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| <div class="title">CLGenerateProposalsLayer.cpp</div> </div> |
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| <a href="_c_l_generate_proposals_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="_c_l_generate_proposals_layer_8h.xhtml">arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h</a>"</span></div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> </div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include "<a class="code" href="_i_c_l_tensor_8h.xhtml">arm_compute/core/CL/ICLTensor.h</a>"</span></div><div class="line"><a name="l00027"></a><span class="lineno"> 27</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="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "<a class="code" href="_toolchain_support_8h.xhtml">support/ToolchainSupport.h</a>"</span></div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span> </div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="keyword">namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a></div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span> {</div><div class="line"><a name="l00032"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a5238a3faae0338e0f8cba6d62e1ad94e"> 32</a></span> <a class="code" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a5238a3faae0338e0f8cba6d62e1ad94e">CLGenerateProposalsLayer::CLGenerateProposalsLayer</a>(std::shared_ptr<IMemoryManager> memory_manager)</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span>  : _memory_group(memory_manager),</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  _permute_deltas_kernel(),</div><div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  _flatten_deltas_kernel(),</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  _permute_scores_kernel(),</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  _flatten_scores_kernel(),</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  _compute_anchors_kernel(),</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  _bounding_box_kernel(),</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  _pad_kernel(),</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  _dequantize_anchors(),</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  _dequantize_deltas(),</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  _quantize_all_proposals(),</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  _cpp_nms(memory_manager),</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  _is_nhwc(false),</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  _is_qasymm8(false),</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  _deltas_permuted(),</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  _deltas_flattened(),</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  _deltas_flattened_f32(),</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  _scores_permuted(),</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  _scores_flattened(),</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  _all_anchors(),</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  _all_anchors_f32(),</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  _all_proposals(),</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  _all_proposals_quantized(),</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  _keeps_nms_unused(),</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  _classes_nms_unused(),</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  _proposals_4_roi_values(),</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  _all_proposals_to_use(nullptr),</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  _num_valid_proposals(nullptr),</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  _scores_out(nullptr)</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> }</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a01a8a849ea1f7fb96263093b7d6978a9"> 65</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a01a8a849ea1f7fb96263093b7d6978a9">CLGenerateProposalsLayer::configure</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *scores, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *deltas, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *anchors, <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *proposals, <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *scores_out, <a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml">ICLTensor</a> *num_valid_proposals,</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_generate_proposals_info.xhtml">GenerateProposalsInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>)</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span> {</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <a class="code" href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a>(scores, deltas, anchors, proposals, scores_out, num_valid_proposals);</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a>(<a class="code" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a0dd15c751cbdd5768cb781ef766e50dd">CLGenerateProposalsLayer::validate</a>(scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), deltas-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), anchors-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), proposals-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), scores_out-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), num_valid_proposals-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>));</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span> </div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  _is_nhwc = scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>() == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> scores_data_type = scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>();</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  _is_qasymm8 = scores_data_type == <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>;</div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> num_anchors = scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(<a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">DataLayoutDimension::CHANNEL</a>));</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> feat_width = scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(<a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>));</div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> feat_height = scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(<a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>));</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> total_num_anchors = num_anchors * feat_width * feat_height;</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> pre_nms_topN = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.pre_nms_topN();</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> post_nms_topN = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.post_nms_topN();</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> values_per_roi = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.values_per_roi();</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> </div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> scores_qinfo = scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>();</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keyword">const</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> rois_data_type = (_is_qasymm8) ? <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a3b989c6b5398b3b9538ad103a324205e">DataType::QASYMM16</a> : scores_data_type;</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a> rois_qinfo = (_is_qasymm8) ? <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a>(0.125f, 0) : scores-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>();</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="comment">// Compute all the anchors</span></div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_all_anchors);</div><div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  _compute_anchors_kernel.<a class="code" href="classarm__compute_1_1_c_l_compute_all_anchors_kernel.xhtml#a4475c404f4bc3140b493a987d1fa0fc6">configure</a>(anchors, &_all_anchors, <a class="code" href="classarm__compute_1_1_compute_anchors_info.xhtml">ComputeAnchorsInfo</a>(feat_width, feat_height, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.spatial_scale()));</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="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> flatten_shape_deltas(values_per_roi, total_num_anchors);</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  _deltas_flattened.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(flatten_shape_deltas, 1, scores_data_type, deltas-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>()));</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="comment">// Permute and reshape deltas</span></div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_deltas_flattened);</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordflow">if</span>(!_is_nhwc)</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  {</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_deltas_permuted);</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  _permute_deltas_kernel.<a class="code" href="classarm__compute_1_1_c_l_permute_kernel.xhtml#af1f5e1b7e8bbf0768c406be880387a0d">configure</a>(deltas, &_deltas_permuted, <a class="code" href="classarm__compute_1_1_strides.xhtml">PermutationVector</a>{ 2, 0, 1 });</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  _flatten_deltas_kernel.<a class="code" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml#a074e10cfb217e657b9e81adeca2abc68">configure</a>(&_deltas_permuted, &_deltas_flattened);</div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  _deltas_permuted.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  }</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  {</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  _flatten_deltas_kernel.