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+<div class="title">Concatenate.cpp</div> </div>
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+<a href="_concatenate_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 © 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> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_concatenate_8hpp.xhtml">Concatenate.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="preprocessor">#include "<a class="code" href="_ref_workload_utils_8hpp.xhtml">RefWorkloadUtils.hpp</a>"</span></div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_decoders_8hpp.xhtml">Decoders.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#include "<a class="code" href="_encoders_8hpp.xhtml">Encoders.hpp</a>"</span></div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="keyword">namespace </span><a class="code" href="namespacearmnn.xhtml">armnn</a></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> </div><div class="line"><a name="l00014"></a><span class="lineno"><a class="line" href="namespacearmnn.xhtml#a1deafe1b2777bcaadefe2371b3ebbb27"> 14</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.xhtml#a1deafe1b2777bcaadefe2371b3ebbb27">Concatenate</a>(<span class="keyword">const</span> <a class="code" href="structarmnn_1_1_concat_queue_descriptor.xhtml">ConcatQueueDescriptor</a> &data)</div><div class="line"><a name="l00015"></a><span class="lineno"> 15</span> {</div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& outputInfo0 = <a class="code" href="namespacearmnn.xhtml#a93d269806f34407695dc10f510001c30">GetTensorInfo</a>(data.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]);</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  std::unique_ptr<Encoder<float>> encoderPtr = MakeEncoder<float>(outputInfo0, data.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">m_Outputs</a>[0]->Map());</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <a class="code" href="classarmnn_1_1_encoder.xhtml">Encoder<float></a>& encoder = *encoderPtr;</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span> </div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> index = 0 ; index < outputInfo0.GetNumElements(); ++index)</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> indices[<a class="code" href="namespacearmnn.xhtml#abdcd184ed3bd648bb31d385040cafd5d">MaxNumOfTensorDimensions</a>] = { 0 };</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> indexRemainder = index;</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimensionStride = outputInfo0.GetNumElements();</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="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < outputInfo0.GetNumDimensions(); i++)</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>  dimensionStride /= outputInfo0.GetShape()[i];</div><div class="line"><a name="l00031"></a><span class="lineno"> 31</span>  indices[i] = indexRemainder / dimensionStride; <span class="comment">// Use integer division to round down.</span></div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  indexRemainder -= indices[i] * dimensionStride;</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"> 35</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> viewIdx = 0; viewIdx < data.<a class="code" href="structarmnn_1_1_concat_queue_descriptor.xhtml#ab1794eb3e74c9700cd3d500fc06dc2e5">m_ViewOrigins</a>.size(); ++viewIdx)</div><div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  {</div><div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <a class="code" href="structarmnn_1_1_concat_queue_descriptor_1_1_view_origin.xhtml">ConcatQueueDescriptor::ViewOrigin</a> <span class="keyword">const</span>& view = data.<a class="code" href="structarmnn_1_1_concat_queue_descriptor.xhtml#ab1794eb3e74c9700cd3d500fc06dc2e5">m_ViewOrigins</a>[viewIdx];</div><div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div><div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="comment">//Split view extents are defined by the size of (the corresponding) input tensor.</span></div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.xhtml">TensorInfo</a>& inputInfo = <a class="code" href="namespacearmnn.xhtml#a93d269806f34407695dc10f510001c30">GetTensorInfo</a>(data.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[viewIdx]);</div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  BOOST_ASSERT(inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>() == outputInfo0.GetNumDimensions());</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="comment">// Check all dimensions to see if this element is inside the given input view.