">uint8x16_t vloadq(const uint8_t *ptr)</div><div class="ttdef"><b>Definition:</b> <a href="load_8h_source.xhtml#l00058">load.h:58</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="classarm__compute_1_1_n_e_crop_kernel_xhtml_a54afc81e82afa5ab200b81f536b8453a"><div class="ttname"><a href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a54afc81e82afa5ab200b81f536b8453a">arm_compute::NECropKernel::InBoundsCropFunction</a></div><div class="ttdeci">void(const ITensor *, const ITensor *, float *, Coordinates, int32_t, int32_t, int32_t) InBoundsCropFunction</div><div class="ttdoc">Function to use for in bounds crop for the particular tensor types passed to configure()</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_crop_kernel_8h_source.xhtml#l00097">NECropKernel.h:97</a></div></div> |
| <div class="ttc" id="_window_8h_xhtml"><div class="ttname"><a href="_window_8h.xhtml">Window.h</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_ae7eed178dac535c6e727061b1f5bc6eb"><div class="ttname"><a href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00791">Validate.h:791</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel</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="_error_8h_xhtml_a938dcd406ce611ef5345ad2531cdb948"><div class="ttname"><a href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_THROW_ON(status)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00327">Error.h:327</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::Format::U16</a></div><div class="ttdoc">1 channel, 1 U16 per channel</div></div> |
| <div class="ttc" id="classarm__compute_1_1_status_xhtml"><div class="ttname"><a href="classarm__compute_1_1_status.xhtml">arm_compute::Status</a></div><div class="ttdoc">Status class.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00052">Error.h:52</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_aef783de4ec01874dbec6054a5868aea2"><div class="ttname"><a href="_validate_8h.xhtml#aef783de4ec01874dbec6054a5868aea2">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(t,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00693">Validate.h:693</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_n_e_crop_kernel_xhtml_af4bfea161972c091109e4bd1c8245f2c"><div class="ttname"><a href="classarm__compute_1_1_n_e_crop_kernel.xhtml#af4bfea161972c091109e4bd1c8245f2c">arm_compute::NECropKernel::configure</a></div><div class="ttdeci">void configure(const ITensor *input, const ITensor *crop_boxes, const ITensor *box_ind, ITensor *output, uint32_t crop_box_ind=0, float extrapolation_value=0)</div><div class="ttdoc">Configure kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_crop_kernel_8cpp_source.xhtml#l00237">NECropKernel.cpp:237</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a206d6e247e0957ac3dee45d27756fc25"><div class="ttname"><a href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00244">Error.h:244</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_ab7980fa5ee693e3282a76da047a1c3b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab7980fa5ee693e3282a76da047a1c3b5">arm_compute::calculate_max_window</a></div><div class="ttdeci">Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps=Steps(), bool skip_border=false, BorderSize border_size=BorderSize())</div><div class="ttdoc">Calculate the maximum window for a given tensor shape and border setting.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_helpers_8cpp_source.xhtml#l00028">Helpers.cpp:28</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="_c_p_p_2_validate_8h_xhtml_ad2633f3560322e1f8d926949dec1b730"><div class="ttname"><a href="_c_p_p_2_validate_8h.xhtml#ad2633f3560322e1f8d926949dec1b730">ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(tensor)</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_2_validate_8h_source.xhtml#l00071">Validate.h:71</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 S32 per channel</div></div> |