<a class="code" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml#a074e10cfb217e657b9e81adeca2abc68">configure</a>(deltas, &_deltas_flattened);</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  }</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span> </div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> flatten_shape_scores(1, total_num_anchors);</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  _scores_flattened.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(flatten_shape_scores, 1, scores_data_type, scores_qinfo));</div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span> </div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  <span class="comment">// Permute and reshape scores</span></div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_scores_flattened);</div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordflow">if</span>(!_is_nhwc)</div><div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  {</div><div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_scores_permuted);</div><div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  _permute_scores_kernel.<a class="code" href="classarm__compute_1_1_c_l_permute_kernel.xhtml#af1f5e1b7e8bbf0768c406be880387a0d">configure</a>(scores, &_scores_permuted, <a class="code" href="classarm__compute_1_1_strides.xhtml">PermutationVector</a>{ 2, 0, 1 });</div><div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  _flatten_scores_kernel.<a class="code" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml#a074e10cfb217e657b9e81adeca2abc68">configure</a>(&_scores_permuted, &_scores_flattened);</div><div class="line"><a name="l00117"></a><span class="lineno"> 117</span>  _scores_permuted.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  }</div><div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  {</div><div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  _flatten_scores_kernel.<a class="code" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml#a074e10cfb217e657b9e81adeca2abc68">configure</a>(scores, &_scores_flattened);</div><div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  }</div><div class="line"><a name="l00123"></a><span class="lineno"> 123</span> </div><div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> *anchors_to_use = &_all_anchors;</div><div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  <a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml">CLTensor</a> *deltas_to_use = &_deltas_flattened;</div><div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keywordflow">if</span>(_is_qasymm8)</div><div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  {</div><div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  _all_anchors_f32.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(_all_anchors.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a269b19ce3f357ac65f41f9951906e38e">tensor_shape</a>(), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  _deltas_flattened_f32.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(_deltas_flattened.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a269b19ce3f357ac65f41f9951906e38e">tensor_shape</a>(), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_all_anchors_f32);</div><div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_deltas_flattened_f32);</div><div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="comment">// Dequantize anchors to float</span></div><div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  _dequantize_anchors.<a class="code" href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml#a074e10cfb217e657b9e81adeca2abc68">configure</a>(&_all_anchors, &_all_anchors_f32);</div><div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  _all_anchors.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  anchors_to_use = &_all_anchors_f32;</div><div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="comment">// Dequantize deltas to float</span></div><div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  _dequantize_deltas.<a class="code" href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml#a074e10cfb217e657b9e81adeca2abc68">configure</a>(&_deltas_flattened, &_deltas_flattened_f32);</div><div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  _deltas_flattened.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  deltas_to_use = &_deltas_flattened_f32;</div><div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  }</div><div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  <span class="comment">// Bounding box transform</span></div><div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_all_proposals);</div><div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <a class="code" href="classarm__compute_1_1_bounding_box_transform_info.xhtml">BoundingBoxTransformInfo</a> bbox_info(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.im_width(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.im_height(), 1.f);</div><div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  _bounding_box_kernel.<a class="code" href="classarm__compute_1_1_c_l_bounding_box_transform_kernel.xhtml#ab70ebf089f4e98eaacb33e43122162f2">configure</a>(anchors_to_use, &_all_proposals, deltas_to_use, bbox_info);</div><div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  deltas_to_use-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  anchors_to_use-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</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>  _all_proposals_to_use = &_all_proposals;</div><div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">if</span>(_is_qasymm8)</div><div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  {</div><div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_all_proposals_quantized);</div><div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="comment">// Requantize all_proposals to QASYMM16 with 0.125 scale and 0 offset</span></div><div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  _all_proposals_quantized.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(_all_proposals.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>()-><a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a269b19ce3f357ac65f41f9951906e38e">tensor_shape</a>(), 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a3b989c6b5398b3b9538ad103a324205e">DataType::QASYMM16</a>, <a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a>(0.125f, 0)));</div><div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  _quantize_all_proposals.<a class="code" href="classarm__compute_1_1_c_l_quantization_layer_kernel.xhtml#a074e10cfb217e657b9e81adeca2abc68">configure</a>(&_all_proposals, &_all_proposals_quantized);</div><div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  _all_proposals.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  _all_proposals_to_use = &_all_proposals_quantized;</div><div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  }</div><div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="comment">// The original layer implementation first selects the best pre_nms_topN anchors (thus having a lightweight sort)</span></div><div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">// that are then transformed by bbox_transform. The boxes generated are then fed into a non-sorting NMS operation.</span></div><div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="comment">// Since we are reusing the NMS layer and we don't implement any CL/sort, we let NMS do the sorting (of all the input)</span></div><div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="comment">// and the filtering</span></div><div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> scores_nms_size = std::min<int>(std::min<int>(post_nms_topN, pre_nms_topN), total_num_anchors);</div><div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> min_size_scaled = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.min_size() * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.im_scale();</div><div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_classes_nms_unused);</div><div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_keeps_nms_unused);</div><div class="line"><a name="l00166"></a><span class="lineno"> 166</span> </div><div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="comment">// Note that NMS needs outputs preinitialized.</span></div><div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*scores_out-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(scores_nms_size), 1, scores_data_type, scores_qinfo);</div><div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*_proposals_4_roi_values.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">info</a>(), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi, scores_nms_size), 1, rois_data_type, rois_qinfo);</div><div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <a class="code" href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">auto_init_if_empty</a>(*num_valid_proposals-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>(), <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1), 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>);</div><div class="line"><a name="l00171"></a><span class="lineno"> 171</span> </div><div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="comment">// Initialize temporaries (unused) outputs</span></div><div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  _classes_nms_unused.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(<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>(scores_nms_size), 1, scores_data_type, scores_qinfo));</div><div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  _keeps_nms_unused.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">init</a>(*scores_out-><a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>());</div><div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div><div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  <span class="comment">// Save the output (to map and unmap them at run)</span></div><div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  _scores_out = scores_out;</div><div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  _num_valid_proposals = num_valid_proposals;</div><div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div><div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  _memory_group.