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<a href="_neon_workload_utils_8hpp.html">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 © 2017 Arm Ltd. All rights reserved.</span></div><div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment">// SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment">//</span></div><div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="preprocessor">#pragma once</span></div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> </div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include <<a class="code" href="_workload_8hpp.html">backendsCommon/Workload.hpp</a>></span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include <<a class="code" href="_arm_compute_tensor_utils_8hpp.html">aclCommon/ArmComputeTensorUtils.hpp</a>></span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include <<a class="code" href="_neon_tensor_handle_8hpp.html">neon/NeonTensorHandle.hpp</a>></span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_neon_timer_8hpp.html">neon/NeonTimer.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include <<a class="code" href="_cpu_tensor_handle_8hpp.html">backendsCommon/CpuTensorHandle.hpp</a>></span></div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> </div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <<a class="code" href="_utils_8hpp.html">armnn/Utils.hpp</a>></span></div><div class="line"><a name="l00014"></a><span class="lineno"> 14</span> </div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include <<a class="code" href="_half_8hpp.html">Half.hpp</a>></span></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> </div><div class="line"><a name="l00017"></a><span class="lineno"><a class="line" href="_neon_workload_utils_8hpp.html#a8bf91fd5e5875631bcf6abbcd97fe2f4"> 17</a></span> <span class="preprocessor">#define ARMNN_SCOPED_PROFILING_EVENT_NEON(name) \</span></div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor"> ARMNN_SCOPED_PROFILING_EVENT_WITH_INSTRUMENTS(armnn::Compute::CpuAcc, \</span></div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor"> name, \</span></div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor"> armnn::NeonTimer(), \</span></div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor"> armnn::WallClockTimer())</span></div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span> </div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="keyword">using namespace </span><a class="code" href="namespacearmnn_1_1armcomputetensorutils.html">armnn::armcomputetensorutils</a>;</div><div class="line"><a name="l00024"></a><span class="lineno"> 24</span> </div><div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span> {</div><div class="line"><a name="l00027"></a><span class="lineno"> 27</span> </div><div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="keyword">template</span> <<span class="keyword">typename</span> T></div><div class="line"><a name="l00029"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a1351e01f9fb983937caf79e353142b41"> 29</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#a1351e01f9fb983937caf79e353142b41">CopyArmComputeTensorData</a>(arm_compute::Tensor& dstTensor, <span class="keyword">const</span> T* srcData)</div><div class="line"><a name="l00030"></a><span class="lineno"> 30</span> {</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  InitialiseArmComputeTensorEmpty(dstTensor);</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  CopyArmComputeITensorData(srcData, dstTensor);</div><div class="line"><a name="l00033"></a><span class="lineno"> 33</span> }</div><div class="line"><a name="l00034"></a><span class="lineno"> 34</span> </div><div class="line"><a name="l00035"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ad9aa8d49d42ada3f757290033af39857"> 35</a></span> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#ad9aa8d49d42ada3f757290033af39857">InitializeArmComputeTensorData</a>(arm_compute::Tensor& tensor,</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.html">ConstCpuTensorHandle</a>* handle)</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span> {</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  BOOST_ASSERT(handle);</div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span> </div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordflow">switch</span>(handle-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.html#a66e8f43a5b42b500871ed96e15419567">GetTensorInfo</a>().