| <div class="ttc" id="_n_e_crop_kernel_8h_xhtml"><div class="ttname"><a href="_n_e_crop_kernel_8h.xhtml">NECropKernel.h</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="_c_p_p_2_validate_8h_xhtml"><div class="ttname"><a href="_c_p_p_2_validate_8h.xhtml">Validate.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::Format::U32</a></div><div class="ttdoc">1 channel, 1 U32 per channel</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_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="_shape_calculator_8h_xhtml"><div class="ttname"><a href="_shape_calculator_8h.xhtml">ShapeCalculator.h</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_1_1wrapper_xhtml_a2902775707bc7bf7d6da1bda1cc15783"><div class="ttname"><a href="namespacearm__compute_1_1wrapper.xhtml#a2902775707bc7bf7d6da1bda1cc15783">arm_compute::wrapper::vgetlow</a></div><div class="ttdeci">uint8x8_t vgetlow(const uint8x16_t val)</div><div class="ttdef"><b>Definition:</b> <a href="getlow_8h_source.xhtml#l00039">getlow.h:39</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_crop_kernel_xhtml_a0da66c75715e5f334da280799a55c923"><div class="ttname"><a href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a0da66c75715e5f334da280799a55c923">arm_compute::NECropKernel::configure_output_shape</a></div><div class="ttdeci">void configure_output_shape()</div><div class="ttdoc">Configure output tensor's shape as this can only be determined at runtime.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_crop_kernel_8cpp_source.xhtml#l00296">NECropKernel.cpp:296</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1wrapper_xhtml_a1598e7eb12a58fc53559332cd0c3ab6f"><div class="ttname"><a href="namespacearm__compute_1_1wrapper.xhtml#a1598e7eb12a58fc53559332cd0c3ab6f">arm_compute::wrapper::vcombine</a></div><div class="ttdeci">uint8x16_t vcombine(const uint8x8_t &a, const uint8x8_t &b)</div><div class="ttdef"><b>Definition:</b> <a href="combine_8h_source.xhtml#l00039">combine.h:39</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_crop_kernel_xhtml_a112b35dd205c62ea6ed1447ef226da82"><div class="ttname"><a href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a112b35dd205c62ea6ed1447ef226da82">arm_compute::NECropKernel::run</a></div><div class="ttdeci">void run(const Window &window, const ThreadInfo &info) override</div><div class="ttdoc">Execute the kernel on the passed window.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_crop_kernel_8cpp_source.xhtml#l00386">NECropKernel.cpp:386</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_crop_kernel_xhtml_a0b1369db011f9d5603d2f6ab4bab8548"><div class="ttname"><a href="classarm__compute_1_1_n_e_crop_kernel.xhtml#a0b1369db011f9d5603d2f6ab4bab8548">arm_compute::NECropKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *crop_boxes, const ITensorInfo *box_ind, const ITensorInfo *output, uint32_t crop_box_ind=0, float extrapolation_value=0)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLStridedSliceKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_crop_kernel_8cpp_source.xhtml#l00275">NECropKernel.cpp:275</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::Format::S16</a></div><div class="ttdoc">1 channel, 1 S16 per channel</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1wrapper_xhtml_a95ee388aa7c5bccab918235dc538a6b3"><div class="ttname"><a href="namespacearm__compute_1_1wrapper.xhtml#a95ee388aa7c5bccab918235dc538a6b3">arm_compute::wrapper::vgethigh</a></div><div class="ttdeci">uint8x8_t vgethigh(const uint8x16_t val)</div><div class="ttdef"><b>Definition:</b> <a href="gethigh_8h_source.xhtml#l00039">gethigh.h:39</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a921b705e9e3e0fe928928447869e62a5"><div class="ttname"><a href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00161">Validate.h:161</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_thread_info_xhtml"><div class="ttname"><a href="structarm__compute_1_1_thread_info.xhtml">arm_compute::ThreadInfo</a></div><div class="ttdoc">Information about executing thread and CPU.</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_types_8h_source.xhtml#l00225">CPPTypes.h:225</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a18064e0011c3869d884653e9e7c47b66"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">arm_compute::ITensorInfo::total_size</a></div><div class="ttdeci">virtual size_t total_size() const =0</div><div class="ttdoc">Returns the total size of the tensor in bytes.</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_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::DataLayout::NHWC</a></div><div class="ttdoc">Num samples, height, width, channels.</div></div> |