<a class="code" href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">manage</a>(&_proposals_4_roi_values);</div><div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  _cpp_nms.<a class="code" href="classarm__compute_1_1_c_p_p_box_with_non_maxima_suppression_limit.xhtml#a014205af76eea5e1ba768fc10b60222a">configure</a>(&_scores_flattened, _all_proposals_to_use, <span class="keyword">nullptr</span>, scores_out, &_proposals_4_roi_values, &_classes_nms_unused, <span class="keyword">nullptr</span>, &_keeps_nms_unused, num_valid_proposals,</div><div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <a class="code" href="classarm__compute_1_1_box_n_m_s_limit_info.xhtml">BoxNMSLimitInfo</a>(0.0f, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.nms_thres(), scores_nms_size, <span class="keyword">false</span>, <a class="code" href="namespacearm__compute.xhtml#a201391f6e13e2a1ac203256a77792718aaac544aacc3615aada24897a215f5046">NMSType::LINEAR</a>, 0.5f, 0.001f, <span class="keyword">true</span>, min_size_scaled, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.im_width(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.im_height()));</div><div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  _keeps_nms_unused.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  _classes_nms_unused.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  _all_proposals_to_use-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  _scores_flattened.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div><div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="comment">// Add the first column that represents the batch id. This will be all zeros, as we don't support multiple images</span></div><div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  _pad_kernel.<a class="code" href="classarm__compute_1_1_c_l_pad_layer_kernel.xhtml#a6f350b775160732d72ab28e01432d6bf">configure</a>(&_proposals_4_roi_values, proposals, <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a>{ { 1, 0 } });</div><div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  _proposals_4_roi_values.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">allocator</a>()-><a class="code" href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">allocate</a>();</div><div class="line"><a name="l00191"></a><span class="lineno"> 191</span> }</div><div class="line"><a name="l00192"></a><span class="lineno"> 192</span> </div><div class="line"><a name="l00193"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a0dd15c751cbdd5768cb781ef766e50dd"> 193</a></span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a> <a class="code" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a0dd15c751cbdd5768cb781ef766e50dd">CLGenerateProposalsLayer::validate</a>(<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *scores, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *deltas, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *anchors, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *proposals, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *scores_out,</div><div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml">ITensorInfo</a> *num_valid_proposals, <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_generate_proposals_info.xhtml">GenerateProposalsInfo</a> &<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>)</div><div class="line"><a name="l00195"></a><span class="lineno"> 195</span> {</div><div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <a class="code" href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a>(scores, deltas, anchors, proposals, scores_out, num_valid_proposals);</div><div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(scores, 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>, <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="_validate_8h.xhtml#a7e906bfc9e333e3f967d8ee9353ce001">ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN</a>(scores, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">DataLayout::NCHW</a>, <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>);</div><div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <a class="code" href="_validate_8h.xhtml#abdb9168800c70e5e2c4c020a3b905738">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT</a>(scores, deltas);</div><div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(scores, deltas);</div><div class="line"><a name="l00201"></a><span class="lineno"> 201</span> </div><div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> num_anchors = scores-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(<a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(scores-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">DataLayoutDimension::CHANNEL</a>));</div><div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> feat_width = scores-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(<a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(scores-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">DataLayoutDimension::WIDTH</a>));</div><div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> feat_height = scores-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(<a class="code" href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">get_data_layout_dimension_index</a>(scores-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>(), <a class="code" href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">DataLayoutDimension::HEIGHT</a>));</div><div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> num_images = scores-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(3);</div><div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> total_num_anchors = num_anchors * feat_width * feat_height;</div><div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> values_per_roi = <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.values_per_roi();</div><div class="line"><a name="l00208"></a><span class="lineno"> 208</span> </div><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> is_qasymm8 = scores-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>() == <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>;</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> </div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(num_images > 1);</div><div class="line"><a name="l00212"></a><span class="lineno"> 212</span> </div><div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="keywordflow">if</span>(is_qasymm8)</div><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  {</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(anchors, 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a3ca8a4ea8f992df3b462bc7b24d097c6">DataType::QSYMM16</a>);</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml">UniformQuantizationInfo</a> anchors_qinfo = anchors-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>().<a class="code" href="classarm__compute_1_1_quantization_info.xhtml#a706fc156bcd4c45441bcaad05884b57d">uniform</a>();</div><div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(anchors_qinfo.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a> != 0.125f);</div><div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  }</div><div class="line"><a name="l00219"></a><span class="lineno"> 219</span> </div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> all_anchors_info(anchors-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi, total_num_anchors)).set_is_resizable(<span class="keyword">true</span>));</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_compute_all_anchors_kernel.xhtml#a3104e859ad98ef70c9d47bbaa5d209e8">CLComputeAllAnchorsKernel::validate</a>(anchors, &all_anchors_info, <a class="code" href="classarm__compute_1_1_compute_anchors_info.xhtml">ComputeAnchorsInfo</a>(feat_width, feat_height, <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.spatial_scale())));</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span> </div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> deltas_permuted_info = deltas-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi * num_anchors, feat_width, feat_height)).set_is_resizable(<span class="keyword">true</span>);</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> scores_permuted_info = scores-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(num_anchors, feat_width, feat_height)).set_is_resizable(<span class="keyword">true</span>);</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keywordflow">if</span>(scores-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">data_layout</a>() == <a class="code" href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">DataLayout::NHWC</a>)</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  {</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <a class="code" href="_validate_8h.xhtml#a27e4638546c88b8916f967e6e54480a9">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES</a>(deltas, &deltas_permuted_info);</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <a class="code" href="_validate_8h.xhtml#a27e4638546c88b8916f967e6e54480a9">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES</a>(scores, &scores_permuted_info);</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  }</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  {</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_permute_kernel.xhtml#a97f09e05a72865753ecb1948b38d4843">CLPermuteKernel::validate</a>(deltas, &deltas_permuted_info, <a class="code" href="classarm__compute_1_1_strides.xhtml">PermutationVector</a>{ 2, 0, 1 }));</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_permute_kernel.xhtml#a97f09e05a72865753ecb1948b38d4843">CLPermuteKernel::validate</a>(scores, &scores_permuted_info, <a class="code" href="classarm__compute_1_1_strides.xhtml">PermutationVector</a>{ 2, 0, 1 }));</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  }</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span> </div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> deltas_flattened_info(deltas-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi, total_num_anchors)).set_is_resizable(<span class="keyword">true</span>));</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">CLReshapeLayerKernel::validate</a>(&deltas_permuted_info, &deltas_flattened_info));</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> </div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> scores_flattened_info(scores-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(1, total_num_anchors)).set_is_resizable(<span class="keyword">true</span>));</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> proposals_4_roi_values(deltas-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi, total_num_anchors)).set_is_resizable(<span class="keyword">true</span>));</div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span> </div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">CLReshapeLayerKernel::validate</a>(&scores_permuted_info, &scores_flattened_info));</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span> </div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> *proposals_4_roi_values_to_use = &proposals_4_roi_values;</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> proposals_4_roi_values_quantized(deltas-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi, total_num_anchors)).set_is_resizable(<span class="keyword">true</span>));</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  proposals_4_roi_values_quantized.