| <a href="_detection_post_process_layer_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <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="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include "<a class="code" href="_c_p_p_detection_post_process_layer_8h.xhtml">arm_compute/runtime/CPP/functions/CPPDetectionPostProcessLayer.h</a>"</span></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include "<a class="code" href="runtime_2_tensor_8h.xhtml">arm_compute/runtime/Tensor.h</a>"</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "<a class="code" href="_tensor_allocator_8h.xhtml">arm_compute/runtime/TensorAllocator.h</a>"</span></div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_accessor_8h.xhtml">tests/NEON/Accessor.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include "<a class="code" href="_padding_calculator_8h.xhtml">tests/PaddingCalculator.h</a>"</span></div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include "tests/datasets/ShapeDatasets.h"</span></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include "<a class="code" href="_asserts_8h.xhtml">tests/framework/Asserts.h</a>"</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="preprocessor">#include "<a class="code" href="tests_2framework_2_macros_8h.xhtml">tests/framework/Macros.h</a>"</span></div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="preprocessor">#include "<a class="code" href="_datasets_8h.xhtml">tests/framework/datasets/Datasets.h</a>"</span></div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="preprocessor">#include "<a class="code" href="_validation_8h.xhtml">tests/validation/Validation.h</a>"</span></div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="keyword">namespace </span>test</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>validation</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> U, <span class="keyword">typename</span> T></div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(U &&tensor, <span class="keyword">const</span> std::vector<T> &v)</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>  std::memcpy(tensor.data(), v.data(), <span class="keyword">sizeof</span>(T) * v.size());</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span> }</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="keyword">template</span> <<span class="keyword">typename</span> U, <span class="keyword">typename</span> T></div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> quantize_and_fill_tensor(U &&tensor, <span class="keyword">const</span> std::vector<T> &v)</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span> {</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  QuantizationInfo qi = tensor.quantization_info();</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  std::vector<uint8_t> quantized;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  quantized.reserve(v.size());</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="keywordflow">for</span>(<span class="keyword">auto</span> elem : v)</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>  quantized.emplace_back(<a class="code" href="namespacearm__compute.xhtml#a25591070cf041aff512719050c39e5ee">quantize_qasymm8</a>(elem, qi));</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  }</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  std::memcpy(tensor.data(), quantized.data(), <span class="keyword">sizeof</span>(uint8_t) * quantized.size());</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span> }</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="keyword">inline</span> QuantizationInfo qinfo_scaleoffset_from_minmax(<span class="keyword">const</span> <span class="keywordtype">float</span> min, <span class="keyword">const</span> <span class="keywordtype">float</span> max)</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="keywordtype">int</span> <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> = 0;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordtype">float</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a> = 0;</div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">const</span> uint8_t qmin = std::numeric_limits<uint8_t>::min();</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keyword">const</span> uint8_t qmax = std::numeric_limits<uint8_t>::max();</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> f_qmin = qmin;</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> f_qmax = qmax;</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> </div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="comment">// Continue only if [min,max] is a valid range and not a point</span></div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordflow">if</span>(min != max)</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  {</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a> = (max - min) / (f_qmax - f_qmin);</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> offset_from_min = f_qmin - min / <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>;</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> offset_from_max = f_qmax - max / <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>;</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> offset_from_min_error = std::abs(f_qmin) + std::abs(min / <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>);</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> offset_from_max_error = std::abs(f_qmax) + std::abs(max / <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>);</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> f_offset = offset_from_min_error < offset_from_max_error ? offset_from_min : offset_from_max;</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>  uint8_t uint8_offset = 0;</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordflow">if</span>(f_offset < f_qmin)</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  {</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  uint8_offset = qmin;</div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  }</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(f_offset > f_qmax)</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  {</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  uint8_offset = qmax;</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  }</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  {</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  uint8_offset = static_cast<uint8_t>(<a class="code" href="namespacearm__compute.xhtml#aaae2b6b1c3f4404121346a4c27b22647">std::round</a>(f_offset));</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  }</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> = uint8_offset;</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="keywordflow">return</span> QuantizationInfo(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acec6d8ad52a28972fa74e071c1a63b6a">scale</a>, <a class="code" href="src_2core_2_c_l_2cl__kernels_2_helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>);</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> }</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9dfdc68c1d13830a59d12d7c9866e228">base_test_case</a>(DetectionPostProcessLayerInfo <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, <span class="keyword">const</span> SimpleTensor<float> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>,</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="keyword">const</span> SimpleTensor<float> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, <span class="keyword">const</span> SimpleTensor<float> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, <span class="keyword">const</span> SimpleTensor<float> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>,</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  AbsoluteTolerance<float> tolerance_boxes = AbsoluteTolerance<float>(0.1f), AbsoluteTolerance<float> tolerance_others = AbsoluteTolerance<float>(0.1f))</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span> {</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  Tensor box_encoding = create_tensor<Tensor>(TensorShape(4U, 6U, 1U), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, 1, qinfo_scaleoffset_from_minmax(-1.0f, 1.0f));</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  Tensor class_prediction = create_tensor<Tensor>(TensorShape(3U, 6U, 1U), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, 1, qinfo_scaleoffset_from_minmax(0.0f, 1.0f));</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  Tensor anchors = create_tensor<Tensor>(TensorShape(4U, 6U), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a>, 1, qinfo_scaleoffset_from_minmax(0.0f, 100.5f));</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  box_encoding.allocator()->allocate();</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  class_prediction.allocator()->allocate();</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  anchors.allocator()->allocate();</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>  std::vector<float> box_encoding_vector =</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  {</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  0.0f, 1.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  0.0f, -1.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  0.0f, 0.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  0.0f, 1.0f, 0.0f, 0.0f,</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  0.0f, 0.0f, 0.0f, 0.0f</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  };</div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  std::vector<float> class_prediction_vector =</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  {</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  0.0f, 0.7f, 0.68f,</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  0.0f, 0.6f, 0.5f,</div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  0.0f, 0.9f, 0.83f,</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  0.0f, 0.91f, 0.97f,</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  0.0f, 0.5f, 0.4f,</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  0.0f, 0.31f, 0.22f</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  };</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  std::vector<float> anchors_vector =</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  {</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  0.4f, 0.4f, 1.1f, 1.1f,</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  0.4f, 0.4f, 1.1f, 1.1f,</div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  0.4f, 0.4f, 1.1f, 1.1f,</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  0.4f, 10.4f, 1.1f, 1.1f,</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  0.4f, 10.4f, 1.1f, 1.1f,</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  0.4f, 100.4f, 1.1f, 1.1f</div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  };</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="comment">// Fill the tensors with random pre-generated values</span></div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a5f5b6c4337eac9e2e0046ca2304d80dc">data_type</a> == <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  {</div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(Accessor(box_encoding), box_encoding_vector);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(Accessor(class_prediction), class_prediction_vector);</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(Accessor(anchors), anchors_vector);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  }</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  {</div><div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  quantize_and_fill_tensor(Accessor(box_encoding), box_encoding_vector);</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  quantize_and_fill_tensor(Accessor(class_prediction), class_prediction_vector);</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  quantize_and_fill_tensor(Accessor(anchors), anchors_vector);</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  }</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span> </div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="comment">// Determine the output through the CPP kernel</span></div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  Tensor output_boxes;</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  Tensor output_classes;</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  Tensor output_scores;</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  Tensor num_detection;</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  CPPDetectionPostProcessLayer detection;</div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  detection.configure(&box_encoding, &class_prediction, &anchors, &output_boxes, &output_classes, &output_scores, &num_detection, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>);</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>  output_boxes.allocator()->allocate();</div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  output_classes.allocator()->allocate();</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  output_scores.allocator()->allocate();</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  num_detection.allocator()->allocate();</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span> </div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="comment">// Run