</span></div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordtype">bool</span> insideView = <span class="keyword">true</span>;</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i < inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); i++)</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  {</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordflow">if</span> (indices[i] < view.<a class="code" href="structarmnn_1_1_concat_queue_descriptor_1_1_view_origin.xhtml#af2f0a8c9eb32861711c0ce30b7986c44">m_Origin</a>[i])</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  {</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  insideView = <span class="keyword">false</span>;</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  }</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="keywordflow">if</span> (indices[i] >= view.<a class="code" href="structarmnn_1_1_concat_queue_descriptor_1_1_view_origin.xhtml#af2f0a8c9eb32861711c0ce30b7986c44">m_Origin</a>[i] + inputInfo.<a class="code" href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>()[i])</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  {</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  insideView = <span class="keyword">false</span>;</div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  }</div><div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  }</div><div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div><div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="keywordflow">if</span> (insideView)</div><div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  {</div><div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  std::unique_ptr<Decoder<float>> decoderPtr =</div><div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  MakeDecoder<float>(inputInfo, data.<a class="code" href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">m_Inputs</a>[viewIdx]->Map());</div><div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <a class="code" href="classarmnn_1_1_decoder.xhtml">Decoder<float></a>& decoder = *decoderPtr;</div><div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inIndex = 0;</div><div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> dimensionStride = 1;</div><div class="line"><a name="l00064"></a><span class="lineno"> 64</span> </div><div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = inputInfo.GetNumDimensions(); i-- > 0;)</div><div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  {</div><div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  inIndex += dimensionStride * (indices[i] - view.<a class="code" href="structarmnn_1_1_concat_queue_descriptor_1_1_view_origin.xhtml#af2f0a8c9eb32861711c0ce30b7986c44">m_Origin</a>[i]);</div><div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  dimensionStride *= inputInfo.GetShape()[i];</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>  decoder += inIndex;</div><div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  encoder.Set(decoder.Get());</div><div class="line"><a name="l00072"></a><span class="lineno"> 72</span> </div><div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="comment">//What should we do if input views overlap on the output tensor?</span></div><div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="comment">//We could error, take the average, or shm else...</span></div><div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="comment">//For now just stop after finding first view (input) that matches.</span></div><div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keywordflow">break</span>;</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>  }</div><div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  ++encoder;</div><div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  }</div><div class="line"><a name="l00081"></a><span class="lineno"> 81</span> }</div><div class="line"><a name="l00082"></a><span class="lineno"> 82</span> </div><div class="line"><a name="l00083"></a><span class="lineno"> 83</span> } <span class="comment">//namespace armnn</span></div><div class="ttc" id="structarmnn_1_1_concat_queue_descriptor_1_1_view_origin_xhtml_af2f0a8c9eb32861711c0ce30b7986c44"><div class="ttname"><a href="structarmnn_1_1_concat_queue_descriptor_1_1_view_origin.xhtml#af2f0a8c9eb32861711c0ce30b7986c44">armnn::ConcatQueueDescriptor::ViewOrigin::m_Origin</a></div><div class="ttdeci">std::vector< unsigned int > m_Origin</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00110">WorkloadData.hpp:110</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a8b5d0f8a24e9d9238f412260a552acf8">armnn::TensorInfo::GetShape</a></div><div class="ttdeci">const TensorShape & GetShape() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00088">Tensor.hpp:88</a></div></div>