<a class="code" href="classarm__compute_1_1_tensor_info.xhtml#a0a9053e6c4729ac5201b58068050c319">set_data_type</a>(<a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a3b989c6b5398b3b9538ad103a324205e">DataType::QASYMM16</a>).<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a575d37eaf8a905c8ca3c0250757c2b81">set_quantization_info</a>(<a class="code" href="classarm__compute_1_1_quantization_info.xhtml">QuantizationInfo</a>(0.125f, 0));</div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="keywordflow">if</span>(is_qasymm8)</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="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> all_anchors_f32_info(anchors-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi, total_num_anchors)).set_is_resizable(<span class="keyword">true</span>).set_data_type(<a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">CLDequantizationLayerKernel::validate</a>(&all_anchors_info, &all_anchors_f32_info));</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_tensor_info.xhtml">TensorInfo</a> deltas_flattened_f32_info(deltas-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi, total_num_anchors)).set_is_resizable(<span class="keyword">true</span>).set_data_type(<a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">CLDequantizationLayerKernel::validate</a>(&deltas_flattened_info, &deltas_flattened_f32_info));</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> </div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a> proposals_4_roi_values_f32(deltas-><a class="code" href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">clone</a>()->set_tensor_shape(<a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>(values_per_roi, total_num_anchors)).set_is_resizable(<span class="keyword">true</span>).set_data_type(<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="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_bounding_box_transform_kernel.xhtml#a174ade6b3a2fe6cf00192a9419514cc1">CLBoundingBoxTransformKernel::validate</a>(&all_anchors_f32_info, &proposals_4_roi_values_f32, &deltas_flattened_f32_info,</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <a class="code" href="classarm__compute_1_1_bounding_box_transform_info.xhtml">BoundingBoxTransformInfo</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.im_width(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.im_height(), 1.f)));</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span> </div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_quantization_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">CLQuantizationLayerKernel::validate</a>(&proposals_4_roi_values_f32, &proposals_4_roi_values_quantized));</div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  proposals_4_roi_values_to_use = &proposals_4_roi_values_quantized;</div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  }</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  {</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_bounding_box_transform_kernel.xhtml#a174ade6b3a2fe6cf00192a9419514cc1">CLBoundingBoxTransformKernel::validate</a>(&all_anchors_info, &proposals_4_roi_values, &deltas_flattened_info,</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  <a class="code" href="classarm__compute_1_1_bounding_box_transform_info.xhtml">BoundingBoxTransformInfo</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.im_width(), <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">info</a>.im_height(), 1.f)));</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  }</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span> </div><div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <a class="code" href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a>(<a class="code" href="classarm__compute_1_1_c_l_pad_layer_kernel.xhtml#a5ab39485b5d0b51df3472895ed0c00a2">CLPadLayerKernel::validate</a>(proposals_4_roi_values_to_use, proposals, <a class="code" href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">PaddingList</a>{ { 1, 0 } }));</div><div class="line"><a name="l00269"></a><span class="lineno"> 269</span> </div><div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="keywordflow">if</span>(num_valid_proposals-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>() > 0)</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="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(num_valid_proposals-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() > 1);</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(num_valid_proposals-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0) > 1);</div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(num_valid_proposals, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>);</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> </div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  <span class="keywordflow">if</span>(proposals-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>() > 0)</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  {</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(proposals-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() > 2);</div><div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(proposals-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0) != size_t(values_per_roi) + 1);</div><div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(proposals-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1) != size_t(total_num_anchors));</div><div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="keywordflow">if</span>(is_qasymm8)</div><div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  {</div><div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <a class="code" href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(proposals, 1, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a3b989c6b5398b3b9538ad103a324205e">DataType::QASYMM16</a>);</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keyword">const</span> <a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml">UniformQuantizationInfo</a> proposals_qinfo = proposals-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">quantization_info</a>().<a class="code" href="classarm__compute_1_1_quantization_info.xhtml#a706fc156bcd4c45441bcaad05884b57d">uniform</a>();</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(proposals_qinfo.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">scale</a> != 0.125f);</div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(proposals_qinfo.<a class="code" href="structarm__compute_1_1_uniform_quantization_info.xhtml#a97bd6c077f3c7769f575b82988b9b668">offset</a> != 0);</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="keywordflow">else</span></div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  {</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(proposals, scores);</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  }</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  }</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>  <span class="keywordflow">if</span>(scores_out-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>() > 0)</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>  {</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(scores_out-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">num_dimensions</a>() > 1);</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <a class="code" href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a>(scores_out-><a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0) != size_t(total_num_anchors));</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <a class="code" href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a>(scores_out, scores);</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  }</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span> </div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keywordflow">return</span> <a class="code" href="classarm__compute_1_1_status.xhtml">Status</a>{};</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span> }</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span> <span class="keywordtype">void</span> CLGenerateProposalsLayer::run_cpp_nms_kernel()</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span> {</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="comment">// Map inputs</span></div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  _scores_flattened.