the kernel</span></div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  detection.run();</div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="comment">// Validate against the expected output</span></div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="comment">// Validate output boxes</span></div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae02c6fc90d9c60c634bfa258049eb46b">validate</a>(Accessor(output_boxes), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, tolerance_boxes);</div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="comment">// Validate detection classes</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae02c6fc90d9c60c634bfa258049eb46b">validate</a>(Accessor(output_classes), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, tolerance_others);</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="comment">// Validate detection scores</span></div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae02c6fc90d9c60c634bfa258049eb46b">validate</a>(Accessor(output_scores), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, tolerance_others);</div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="comment">// Validate num detections</span></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae02c6fc90d9c60c634bfa258049eb46b">validate</a>(Accessor(num_detection), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>, tolerance_others);</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="comment">// namespace</span></div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span> </div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8f65156abdd90180036790221cfc915f">TEST_SUITE</a>(CPP)</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8f65156abdd90180036790221cfc915f">TEST_SUITE</a>(DetectionPostProcessLayer)</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span> </div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span> <span class="comment">// *INDENT-OFF*</span></div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span> <span class="comment">// clang-format off</span></div><div class="line"><a name="l00186"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9319d62cd0f2627f92929d302d685f38"> 186</a></span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1f1266d183bfb4d479ec334fed85dc27">DATA_TEST_CASE</a>(Validate, framework::<a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cf">DatasetMode</a>::ALL, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a96f9e78d0c2a93f0e3a876eeae4be4b0">zip</a>(</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  framework::dataset::<a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">make</a>("BoxEncodingsInfo", { <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 3U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>), <span class="comment">// Mismatching batch_size</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">DataType::S8</a>), <span class="comment">// Unsupported data type</span></div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>), <span class="comment">// Wrong Detection Info</span></div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>), <span class="comment">// Wrong boxes dimensions</span></div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>)}), <span class="comment">// Wrong score dimension </span></div><div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"ClassPredsInfo"</span>,{ <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U ,10U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U ,10U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U ,10U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U ,10U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U ,10U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U ,10U), 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>)})),</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"AnchorsInfo"</span>,{ <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 10U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>)})),</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"OutputBoxInfo"</span>, { TensorInfo(TensorShape(4U, 3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  TensorInfo(TensorShape(4U, 3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  TensorInfo(TensorShape(4U, 3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">DataType::S8</a>),</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  TensorInfo(TensorShape(4U, 3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  TensorInfo(TensorShape(1U, 5U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  TensorInfo(TensorShape(4U, 3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)})),</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"OuputClassesInfo"</span>,{ TensorInfo(TensorShape(3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  TensorInfo(TensorShape(3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  TensorInfo(TensorShape(3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  TensorInfo(TensorShape(3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  TensorInfo(TensorShape(3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  TensorInfo(TensorShape(6U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)})),</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"OutputScoresInfo"</span>,{ TensorInfo(TensorShape(3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  TensorInfo(TensorShape(3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  TensorInfo(TensorShape(3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  TensorInfo(TensorShape(3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  TensorInfo(TensorShape(3U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  TensorInfo(TensorShape(6U, 1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)})),</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"NumDetectionsInfo"</span>,{ TensorInfo(TensorShape(1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  TensorInfo(TensorShape(1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  TensorInfo(TensorShape(1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  TensorInfo(TensorShape(1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  TensorInfo(TensorShape(1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>),</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  TensorInfo(TensorShape(1U), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>)})),</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"DetectionPostProcessLayerInfo"</span>,{ DetectionPostProcessLayerInfo(3, 1, 0.0f, 0.5f, 2, {0.1f,0.1f,0.1f,0.1f}),</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  DetectionPostProcessLayerInfo(3, 1, 0.0f, 0.5f, 