<a class="code" href="classarmnn_1_1_tensor_info.html#aea909c7327109228ef618d459015def3">GetDataType</a>())</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  {</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a26e6ed77470c6f2f830ecf874e6c0d55">DataType::Float16</a>:</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <a class="code" href="namespacearmnn.html#a1351e01f9fb983937caf79e353142b41">CopyArmComputeTensorData</a>(tensor, handle-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.html#a3a76fc8b348e13d5a6ac1240c96ebef4">GetConstTensor</a><<a class="code" href="namespacearmnn.html#a0f38fa92b2468d5378258a2b074c1a31">armnn::Half</a>>());</div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">DataType::Float32</a>:</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <a class="code" href="namespacearmnn.html#a1351e01f9fb983937caf79e353142b41">CopyArmComputeTensorData</a>(tensor, handle-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.html#a3a76fc8b348e13d5a6ac1240c96ebef4">GetConstTensor</a><<span class="keywordtype">float</span>>());</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a0a3f57c876f5a230244c38e1453a8a6e">DataType::QAsymmU8</a>:</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <a class="code" href="namespacearmnn.html#a1351e01f9fb983937caf79e353142b41">CopyArmComputeTensorData</a>(tensor, handle-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.html#a3a76fc8b348e13d5a6ac1240c96ebef4">GetConstTensor</a><uint8_t>());</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="_deprecated_8hpp.html#ab66a241a0ed3ee89c866e777b035d0ed">ARMNN_NO_DEPRECATE_WARN_BEGIN</a></div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a34346ec9593088efe3a29c0dad92166d">DataType::QuantizedSymm8PerAxis</a>:</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <a class="code" href="_utils_8hpp.html#abbf421eb1186af0d505648ed2ea54a00">ARMNN_FALLTHROUGH</a>;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6a9945327825b115e93a3b89f4302e76db">DataType::QSymmS8</a>:</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="namespacearmnn.html#a1351e01f9fb983937caf79e353142b41">CopyArmComputeTensorData</a>(tensor, handle-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.html#a3a76fc8b348e13d5a6ac1240c96ebef4">GetConstTensor</a><int8_t>());</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <a class="code" href="_deprecated_8hpp.html#ad762b11b48e5c1d1c1743f529485728a">ARMNN_NO_DEPRECATE_WARN_END</a></div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearmnn.html#ad8ed01ff3ff33333d8e19db4d2818bb6accedffbc6e5308e33d3843e8bdc0dad7">DataType::Signed32</a>:</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <a class="code" href="namespacearmnn.html#a1351e01f9fb983937caf79e353142b41">CopyArmComputeTensorData</a>(tensor, handle-><a class="code" href="classarmnn_1_1_const_cpu_tensor_handle.html#a3a76fc8b348e13d5a6ac1240c96ebef4">GetConstTensor</a><int32_t>());</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  BOOST_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Unexpected tensor type."</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"> 65</span> </div><div class="line"><a name="l00066"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a01d1e745f360ccd0b655214645bcef32"> 66</a></span> <span class="keyword">inline</span> <span class="keyword">auto</span> <a class="code" href="namespacearmnn.html#a01d1e745f360ccd0b655214645bcef32">SetNeonStridedSliceData</a>(<span class="keyword">const</span> std::vector<int>& m_begin,</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="keyword">const</span> std::vector<int>& m_end,</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="keyword">const</span> std::vector<int>& m_stride)</div><div class="line"><a name="l00069"></a><span class="lineno"> 69</span> {</div><div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <a class="code" href="namespacearmnn.html#ac6e86c1def7f674d3c4cb7f577874aa6">arm_compute::Coordinates</a> starts;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <a class="code" href="namespacearmnn.html#ac6e86c1def7f674d3c4cb7f577874aa6">arm_compute::Coordinates</a> ends;</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <a class="code" href="namespacearmnn.html#ac6e86c1def7f674d3c4cb7f577874aa6">arm_compute::Coordinates</a> strides;</div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span> </div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_dims = <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(m_begin.size());</div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span> </div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < num_dims; i++)</div><div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  {</div><div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> revertedIndex = num_dims - i - 1;</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  starts.set(i, static_cast<int>(m_begin[revertedIndex]));</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  ends.set(i, static_cast<int>(m_end[revertedIndex]));</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  strides.set(i, static_cast<int>(m_stride[revertedIndex]));</div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  }</div><div class="line"><a name="l00084"></a><span class="lineno"> 