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a14c53d2d17be6fa8a2c9861527c7b002">map</a>(<span class="keyword">true</span>);</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  _all_proposals_to_use-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a14c53d2d17be6fa8a2c9861527c7b002">map</a>(<span class="keyword">true</span>);</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> </div><div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="comment">// Map outputs</span></div><div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  _scores_out-><a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml#ac0abc7a5c0d172947f0e6a0c0dde3df0">map</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue(), <span class="keyword">true</span>);</div><div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  _proposals_4_roi_values.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a14c53d2d17be6fa8a2c9861527c7b002">map</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue(), <span class="keyword">true</span>);</div><div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  _num_valid_proposals-><a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml#ac0abc7a5c0d172947f0e6a0c0dde3df0">map</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue(), <span class="keyword">true</span>);</div><div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  _keeps_nms_unused.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a14c53d2d17be6fa8a2c9861527c7b002">map</a>(<span class="keyword">true</span>);</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  _classes_nms_unused.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a14c53d2d17be6fa8a2c9861527c7b002">map</a>(<span class="keyword">true</span>);</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span> </div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <span class="comment">// Run nms</span></div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  _cpp_nms.<a class="code" href="classarm__compute_1_1_c_p_p_box_with_non_maxima_suppression_limit.xhtml#ad1717410afd0be936c6213a63c8005fb">run</a>();</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span> </div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="comment">// Unmap outputs</span></div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  _keeps_nms_unused.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a1ffeb3b5abb3d61f62b58a391816201c">unmap</a>();</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  _classes_nms_unused.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a1ffeb3b5abb3d61f62b58a391816201c">unmap</a>();</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  _scores_out-><a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml#af974a2360069c2ef8df4496d00e4f6cc">unmap</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  _proposals_4_roi_values.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a1ffeb3b5abb3d61f62b58a391816201c">unmap</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  _num_valid_proposals-><a class="code" href="classarm__compute_1_1_i_c_l_tensor.xhtml#af974a2360069c2ef8df4496d00e4f6cc">unmap</a>(<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().queue());</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> </div><div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="comment">// Unmap inputs</span></div><div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  _scores_flattened.<a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a1ffeb3b5abb3d61f62b58a391816201c">unmap</a>();</div><div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  _all_proposals_to_use-><a class="code" href="classarm__compute_1_1_c_l_tensor.xhtml#a1ffeb3b5abb3d61f62b58a391816201c">unmap</a>();</div><div class="line"><a name="l00331"></a><span class="lineno"> 331</span> }</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> </div><div class="line"><a name="l00333"></a><span class="lineno"><a class="line" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#ad1717410afd0be936c6213a63c8005fb"> 333</a></span> <span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">CLGenerateProposalsLayer::run</a>()</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> {</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="comment">// Acquire all the temporaries</span></div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <a class="code" href="classarm__compute_1_1_memory_group_resource_scope.xhtml">MemoryGroupResourceScope</a> scope_mg(_memory_group);</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>  <span class="comment">// Compute all the anchors</span></div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_compute_anchors_kernel, <span class="keyword">false</span>);</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>  <span class="comment">// Transpose and reshape the inputs</span></div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">if</span>(!_is_nhwc)</div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  {</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_permute_deltas_kernel, <span class="keyword">false</span>);</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_permute_scores_kernel, <span class="keyword">false</span>);</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  }</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_flatten_deltas_kernel, <span class="keyword">false</span>);</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_flatten_scores_kernel, <span class="keyword">false</span>);</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span> </div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="keywordflow">if</span>(_is_qasymm8)</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  {</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_dequantize_anchors, <span class="keyword">false</span>);</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_dequantize_deltas, <span class="keyword">false</span>);</div><div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  }</div><div class="line"><a name="l00355"></a><span class="lineno"> 355</span> </div><div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="comment">// Build the boxes</span></div><div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_bounding_box_kernel, <span class="keyword">false</span>);</div><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> </div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="keywordflow">if</span>(_is_qasymm8)</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>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_quantize_all_proposals, <span class="keyword">false</span>);</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  }</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>  <span class="comment">// Non maxima suppression</span></div><div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  run_cpp_nms_kernel();</div><div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="comment">// Add dummy batch indexes</span></div><div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">CLScheduler::get</a>().<a class="code" href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">enqueue</a>(_pad_kernel, <span class="keyword">true</span>);</div><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> }</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span> } <span class="comment">// namespace arm_compute</span></div><div class="ttc" id="classarm__compute_1_1_c_l_generate_proposals_layer_xhtml_a01a8a849ea1f7fb96263093b7d6978a9"><div class="ttname"><a href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a01a8a849ea1f7fb96263093b7d6978a9">arm_compute::CLGenerateProposalsLayer::configure</a></div><div class="ttdeci">void configure(const ICLTensor *scores, const ICLTensor *deltas, const ICLTensor *anchors, ICLTensor *proposals, ICLTensor *scores_out, ICLTensor *num_valid_proposals, const GenerateProposalsInfo &info)</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_generate_proposals_layer_8cpp_source.xhtml#l00065">CLGenerateProposalsLayer.cpp:65</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a1f4e725b8e1ea36b30e09dc08ae6961d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a1f4e725b8e1ea36b30e09dc08ae6961d">arm_compute::ITensorInfo::num_dimensions</a></div><div class="ttdeci">virtual size_t num_dimensions() const =0</div><div class="ttdoc">The number of dimensions of the tensor (rank)</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_pad_layer_kernel_xhtml_a5ab39485b5d0b51df3472895ed0c00a2"><div class="ttname"><a href="classarm__compute_1_1_c_l_pad_layer_kernel.xhtml#a5ab39485b5d0b51df3472895ed0c00a2">arm_compute::CLPadLayerKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output, const PaddingList &padding, PixelValue constant_value=PixelValue(), PaddingMode mode=PaddingMode::CONSTANT)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLPadLayerKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_pad_layer_kernel_8cpp_source.xhtml#l00194">CLPadLayerKernel.cpp:194</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_compute_all_anchors_kernel_xhtml_a4475c404f4bc3140b493a987d1fa0fc6"><div class="ttname"><a href="classarm__compute_1_1_c_l_compute_all_anchors_kernel.xhtml#a4475c404f4bc3140b493a987d1fa0fc6">arm_compute::CLComputeAllAnchorsKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info)</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_generate_proposals_layer_kernel_8cpp_source.xhtml#l00073">CLGenerateProposalsLayerKernel.cpp:73</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_generate_proposals_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_generate_proposals_info.xhtml">arm_compute::GenerateProposalsInfo</a></div><div class="ttdoc">Generate Proposals Information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01417">Types.h:1417</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_tensor_xhtml_ac0abc7a5c0d172947f0e6a0c0dde3df0"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_tensor.xhtml#ac0abc7a5c0d172947f0e6a0c0dde3df0">arm_compute::ICLTensor::map</a></div><div class="ttdeci">void map(cl::CommandQueue &q, bool blocking=true)</div><div class="ttdoc">Enqueue a map operation of the allocated buffer on the given queue.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_tensor_8cpp_source.xhtml#l00035">ICLTensor.cpp:35</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div> |