2, {0.1f,0.1f,0.1f,0.1f}),</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  DetectionPostProcessLayerInfo(3, 1, 0.0f, 0.5f, 2, {0.1f,0.1f,0.1f,0.1f}),</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  DetectionPostProcessLayerInfo(3, 1, 0.0f, 1.5f, 2, {0.0f,0.1f,0.1f,0.1f}),</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  DetectionPostProcessLayerInfo(3, 1, 0.0f, 0.5f, 2, {0.1f,0.1f,0.1f,0.1f}),</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  DetectionPostProcessLayerInfo(3, 1, 0.0f, 0.5f, 2, {0.1f,0.1f,0.1f,0.1f})})),</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  <a class="code" href="namespacearm__compute_1_1test_1_1framework_1_1dataset.xhtml#a352791fb808d42a82ad70df5efa3508b">framework::dataset::make</a>(<span class="stringliteral">"Expected"</span>, {<span class="keyword">true</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span>, <span class="keyword">false</span> })),</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  box_encodings_info, classes_info, anchors_info, output_boxes_info, output_classes_info,output_scores_info, num_detection_info, detect_info, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa6e67bddae371a5731f6d4002e787299">expected</a>)</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> {</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="keyword">const</span> Status status = <a class="code" href="classarm__compute_1_1_c_p_p_detection_post_process_layer.xhtml#a08744faa3f68379fa82bcbd96bbec691">CPPDetectionPostProcessLayer::validate</a>(&box_encodings_info.clone()->set_is_resizable(<span class="keyword">false</span>),</div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  &classes_info.clone()->set_is_resizable(<span class="keyword">false</span>),</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  &anchors_info.clone()->set_is_resizable(<span class="keyword">false</span>),</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  &output_boxes_info.clone()->set_is_resizable(<span class="keyword">false</span>),</div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  &output_classes_info.clone()->set_is_resizable(<span class="keyword">false</span>),</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  &output_scores_info.clone()->set_is_resizable(<span class="keyword">false</span>), &num_detection_info.clone()->set_is_resizable(<span class="keyword">false</span>), detect_info);</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a3c8562a1f05d23f44aed87545b7892cf">ARM_COMPUTE_EXPECT</a>(<span class="keywordtype">bool</span>(status) == <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa6e67bddae371a5731f6d4002e787299">expected</a>, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#aca1fd1d8935433e6ba2e3918214e07f9a6f3a603fac4d817f1848c3173b243b57">framework::LogLevel::ERRORS</a>);</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span> }</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> <span class="comment">// clang-format on</span></div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span> <span class="comment">// *INDENT-ON*</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span> </div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8f65156abdd90180036790221cfc915f">TEST_SUITE</a>(F32)</div><div class="line"><a name="l00250"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7ca22e688d555d293fe43151a90e7c48"> 250</a></span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a963c5b8a3279186004d6a7e97a1b87e6">TEST_CASE</a>(Float_general, framework::<a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cf">DatasetMode</a>::ALL)</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> {</div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a> = <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a>(3 <span class="comment">/*max_detections*/</span>, 1 <span class="comment">/*max_classes_per_detection*/</span>, 0.0 <span class="comment">/*nms_score_threshold*/</span>,</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  0.5 <span class="comment">/*nms_iou_threshold*/</span>, 2 <span class="comment">/*num_classes*/</span>, { 11.0, 11.0, 6.0, 6.0 } <span class="comment">/*scale*/</span>);</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="comment">// Fill expected detection boxes</span></div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, std::vector<float> { -0.15, 9.85, 0.95, 10.95, -0.15, -0.15, 0.95, 0.95, -0.15, 99.85, 0.95, 100.95 });</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="comment">// Fill expected detection classes</span></div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, std::vector<float> { 1.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="comment">// Fill expected detection scores</span></div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, std::vector<float> { 0.97f, 0.95f, 0.31f });</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  <span class="comment">// Fill expected num detections</span></div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>, std::vector<float> { 3.f });</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="comment">// Run base test</span></div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9dfdc68c1d13830a59d12d7c9866e228">base_test_case</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>);</div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span> }</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> </div><div class="line"><a name="l00270"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa48337dd40db1668cf0936031321fae2"> 270</a></span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a963c5b8a3279186004d6a7e97a1b87e6">TEST_CASE</a>(Float_fast, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>)</div><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> {</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a> = <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a>(3 <span class="comment">/*max_detections*/</span>, 1 <span class="comment">/*max_classes_per_detection*/</span>, 0.0 <span class="comment">/*nms_score_threshold*/</span>,</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  0.5 <span class="comment">/*nms_iou_threshold*/</span>, 2 <span class="comment">/*num_classes*/</span>, { 11.0, 11.0, 6.0, 6.0 } <span class="comment">/*scale*/</span>,</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keyword">false</span> <span class="comment">/*use_regular_nms*/</span>, 1 <span class="comment">/*detections_per_class*/</span>);</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span> </div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <span class="comment">// Fill expected detection boxes</span></div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, std::vector<float> { -0.15, 9.85, 0.95, 10.95, -0.15, -0.15, 0.95, 0.95, -0.15, 99.85, 0.95, 100.95 });</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <span class="comment">// Fill expected detection classes</span></div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, std::vector<float> { 1.