| <div class="ttc" id="namespacearm__compute_1_1wrapper_xhtml_aa7a641703a9c98932d775d915bf7a3e5"><div class="ttname"><a href="namespacearm__compute_1_1wrapper.xhtml#aa7a641703a9c98932d775d915bf7a3e5">arm_compute::wrapper::vrev64</a></div><div class="ttdeci">uint8x8_t vrev64(const uint8x8_t &a)</div><div class="ttdef"><b>Definition:</b> <a href="rev64_8h_source.xhtml#l00039">rev64.h:39</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1wrapper_xhtml_ae1a6f6dde14fc3b0470cd0b08041ea9f"><div class="ttname"><a href="namespacearm__compute_1_1wrapper.xhtml#ae1a6f6dde14fc3b0470cd0b08041ea9f">arm_compute::wrapper::vload</a></div><div class="ttdeci">uint8x8_t vload(const uint8_t *ptr)</div><div class="ttdef"><b>Definition:</b> <a href="load_8h_source.xhtml#l00039">load.h:39</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1wrapper_xhtml_ae7943ea9c1f74dc72c62d4cc3966a459"><div class="ttname"><a href="namespacearm__compute_1_1wrapper.xhtml#ae7943ea9c1f74dc72c62d4cc3966a459">arm_compute::wrapper::vstore</a></div><div class="ttdeci">void vstore(uint8_t *ptr, uint8x8_t val)</div><div class="ttdef"><b>Definition:</b> <a href="store_8h_source.xhtml#l00039">store.h:39</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1wrapper_xhtml_a39e87435be178fba49b76f49426ef873"><div class="ttname"><a href="namespacearm__compute_1_1wrapper.xhtml#a39e87435be178fba49b76f49426ef873">arm_compute::wrapper::vdup_n</a></div><div class="ttdeci">uint8x8_t vdup_n(uint8_t value, traits::vector_64_tag)</div><div class="ttdef"><b>Definition:</b> <a href="dup__n_8h_source.xhtml#l00041">dup_n.h:41</a></div></div> |
| <div class="ttc" id="bit__ops_8h_xhtml"><div class="ttname"><a href="bit__ops_8h.xhtml">bit_ops.h</a></div></div> |
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| <div class="ttc" id="_validate_8h_xhtml_a7e906bfc9e333e3f967d8ee9353ce001"><div class="ttname"><a href="_validate_8h.xhtml#a7e906bfc9e333e3f967d8ee9353ce001">ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(t,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00745">Validate.h:745</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="_validate_8h_xhtml_a6eb9ce82815fe429250189da7592ba75"><div class="ttname"><a href="_validate_8h.xhtml#a6eb9ce82815fe429250189da7592ba75">ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00205">Validate.h:205</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="_validate_8h_xhtml_a1b35b0d258183cf9ef36adf684d0b88c"><div class="ttname"><a href="_validate_8h.xhtml#a1b35b0d258183cf9ef36adf684d0b88c">ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00940">Validate.h:940</a></div></div> |
| <div class="ttc" id="_i_access_window_8h_xhtml"><div class="ttname"><a href="_i_access_window_8h.xhtml">IAccessWindow.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_ac394d6570ab3325810a3532d39091a52"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#ac394d6570ab3325810a3532d39091a52">arm_compute::ITensorInfo::has_padding</a></div><div class="ttdeci">virtual bool has_padding() const =0</div><div class="ttdoc">Checks if the tensor has been allocated with padding or not.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_n_e_crop_kernel_xhtml_ad8887523c29f0065e3557ca800c4b042"><div class="ttname"><a href="classarm__compute_1_1_n_e_crop_kernel.xhtml#ad8887523c29f0065e3557ca800c4b042">arm_compute::NECropKernel::NECropKernel</a></div><div class="ttdeci">NECropKernel()</div><div class="ttdoc">Default constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_n_e_crop_kernel_8cpp_source.xhtml#l00231">NECropKernel.cpp:231</a></div></div> |
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