| <div class="ttc" id="_toolchain_support_8h_xhtml"><div class="ttname"><a href="_toolchain_support_8h.xhtml">ToolchainSupport.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a3ca8a4ea8f992df3b462bc7b24d097c6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a3ca8a4ea8f992df3b462bc7b24d097c6">arm_compute::DataType::QSYMM16</a></div><div class="ttdoc">quantized, symmetric fixed-point 16-bit number</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_ad45f0c01a0713dfb6bd7232c7f396fc4"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#ad45f0c01a0713dfb6bd7232c7f396fc4">arm_compute::CLTensor::info</a></div><div class="ttdeci">TensorInfo * info() const override</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00041">CLTensor.cpp:41</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a178f0d3d87f959e00a743328d95359d2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">arm_compute::ITensorInfo::dimension</a></div><div class="ttdeci">virtual size_t dimension(size_t index) const =0</div><div class="ttdoc">Return the size of the requested dimension.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ac1a1b012674e0f1de071a611391828ad"><div class="ttname"><a href="namespacearm__compute.xhtml#ac1a1b012674e0f1de071a611391828ad">arm_compute::PaddingList</a></div><div class="ttdeci">std::vector< PaddingInfo > PaddingList</div><div class="ttdoc">List of padding information.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00455">Types.h:455</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_a9b58d0eb9a2af8e6d7908695e1557d6c"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#a9b58d0eb9a2af8e6d7908695e1557d6c">arm_compute::CLScheduler::get</a></div><div class="ttdeci">static CLScheduler & get()</div><div class="ttdoc">Access the scheduler singleton.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00099">CLScheduler.cpp:99</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_abdb9168800c70e5e2c4c020a3b905738"><div class="ttname"><a href="_validate_8h.xhtml#abdb9168800c70e5e2c4c020a3b905738">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00494">Validate.h:494</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a8f3ff7da485ff7e75dab07baadf5b4bd"><div class="ttname"><a href="_validate_8h.xhtml#a8f3ff7da485ff7e75dab07baadf5b4bd">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00545">Validate.h:545</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_box_n_m_s_limit_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_box_n_m_s_limit_info.xhtml">arm_compute::BoxNMSLimitInfo</a></div><div class="ttdoc">BoxWithNonMaximaSuppressionLimit Information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00590">Types.h:590</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a8a1e1c105f0bdaf37db408c7cfcb77a4"><div class="ttname"><a href="_error_8h.xhtml#a8a1e1c105f0bdaf37db408c7cfcb77a4">ARM_COMPUTE_RETURN_ON_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ON_ERROR(status)</div><div class="ttdoc">Checks if a status contains an error and returns it.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00204">Error.h:204</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_p_p_box_with_non_maxima_suppression_limit_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_c_p_p_box_with_non_maxima_suppression_limit.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::CPPBoxWithNonMaximaSuppressionLimit::run</a></div><div class="ttdeci">void run() override</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_box_with_non_maxima_suppression_limit_8cpp_source.xhtml#l00217">CPPBoxWithNonMaximaSuppressionLimit.cpp:217</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_ae7eed178dac535c6e727061b1f5bc6eb"><div class="ttname"><a href="_validate_8h.xhtml#ae7eed178dac535c6e727061b1f5bc6eb">ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00792">Validate.h:792</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_generate_proposals_layer_xhtml_ad1717410afd0be936c6213a63c8005fb"><div class="ttname"><a href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#ad1717410afd0be936c6213a63c8005fb">arm_compute::CLGenerateProposalsLayer::run</a></div><div class="ttdeci">void run() override</div><div class="ttdoc">Run the kernels contained in the function.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_generate_proposals_layer_8cpp_source.xhtml#l00333">CLGenerateProposalsLayer.cpp:333</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02ad770ba3ce18fa409965dfdf5e7c348e6">arm_compute::DataLayoutDimension::HEIGHT</a></div><div class="ttdoc">height</div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a0a9053e6c4729ac5201b58068050c319"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a0a9053e6c4729ac5201b58068050c319">arm_compute::TensorInfo::set_data_type</a></div><div class="ttdeci">ITensorInfo & set_data_type(DataType data_type) override</div><div class="ttdoc">Set the data type to the specified value.</div><div class="ttdef"><b>Definition:</b> <a href="src_2core_2_tensor_info_8cpp_source.xhtml#l00319">TensorInfo.cpp:319</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml">arm_compute::ITensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_info_8h_source.xhtml#l00040">ITensorInfo.h:40</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_a4083de30daebd6bdee6b35d9c8262108"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a4083de30daebd6bdee6b35d9c8262108">arm_compute::CLTensor::allocator</a></div><div class="ttdeci">CLTensorAllocator * allocator()</div><div class="ttdoc">Return a pointer to the tensor's allocator.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00061">CLTensor.cpp:61</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a938dcd406ce611ef5345ad2531cdb948"><div class="ttname"><a href="_error_8h.xhtml#a938dcd406ce611ef5345ad2531cdb948">ARM_COMPUTE_ERROR_THROW_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_THROW_ON(status)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00455">Error.h:455</a></div></div> |
| <div class="ttc" id="structarm__compute_1_1_uniform_quantization_info_xhtml"><div class="ttname"><a href="structarm__compute_1_1_uniform_quantization_info.xhtml">arm_compute::UniformQuantizationInfo</a></div><div class="ttdoc">Quantization info when assuming per layer quantization.</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00042">QuantizationInfo.h:42</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a3b989c6b5398b3b9538ad103a324205e"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a3b989c6b5398b3b9538ad103a324205e">arm_compute::DataType::QASYMM16</a></div><div class="ttdoc">quantized, asymmetric fixed-point 16-bit number</div></div> |
| <div class="ttc" id="structarm__compute_1_1_uniform_quantization_info_xhtml_a1d28dec57cce925ad92342891bd71e7c"><div class="ttname"><a href="structarm__compute_1_1_uniform_quantization_info.xhtml#a1d28dec57cce925ad92342891bd71e7c">arm_compute::UniformQuantizationInfo::scale</a></div><div class="ttdeci">float scale</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00064">QuantizationInfo.h:64</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_status_xhtml"><div class="ttname"><a href="classarm__compute_1_1_status.xhtml">arm_compute::Status</a></div><div class="ttdoc">Status class.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00052">Error.h:52</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a206d6e247e0957ac3dee45d27756fc25"><div class="ttname"><a href="_error_8h.xhtml#a206d6e247e0957ac3dee45d27756fc25">ARM_COMPUTE_RETURN_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true, an error is returned.</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00296">Error.h:296</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_allocator_xhtml_af36143939a43fa124312e395975091ed"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_allocator.xhtml#af36143939a43fa124312e395975091ed">arm_compute::ITensorAllocator::init</a></div><div class="ttdeci">void init(const TensorInfo &input, size_t alignment=0)</div><div class="ttdoc">Initialize a tensor based on the passed TensorInfo.</div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_allocator_8cpp_source.xhtml#l00038">ITensorAllocator.cpp:38</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_quantization_layer_kernel_xhtml_a968b23a6ef327fcfb5b99d58e3fbe883"><div class="ttname"><a href="classarm__compute_1_1_c_l_quantization_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">arm_compute::CLQuantizationLayerKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLQuantizationLayerKerne...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_quantization_layer_kernel_8cpp_source.xhtml#l00159">CLQuantizationLayerKernel.cpp:159</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">Copyright (c) 2017-2020 ARM Limited.</div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00024">00_introduction.dox:24</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a47be6fa38308d0003c25b60b7dbc45ce"><div class="ttname"><a href="namespacearm__compute.xhtml#a47be6fa38308d0003c25b60b7dbc45ce">arm_compute::auto_init_if_empty</a></div><div class="ttdeci">bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())</div><div class="ttdoc">Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00202">Helpers.inl:202</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_a14c53d2d17be6fa8a2c9861527c7b002"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a14c53d2d17be6fa8a2c9861527c7b002">arm_compute::CLTensor::map</a></div><div class="ttdeci">void map(bool blocking=true)</div><div class="ttdoc">Enqueue a map operation of the allocated buffer.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00066">CLTensor.cpp:66</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_quantization_layer_kernel_xhtml_a074e10cfb217e657b9e81adeca2abc68"><div class="ttname"><a href="classarm__compute_1_1_c_l_quantization_layer_kernel.xhtml#a074e10cfb217e657b9e81adeca2abc68">arm_compute::CLQuantizationLayerKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output)</div><div class="ttdoc">Set the input, output.