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="comment">// Fill expected detection scores</span></div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, std::vector<float> { 0.97f, 0.95f, 0.31f });</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="comment">// Fill expected num detections</span></div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>, std::vector<float> { 3.f });</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span> </div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="comment">// Run base test</span></div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9dfdc68c1d13830a59d12d7c9866e228">base_test_case</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>);</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span> }</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> </div><div class="line"><a name="l00293"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad50764661260515531306518b912451c"> 293</a></span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a963c5b8a3279186004d6a7e97a1b87e6">TEST_CASE</a>(Float_regular, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</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>  <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a> = <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a>(3 <span class="comment">/*max_detections*/</span>, 1 <span class="comment">/*max_classes_per_detection*/</span>, 0.0 <span class="comment">/*nms_score_threshold*/</span>,</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  0.5 <span class="comment">/*nms_iou_threshold*/</span>, 2 <span class="comment">/*num_classes*/</span>, { 11.0, 11.0, 6.0, 6.0 } <span class="comment">/*scale*/</span>,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keyword">true</span> <span class="comment">/*use_regular_nms*/</span>, 1 <span class="comment">/*detections_per_class*/</span>);</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span> </div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="comment">// Fill expected detection boxes</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, std::vector<float> { -0.15, 9.85, 0.95, 10.95, -0.15, 9.85, 0.95, 10.95, 0.0f, 0.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="comment">// Fill expected detection classes</span></div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, std::vector<float> { 1.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="comment">// Fill expected detection scores</span></div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, std::vector<float> { 0.97f, 0.91f, 0.0f });</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="comment">// Fill expected num detections</span></div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>, std::vector<float> { 2.f });</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>  <span class="comment">// Run test</span></div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9dfdc68c1d13830a59d12d7c9866e228">base_test_case</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>);</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span> }</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ed31007ae463a3cec24a581f3651f6">TEST_SUITE_END</a>() <span class="comment">// F32</span></div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span> </div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8f65156abdd90180036790221cfc915f">TEST_SUITE</a>(QASYMM8)</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a963c5b8a3279186004d6a7e97a1b87e6">TEST_CASE</a>(Quantized_general, framework::<a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cf">DatasetMode</a>::ALL)</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span> {</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a> = <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a>(3 <span class="comment">/*max_detections*/</span>, 1 <span class="comment">/*max_classes_per_detection*/</span>, 0.0 <span class="comment">/*nms_score_threshold*/</span>,</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  0.5 <span class="comment">/*nms_iou_threshold*/</span>, 2 <span class="comment">/*num_classes*/</span>, { 11.0, 11.0, 6.0, 6.0 } <span class="comment">/*scale*/</span>);</div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span> </div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="comment">// Fill expected detection boxes</span></div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  SimpleTensor<float> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, std::vector<float> { -0.15, 9.85, 0.95, 10.95, -0.15, -0.15, 0.95, 0.95, -0.15, 99.85, 0.95, 100.95 });</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="comment">// Fill expected detection classes</span></div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  SimpleTensor<float> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>(TensorShape(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, std::vector<float> { 1.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="comment">// Fill expected detection scores</span></div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  SimpleTensor<float> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>(TensorShape(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, std::vector<float> { 0.97f, 0.95f, 0.31f });</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="comment">// Fill expected num detections</span></div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  SimpleTensor<float> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>(TensorShape(1U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>, std::vector<float> { 3.f });</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="comment">// Run test</span></div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9dfdc68c1d13830a59d12d7c9866e228">base_test_case</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>, AbsoluteTolerance<float>(0.3f));</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span> }</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span> </div><div class="line"><a name="l00339"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9260a33ddeffba2e07266fbb3637a3ae"> 339</a></span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a963c5b8a3279186004d6a7e97a1b87e6">TEST_CASE</a>(Quantized_fast, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>)</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span> {</div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a> = <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a>(3 <span class="comment">/*max_detections*/</span>, 1 <span class="comment">/*max_classes_per_detection*/</span>, 0.0 <span class="comment">/*nms_score_threshold*/</span>,</div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  0.5 <span class="comment">/*nms_iou_threshold*/</span>, 2 <span class="comment">/*num_classes*/</span>, { 11.0, 11.0, 6.0, 6.0 } <span class="comment">/*scale*/</span>,</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keyword">false</span> <span class="comment">/*use_regular_nms*/</span>, 1 <span class="comment">/*detections_per_class*/</span>);</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span> </div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="comment">// Fill expected detection boxes</span></div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, std::vector<float> { -0.15, 9.85, 0.95, 10.95, -0.15, -0.15, 0.95, 0.95, -0.15, 99.85, 0.95, 100.95 });</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="comment">// Fill expected detection classes</span></div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, std::vector<float> { 1.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="comment">// Fill expected detection scores</span></div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, std::vector<float> { 0.97f, 0.95f, 0.31f });</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="comment">// Fill expected num detections</span></div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>, std::vector<float> { 3.f });</div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span> </div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="comment">// Run base test</span></div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9dfdc68c1d13830a59d12d7c9866e228">base_test_case</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>, <a class="code" href="classarm__compute_1_1test_1_1validation_1_1_absolute_tolerance.xhtml">AbsoluteTolerance<float></a>(0.3f));</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span> }</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span> </div><div class="line"><a name="l00362"></a><span class="lineno"><a class="line" href="namespacearm__compute_1_1test_1_1validation.xhtml#a30e25cce747f33c33a9c1ff54d0caa93"> 362</a></span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a963c5b8a3279186004d6a7e97a1b87e6">TEST_CASE</a>(Quantized_regular, <a class="code" href="namespacearm__compute_1_1test_1_1framework.xhtml#a7edf31944a6144ffd493d2f9a7bfb5cfa5fb1f955b45e38e31789286a1790398d">framework::DatasetMode::ALL</a>)</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> {</div><div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a> = <a class="code" href="classarm__compute_1_1_detection_post_process_layer_info.xhtml">DetectionPostProcessLayerInfo</a>(3 <span class="comment">/*max_detections*/</span>, 1 <span class="comment">/*max_classes_per_detection*/</span>, 0.0 <span class="comment">/*nms_score_threshold*/</span>,</div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  0.5 <span class="comment">/*nms_iou_threshold*/</span>, 2 <span class="comment">/*num_classes*/</span>, { 11.0, 11.0, 6.0, 6.0 } <span class="comment">/*scale*/</span>,</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="keyword">true</span> <span class="comment">/*use_regular_nms*/</span>, 1 <span class="comment">/*detections_per_class*/</span>);</div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="comment">// Fill expected detection boxes</span></div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(4U, 3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, std::vector<float> { -0.15, 9.85, 0.95, 10.95, -0.15, 9.85, 0.95, 10.95, 0.0f, 0.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  <span class="comment">// Fill expected detection classes</span></div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, std::vector<float> { 1.0f, 0.0f, 0.0f });</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="comment">// Fill expected detection scores</span></div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(3U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, std::vector<float> { 0.95f, 0.91f, 0.0f });</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="comment">// Fill expected num detections</span></div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  <a class="code" href="classarm__compute_1_1test_1_1_simple_tensor.xhtml">SimpleTensor<float></a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1U), <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>);</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a0f11d0a0280334ed2501740d7dfc33e5">fill_tensor</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>, std::vector<float> { 2.f });</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>  <span class="comment">// Run test</span></div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9dfdc68c1d13830a59d12d7c9866e228">base_test_case</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6bc71733081deeb08c66a3d6555f83eb">expected_output_boxes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a319e01e1e700275035e56af9ba050157">expected_output_classes</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#acb121e28a17ace0117bbfbae307ad745">expected_output_scores</a>, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a12958d8604dbb3ebe6669a5090b0368a">expected_num_detection</a>, <a class="code" href="classarm__compute_1_1test_1_1validation_1_1_absolute_tolerance.xhtml">AbsoluteTolerance<float></a>(0.3f));</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> </div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ed31007ae463a3cec24a581f3651f6">TEST_SUITE_END</a>() <span class="comment">// QASYMM8</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"> 386</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ed31007ae463a3cec24a581f3651f6">TEST_SUITE_END</a>() <span class="comment">// DetectionPostProcessLayer</span></div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac2ed31007ae463a3cec24a581f3651f6">TEST_SUITE_END</a>() <span class="comment">// CPP</span></div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span> } <span class="comment">// namespace validation</span></div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span> } <span class="comment">// namespace test</span></div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span> } <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="_accessor_8h_xhtml"><div class="ttname"><a href="_accessor_8h.xhtml">Accessor.h</a></div></div> |