+<div class="ttc" id="structarmnn_1_1_concat_queue_descriptor_1_1_view_origin_xhtml"><div class="ttname"><a href="structarmnn_1_1_concat_queue_descriptor_1_1_view_origin.xhtml">armnn::ConcatQueueDescriptor::ViewOrigin</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00104">WorkloadData.hpp:104</a></div></div>
+<div class="ttc" id="_ref_workload_utils_8hpp_xhtml"><div class="ttname"><a href="_ref_workload_utils_8hpp.xhtml">RefWorkloadUtils.hpp</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00053">Tensor.hpp:53</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a93d269806f34407695dc10f510001c30"><div class="ttname"><a href="namespacearmnn.xhtml#a93d269806f34407695dc10f510001c30">armnn::GetTensorInfo</a></div><div class="ttdeci">const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)</div><div class="ttdoc">float32 helpers </div><div class="ttdef"><b>Definition:</b> <a href="_ref_workload_utils_8hpp_source.xhtml#l00025">RefWorkloadUtils.hpp:25</a></div></div>
+<div class="ttc" id="classarmnn_1_1_encoder_xhtml"><div class="ttname"><a href="classarmnn_1_1_encoder.xhtml">armnn::Encoder< float ></a></div></div>
+<div class="ttc" id="_concatenate_8hpp_xhtml"><div class="ttname"><a href="_concatenate_8hpp.xhtml">Concatenate.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml"><div class="ttname"><a href="namespacearmnn.xhtml">armnn</a></div><div class="ttdoc">Copyright (c) 2020 ARM Limited. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00025">00_introduction.dox:25</a></div></div>
+<div class="ttc" id="structarmnn_1_1_concat_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_concat_queue_descriptor.xhtml">armnn::ConcatQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00102">WorkloadData.hpp:102</a></div></div>
+<div class="ttc" id="_encoders_8hpp_xhtml"><div class="ttname"><a href="_encoders_8hpp.xhtml">Encoders.hpp</a></div></div>
+<div class="ttc" id="structarmnn_1_1_concat_queue_descriptor_xhtml_ab1794eb3e74c9700cd3d500fc06dc2e5"><div class="ttname"><a href="structarmnn_1_1_concat_queue_descriptor.xhtml#ab1794eb3e74c9700cd3d500fc06dc2e5">armnn::ConcatQueueDescriptor::m_ViewOrigins</a></div><div class="ttdeci">std::vector< ViewOrigin > m_ViewOrigins</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00115">WorkloadData.hpp:115</a></div></div>
+<div class="ttc" id="_decoders_8hpp_xhtml"><div class="ttname"><a href="_decoders_8hpp.xhtml">Decoders.hpp</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_a1deafe1b2777bcaadefe2371b3ebbb27"><div class="ttname"><a href="namespacearmnn.xhtml#a1deafe1b2777bcaadefe2371b3ebbb27">armnn::Concatenate</a></div><div class="ttdeci">void Concatenate(const ConcatQueueDescriptor &data)</div><div class="ttdef"><b>Definition:</b> <a href="_concatenate_8cpp_source.xhtml#l00014">Concatenate.cpp:14</a></div></div>
+<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a6abd491bb99ffe88bd472c1ae5a1ed1a"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a6abd491bb99ffe88bd472c1ae5a1ed1a">armnn::QueueDescriptor::m_Outputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Outputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00031">WorkloadData.hpp:31</a></div></div>
+<div class="ttc" id="structarmnn_1_1_queue_descriptor_xhtml_a4b50e46a6810018f3edecfb68b2a76b3"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor.xhtml#a4b50e46a6810018f3edecfb68b2a76b3">armnn::QueueDescriptor::m_Inputs</a></div><div class="ttdeci">std::vector< ITensorHandle * > m_Inputs</div><div class="ttdef"><b>Definition:</b> <a href="_workload_data_8hpp_source.xhtml#l00030">WorkloadData.hpp:30</a></div></div>
+<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml#a157e27d41e9f6b21f0d3c025fa47dc24">armnn::TensorInfo::GetNumDimensions</a></div><div class="ttdeci">unsigned int GetNumDimensions() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00092">Tensor.hpp:92</a></div></div>
+<div class="ttc" id="namespacearmnn_xhtml_abdcd184ed3bd648bb31d385040cafd5d"><div class="ttname"><a href="namespacearmnn.xhtml#abdcd184ed3bd648bb31d385040cafd5d">armnn::MaxNumOfTensorDimensions</a></div><div class="ttdeci">constexpr unsigned int MaxNumOfTensorDimensions</div><div class="ttdef"><b>Definition:</b> <a href="_types_8hpp_source.xhtml#l00018">Types.hpp:18</a></div></div>
+<div class="ttc" id="classarmnn_1_1_decoder_xhtml"><div class="ttname"><a href="classarmnn_1_1_decoder.xhtml">armnn::Decoder< float ></a></div></div>
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