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_quantization_layer_kernel_8cpp_source.xhtml#l00081">CLQuantizationLayerKernel.cpp:81</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_memory_group_xhtml_a6fc0a49304c152c20a0f6df0634fb3cd"><div class="ttname"><a href="classarm__compute_1_1_memory_group.xhtml#a6fc0a49304c152c20a0f6df0634fb3cd">arm_compute::MemoryGroup::manage</a></div><div class="ttdeci">void manage(IMemoryManageable *obj) override</div><div class="ttdoc">Sets a object to be managed by the given memory group.</div><div class="ttdef"><b>Definition:</b> <a href="_memory_group_8h_source.xhtml#l00079">MemoryGroup.h:79</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_bounding_box_transform_kernel_xhtml_ab70ebf089f4e98eaacb33e43122162f2"><div class="ttname"><a href="classarm__compute_1_1_c_l_bounding_box_transform_kernel.xhtml#ab70ebf089f4e98eaacb33e43122162f2">arm_compute::CLBoundingBoxTransformKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *boxes, ICLTensor *pred_boxes, const ICLTensor *deltas, const BoundingBoxTransformInfo &info)</div><div class="ttdoc">Set the input and output tensors.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_bounding_box_transform_kernel_8cpp_source.xhtml#l00090">CLBoundingBoxTransformKernel.cpp:90</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_dequantization_layer_kernel_xhtml_a968b23a6ef327fcfb5b99d58e3fbe883"><div class="ttname"><a href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">arm_compute::CLDequantizationLayerKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLDequantizationLayerKer...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_dequantization_layer_kernel_8cpp_source.xhtml#l00125">CLDequantizationLayerKernel.cpp:125</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_quantization_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_quantization_info.xhtml">arm_compute::QuantizationInfo</a></div><div class="ttdoc">Quantization information.</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00069">QuantizationInfo.h:69</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_compute_all_anchors_kernel_xhtml_a3104e859ad98ef70c9d47bbaa5d209e8"><div class="ttname"><a href="classarm__compute_1_1_c_l_compute_all_anchors_kernel.xhtml#a3104e859ad98ef70c9d47bbaa5d209e8">arm_compute::CLComputeAllAnchorsKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLComputeAllAnchorsKerne...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_generate_proposals_layer_kernel_8cpp_source.xhtml#l00121">CLGenerateProposalsLayerKernel.cpp:121</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::Format::U32</a></div><div class="ttdoc">1 channel, 1 U32 per channel</div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a27e4638546c88b8916f967e6e54480a9"><div class="ttname"><a href="_validate_8h.xhtml#a27e4638546c88b8916f967e6e54480a9">ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00443">Validate.h:443</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::DataType::QASYMM8</a></div><div class="ttdoc">quantized, asymmetric fixed-point 8-bit number unsigned</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_tensor_xhtml_af974a2360069c2ef8df4496d00e4f6cc"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_tensor.xhtml#af974a2360069c2ef8df4496d00e4f6cc">arm_compute::ICLTensor::unmap</a></div><div class="ttdeci">void unmap(cl::CommandQueue &q)</div><div class="ttdoc">Enqueue an unmap operation of the allocated and mapped buffer on the given queue.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_tensor_8cpp_source.xhtml#l00040">ICLTensor.cpp:40</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_quantization_info_xhtml_a706fc156bcd4c45441bcaad05884b57d"><div class="ttname"><a href="classarm__compute_1_1_quantization_info.xhtml#a706fc156bcd4c45441bcaad05884b57d">arm_compute::QuantizationInfo::uniform</a></div><div class="ttdeci">UniformQuantizationInfo uniform() const</div><div class="ttdoc">Return per layer quantization info.</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00148">QuantizationInfo.h:148</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1misc_1_1_i_cloneable_xhtml_a4d10e5012a872e7f78f2b539b673049d"><div class="ttname"><a href="classarm__compute_1_1misc_1_1_i_cloneable.xhtml#a4d10e5012a872e7f78f2b539b673049d">arm_compute::misc::ICloneable::clone</a></div><div class="ttdeci">virtual std::unique_ptr< T > clone() const =0</div><div class="ttdoc">Provide a clone of the current object of class T.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor's metadata.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a575d37eaf8a905c8ca3c0250757c2b81"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a575d37eaf8a905c8ca3c0250757c2b81">arm_compute::ITensorInfo::set_quantization_info</a></div><div class="ttdeci">virtual ITensorInfo & set_quantization_info(const QuantizationInfo &quantization_info)=0</div><div class="ttdoc">Set the quantization settings (scale and offset) of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_reshape_layer_kernel_xhtml_a968b23a6ef327fcfb5b99d58e3fbe883"><div class="ttname"><a href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml#a968b23a6ef327fcfb5b99d58e3fbe883">arm_compute::CLReshapeLayerKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLReshapeLayerKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_reshape_layer_kernel_8cpp_source.xhtml#l00104">CLReshapeLayerKernel.cpp:104</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02af52e9c50a060add65a035429b2a22229">arm_compute::DataLayoutDimension::CHANNEL</a></div><div class="ttdoc">channel</div></div> |
| <div class="ttc" id="classarm__compute_1_1_bounding_box_transform_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_bounding_box_transform_info.xhtml">arm_compute::BoundingBoxTransformInfo</a></div><div class="ttdoc">Bounding Box Transform information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01548">Types.h:1548</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a3f3e1a3200223e6a304a533b1016e749"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a3f3e1a3200223e6a304a533b1016e749">arm_compute::ITensorInfo::quantization_info</a></div><div class="ttdeci">virtual QuantizationInfo quantization_info() const =0</div><div class="ttdoc">Get the quantization settings (scale and offset) of the tensor.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_pad_layer_kernel_xhtml_a6f350b775160732d72ab28e01432d6bf"><div class="ttname"><a href="classarm__compute_1_1_c_l_pad_layer_kernel.xhtml#a6f350b775160732d72ab28e01432d6bf">arm_compute::CLPadLayerKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output, const PaddingList &padding, PixelValue constant_value=PixelValue(), PaddingMode mode=PaddingMode::CONSTANT)</div><div class="ttdoc">Set the input and output tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_pad_layer_kernel_8cpp_source.xhtml#l00098">CLPadLayerKernel.cpp:98</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_scheduler_xhtml_ae1a643e517f50bf0392fb6516dd7cf67"><div class="ttname"><a href="classarm__compute_1_1_c_l_scheduler.xhtml#ae1a643e517f50bf0392fb6516dd7cf67">arm_compute::CLScheduler::enqueue</a></div><div class="ttdeci">void enqueue(ICLKernel &kernel, bool flush=true)</div><div class="ttdoc">Schedule the execution of the passed kernel if possible.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_scheduler_8cpp_source.xhtml#l00154">CLScheduler.cpp:154</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0a6b99f356fe3b30a2a850b5ea897c289f">arm_compute::DataLayout::NCHW</a></div><div class="ttdoc">Num samples, channels, height, width.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_bounding_box_transform_kernel_xhtml_a174ade6b3a2fe6cf00192a9419514cc1"><div class="ttname"><a href="classarm__compute_1_1_c_l_bounding_box_transform_kernel.xhtml#a174ade6b3a2fe6cf00192a9419514cc1">arm_compute::CLBoundingBoxTransformKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *boxes, const ITensorInfo *pred_boxes, const ITensorInfo *deltas, const BoundingBoxTransformInfo &info)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLBoundingBoxTransform.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_bounding_box_transform_kernel_8cpp_source.xhtml#l00147">CLBoundingBoxTransformKernel.cpp:147</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_strides_xhtml"><div class="ttname"><a href="classarm__compute_1_1_strides.xhtml">arm_compute::Strides</a></div><div class="ttdoc">Strides of an item in bytes.</div><div class="ttdef"><b>Definition:</b> <a href="_strides_8h_source.xhtml#l00037">Strides.h:37</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_reshape_layer_kernel_xhtml_a074e10cfb217e657b9e81adeca2abc68"><div class="ttname"><a href="classarm__compute_1_1_c_l_reshape_layer_kernel.xhtml#a074e10cfb217e657b9e81adeca2abc68">arm_compute::CLReshapeLayerKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output)</div><div class="ttdoc">Set the input and output of the kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_reshape_layer_kernel_8cpp_source.xhtml#l00065">CLReshapeLayerKernel.cpp:65</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_aff911654521523937ff24372a870b89f"><div class="ttname"><a href="_validate_8h.xhtml#aff911654521523937ff24372a870b89f">ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00163">Validate.h:163</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_generate_proposals_layer_xhtml_a0dd15c751cbdd5768cb781ef766e50dd"><div class="ttname"><a href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a0dd15c751cbdd5768cb781ef766e50dd">arm_compute::CLGenerateProposalsLayer::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *scores, const ITensorInfo *deltas, const ITensorInfo *anchors, const ITensorInfo *proposals, const ITensorInfo *scores_out, const ITensorInfo *num_valid_proposals, const GenerateProposalsInfo &info)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLGenerateProposalsLayer...</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_generate_proposals_layer_8cpp_source.xhtml#l00193">CLGenerateProposalsLayer.cpp:193</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_allocator_xhtml_a6e509c2a177b0b29e9e2369535094dee"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor_allocator.xhtml#a6e509c2a177b0b29e9e2369535094dee">arm_compute::CLTensorAllocator::allocate</a></div><div class="ttdeci">void allocate() override</div><div class="ttdoc">Allocate size specified by TensorInfo of OpenCL memory.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_allocator_8cpp_source.xhtml#l00127">CLTensorAllocator.cpp:127</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a921b705e9e3e0fe928928447869e62a5"><div class="ttname"><a href="_validate_8h.xhtml#a921b705e9e3e0fe928928447869e62a5">ARM_COMPUTE_ERROR_ON_NULLPTR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00161">Validate.h:161</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_memory_group_resource_scope_xhtml"><div class="ttname"><a href="classarm__compute_1_1_memory_group_resource_scope.xhtml">arm_compute::MemoryGroupResourceScope</a></div><div class="ttdoc">Memory group resources scope handling class.</div><div class="ttdef"><b>Definition:</b> <a href="_i_memory_group_8h_source.xhtml#l00082">IMemoryGroup.h:82</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_c_l_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_c_l_tensor.xhtml">arm_compute::ICLTensor</a></div><div class="ttdoc">Interface for OpenCL tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_i_c_l_tensor_8h_source.xhtml#l00042">ICLTensor.h:42</a></div></div> |