84</span> </div><div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keywordflow">return</span> std::make_tuple(starts, ends, strides);</div><div class="line"><a name="l00086"></a><span class="lineno"> 86</span> }</div><div class="line"><a name="l00087"></a><span class="lineno"> 87</span> </div><div class="line"><a name="l00088"></a><span class="lineno"><a class="line" href="namespacearmnn.html#ab40e30cea5a328a3c35aa32f9b7db1c1"> 88</a></span> <span class="keyword">inline</span> <span class="keyword">auto</span> <a class="code" href="namespacearmnn.html#ab40e30cea5a328a3c35aa32f9b7db1c1">SetNeonSliceData</a>(<span class="keyword">const</span> std::vector<unsigned int>& m_begin,</div><div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keyword">const</span> std::vector<unsigned int>& m_size)</div><div class="line"><a name="l00090"></a><span class="lineno"> 90</span> {</div><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="comment">// This function must translate the size vector given to an end vector</span></div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="comment">// expected by the ACL NESlice workload</span></div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="namespacearmnn.html#ac6e86c1def7f674d3c4cb7f577874aa6">arm_compute::Coordinates</a> starts;</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="namespacearmnn.html#ac6e86c1def7f674d3c4cb7f577874aa6">arm_compute::Coordinates</a> ends;</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> num_dims = <span class="keyword">static_cast<</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">></span>(m_begin.size());</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span> </div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="comment">// For strided slices, we have the relationship size = (end - begin) / stride</span></div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="comment">// For slice, we assume stride to be a vector of all ones, yielding the formula</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  <span class="comment">// size = (end - begin) therefore we know end = size + begin</span></div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < num_dims; i++)</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  {</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> revertedIndex = num_dims - i - 1;</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span> </div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  starts.set(i, static_cast<int>(m_begin[revertedIndex]));</div><div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  ends.set(i, static_cast<int>(m_begin[revertedIndex] + m_size[revertedIndex]));</div><div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  }</div><div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div><div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="keywordflow">return</span> std::make_tuple(starts, ends);</div><div class="line"><a name="l00110"></a><span class="lineno"> 110</span> }</div><div class="line"><a name="l00111"></a><span class="lineno"> 111</span> </div><div class="line"><a name="l00112"></a><span class="lineno"> 112</span> } <span class="comment">//namespace armnn</span></div><div class="ttc" id="classarmnn_1_1_const_cpu_tensor_handle_html_a3a76fc8b348e13d5a6ac1240c96ebef4"><div class="ttname"><a href="classarmnn_1_1_const_cpu_tensor_handle.html#a3a76fc8b348e13d5a6ac1240c96ebef4">armnn::ConstCpuTensorHandle::GetConstTensor</a></div><div class="ttdeci">const T * GetConstTensor() const</div><div class="ttdef"><b>Definition:</b> <a href="_cpu_tensor_handle_8hpp_source.html#l00031">CpuTensorHandle.hpp:31</a></div></div>
<div class="ttc" id="_neon_timer_8hpp_html"><div class="ttname"><a href="_neon_timer_8hpp.html">NeonTimer.hpp</a></div></div>
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<div class="ttc" id="_arm_compute_tensor_utils_8hpp_html"><div class="ttname"><a href="_arm_compute_tensor_utils_8hpp.html">ArmComputeTensorUtils.hpp</a></div></div>
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<div class="ttc" id="_cpu_tensor_handle_8hpp_html"><div class="ttname"><a href="_cpu_tensor_handle_8hpp.html">CpuTensorHandle.hpp</a></div></div>
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<div class="ttc" id="namespacearmnn_html_ad9aa8d49d42ada3f757290033af39857"><div class="ttname"><a href="namespacearmnn.html#ad9aa8d49d42ada3f757290033af39857">armnn::InitializeArmComputeTensorData</a></div><div class="ttdeci">void InitializeArmComputeTensorData(arm_compute::Tensor &tensor, const ConstCpuTensorHandle *handle)</div><div class="ttdef"><b>Definition:</b> <a href="_neon_workload_utils_8hpp_source.html#l00035">NeonWorkloadUtils.hpp:35</a></div></div>
<div class="ttc" id="_half_8hpp_html"><div class="ttname"><a href="_half_8hpp.html">Half.hpp</a></div></div>
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