| <div class="ttc" id="_i_c_l_tensor_8h_xhtml"><div class="ttname"><a href="_i_c_l_tensor_8h.xhtml">ICLTensor.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a18064e0011c3869d884653e9e7c47b66"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">arm_compute::ITensorInfo::total_size</a></div><div class="ttdeci">virtual size_t total_size() const =0</div><div class="ttdoc">Returns the total size of the tensor in bytes.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_dequantization_layer_kernel_xhtml_a074e10cfb217e657b9e81adeca2abc68"><div class="ttname"><a href="classarm__compute_1_1_c_l_dequantization_layer_kernel.xhtml#a074e10cfb217e657b9e81adeca2abc68">arm_compute::CLDequantizationLayerKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output)</div><div class="ttdoc">Set the input, output, min and max.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_dequantization_layer_kernel_8cpp_source.xhtml#l00077">CLDequantizationLayerKernel.cpp:77</a></div></div> |
| <div class="ttc" id="_c_l_generate_proposals_layer_8h_xhtml"><div class="ttname"><a href="_c_l_generate_proposals_layer_8h.xhtml">CLGenerateProposalsLayer.h</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_compute_anchors_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_compute_anchors_info.xhtml">arm_compute::ComputeAnchorsInfo</a></div><div class="ttdoc">ComputeAnchors information class.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l01498">Types.h:1498</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51"><div class="ttname"><a href="namespacearm__compute.xhtml#ad1d5cce2d9e9a5d61c243e5c989112e0ad066db54b89b0912e7e7c6da51e2da51">arm_compute::DataLayout::NHWC</a></div><div class="ttdoc">Num samples, height, width, channels.</div></div> |
| <div class="ttc" id="structarm__compute_1_1_uniform_quantization_info_xhtml_a97bd6c077f3c7769f575b82988b9b668"><div class="ttname"><a href="structarm__compute_1_1_uniform_quantization_info.xhtml#a97bd6c077f3c7769f575b82988b9b668">arm_compute::UniformQuantizationInfo::offset</a></div><div class="ttdeci">int32_t offset</div><div class="ttdef"><b>Definition:</b> <a href="_quantization_info_8h_source.xhtml#l00065">QuantizationInfo.h:65</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_permute_kernel_xhtml_af1f5e1b7e8bbf0768c406be880387a0d"><div class="ttname"><a href="classarm__compute_1_1_c_l_permute_kernel.xhtml#af1f5e1b7e8bbf0768c406be880387a0d">arm_compute::CLPermuteKernel::configure</a></div><div class="ttdeci">void configure(const ICLTensor *input, ICLTensor *output, const PermutationVector &perm)</div><div class="ttdoc">Set the input and output of the kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_permute_kernel_8cpp_source.xhtml#l00078">CLPermuteKernel.cpp:78</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_generate_proposals_layer_xhtml_a5238a3faae0338e0f8cba6d62e1ad94e"><div class="ttname"><a href="classarm__compute_1_1_c_l_generate_proposals_layer.xhtml#a5238a3faae0338e0f8cba6d62e1ad94e">arm_compute::CLGenerateProposalsLayer::CLGenerateProposalsLayer</a></div><div class="ttdeci">CLGenerateProposalsLayer(std::shared_ptr< IMemoryManager > memory_manager=nullptr)</div><div class="ttdoc">Default constructor.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_generate_proposals_layer_8cpp_source.xhtml#l00032">CLGenerateProposalsLayer.cpp:32</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195"><div class="ttname"><a href="namespacearm__compute.xhtml#a74ce3f7420453d3446218ff3b7453e02a49da85b69bc6285eeee286ca49fa7195">arm_compute::DataLayoutDimension::WIDTH</a></div><div class="ttdoc">width</div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor's metadata.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00045">TensorInfo.h:45</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a46e938020a3ac8c926d0590b7fe957db"><div class="ttname"><a href="namespacearm__compute.xhtml#a46e938020a3ac8c926d0590b7fe957db">arm_compute::get_data_layout_dimension_index</a></div><div class="ttdeci">size_t get_data_layout_dimension_index(const DataLayout data_layout, const DataLayoutDimension data_layout_dimension)</div><div class="ttdoc">Get the index of the given dimension.</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00327">Helpers.inl:327</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a4f4125dba5283887b34f889b1c615c0c"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a4f4125dba5283887b34f889b1c615c0c">arm_compute::test::validation::info</a></div><div class="ttdeci">info</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_layer_8cpp_source.xhtml#l00182">ConvolutionLayer.cpp:182</a></div></div> |
| <div class="ttc" id="_validate_8h_xhtml_a7e906bfc9e333e3f967d8ee9353ce001"><div class="ttname"><a href="_validate_8h.xhtml#a7e906bfc9e333e3f967d8ee9353ce001">ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(t,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00746">Validate.h:746</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml_a269b19ce3f357ac65f41f9951906e38e"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml#a269b19ce3f357ac65f41f9951906e38e">arm_compute::TensorInfo::tensor_shape</a></div><div class="ttdeci">const TensorShape & tensor_shape() const override</div><div class="ttdoc">Size for each dimension of the tensor.</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00261">TensorInfo.h:261</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_permute_kernel_xhtml_a97f09e05a72865753ecb1948b38d4843"><div class="ttname"><a href="classarm__compute_1_1_c_l_permute_kernel.xhtml#a97f09e05a72865753ecb1948b38d4843">arm_compute::CLPermuteKernel::validate</a></div><div class="ttdeci">static Status validate(const ITensorInfo *input, const ITensorInfo *output, const PermutationVector &perm)</div><div class="ttdoc">Static function to check if given info will lead to a valid configuration of CLPermuteKernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_permute_kernel_8cpp_source.xhtml#l00114">CLPermuteKernel.cpp:114</a></div></div> |
| <div class="ttc" id="arm__compute_2core_2_types_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_types_8h.xhtml">Types.h</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">arm_compute::DataType</a></div><div class="ttdeci">DataType</div><div class="ttdoc">Available data types.</div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00075">Types.h:75</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml_a1ffeb3b5abb3d61f62b58a391816201c"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml#a1ffeb3b5abb3d61f62b58a391816201c">arm_compute::CLTensor::unmap</a></div><div class="ttdeci">void unmap()</div><div class="ttdoc">Enqueue an unmap operation of the allocated and mapped buffer.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8cpp_source.xhtml#l00071">CLTensor.cpp:71</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a367b5090ab432bc7de2c32369e087ab1"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a367b5090ab432bc7de2c32369e087ab1">arm_compute::ITensorInfo::data_layout</a></div><div class="ttdeci">virtual DataLayout data_layout() const =0</div><div class="ttdoc">Get the data layout of the tensor.</div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a201391f6e13e2a1ac203256a77792718aaac544aacc3615aada24897a215f5046"><div class="ttname"><a href="namespacearm__compute.xhtml#a201391f6e13e2a1ac203256a77792718aaac544aacc3615aada24897a215f5046">arm_compute::NMSType::LINEAR</a></div><div class="ttdoc">Linear NMS.</div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_p_p_box_with_non_maxima_suppression_limit_xhtml_a014205af76eea5e1ba768fc10b60222a"><div class="ttname"><a href="classarm__compute_1_1_c_p_p_box_with_non_maxima_suppression_limit.xhtml#a014205af76eea5e1ba768fc10b60222a">arm_compute::CPPBoxWithNonMaximaSuppressionLimit::configure</a></div><div class="ttdeci">void configure(const ITensor *scores_in, const ITensor *boxes_in, const ITensor *batch_splits_in, ITensor *scores_out, ITensor *boxes_out, ITensor *classes, ITensor *batch_splits_out=nullptr, ITensor *keeps=nullptr, ITensor *keeps_size=nullptr, const BoxNMSLimitInfo info=BoxNMSLimitInfo())</div><div class="ttdoc">Configure the BoxWithNonMaximaSuppressionLimit CPP kernel.</div><div class="ttdef"><b>Definition:</b> <a href="_c_p_p_box_with_non_maxima_suppression_limit_8cpp_source.xhtml#l00119">CPPBoxWithNonMaximaSuppressionLimit.cpp:119</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1_c_l_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_c_l_tensor.xhtml">arm_compute::CLTensor</a></div><div class="ttdoc">Basic implementation of the OpenCL tensor interface.</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_tensor_8h_source.xhtml#l00041">CLTensor.h:41</a></div></div> |
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