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<a href="backends_2reference_2workloads_2_gather_8cpp.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> </div><div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="preprocessor">#include "<a class="code" href="_gather_8hpp.html">Gather.hpp</a>"</span></div><div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div><div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="preprocessor">#include "<a class="code" href="_ref_workload_utils_8hpp.html">RefWorkloadUtils.hpp</a>"</span></div><div class="line"><a name="l00009"></a><span class="lineno"> 9</span> </div><div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor">#include <<a class="code" href="_workload_data_8hpp.html">backendsCommon/WorkloadData.hpp</a>></span></div><div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div><div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <boost/core/ignore_unused.hpp></span></div><div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <boost/numeric/conversion/cast.hpp></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="keyword">namespace </span><a class="code" href="namespacearmnn.html">armnn</a></div><div class="line"><a name="l00016"></a><span class="lineno"> 16</span> {</div><div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div><div class="line"><a name="l00018"></a><span class="lineno"><a class="line" href="namespacearmnn.html#a66004b2326f8ccb1faa71d5efa186633"> 18</a></span> <span class="keywordtype">void</span> <a class="code" href="namespacearmnn.html#a66004b2326f8ccb1faa71d5efa186633">Gather</a>(<span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& paramsInfo,</div><div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& indicesInfo,</div><div class="line"><a name="l00020"></a><span class="lineno"> 20</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_info.html">TensorInfo</a>& outputInfo,</div><div class="line"><a name="l00021"></a><span class="lineno"> 21</span>  <a class="code" href="classarmnn_1_1_decoder.html">Decoder<float></a>& params,</div><div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="keyword">const</span> int32_t* indices,</div><div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <a class="code" href="classarmnn_1_1_encoder.html">Encoder<float></a>& output)</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>  boost::ignore_unused(outputInfo);</div><div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keyword">const</span> <a class="code" href="classarmnn_1_1_tensor_shape.html">TensorShape</a>& paramsShape = paramsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8b5d0f8a24e9d9238f412260a552acf8">GetShape</a>();</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="keywordtype">unsigned</span> <span class="keywordtype">int</span> paramsProduct = 1;</div><div class="line"><a name="l00029"></a><span class="lineno"> 29</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 1; i < paramsInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a157e27d41e9f6b21f0d3c025fa47dc24">GetNumDimensions</a>(); ++i)</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>  paramsProduct = paramsProduct * paramsShape[i];</div><div class="line"><a name="l00032"></a><span class="lineno"> 32</span>  }</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outIndex = 0;</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> i = 0; i < indicesInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>(); ++i)</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>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> indx = boost::numeric_cast<<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>>(indices[i]);</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>  BOOST_ASSERT(indices[i] >= 0 && indx < paramsShape[0]);</div><div class="line"><a name="l00040"></a><span class="lineno"> 40</span> </div><div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> startOffset = indx * paramsProduct;</div><div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> endOffset = startOffset + paramsProduct;</div><div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div><div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> j = startOffset; j < endOffset; ++j)</div><div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  {</div><div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  params[j];</div><div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordtype">float</span> outputValue = params.<a class="code" href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">Get</a>();</div><div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  output[outIndex];</div><div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  output.<a class="code" href="classarmnn_1_1_encoder.html#ae3b62b846a9c239f332830b9e36030eb">Set</a>(outputValue);</div><div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  ++outIndex;</div><div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  }</div><div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  }</div><div class="line"><a name="l00053"></a><span class="lineno"> 53</span> </div><div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  BOOST_ASSERT(outIndex == outputInfo.<a class="code" href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">GetNumElements</a>());</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="comment">//namespace armnn</span></div><div class="ttc" id="_gather_8hpp_html"><div class="ttname"><a href="_gather_8hpp.html">Gather.hpp</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_a157e27d41e9f6b21f0d3c025fa47dc24"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#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.html#l00092">Tensor.hpp:92</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00053">Tensor.hpp:53</a></div></div>
<div class="ttc" id="namespacearmnn_html_a66004b2326f8ccb1faa71d5efa186633"><div class="ttname"><a href="namespacearmnn.html#a66004b2326f8ccb1faa71d5efa186633">armnn::Gather</a></div><div class="ttdeci">void Gather(const TensorInfo &paramsInfo, const TensorInfo &indicesInfo, const TensorInfo &outputInfo, Decoder< float > &params, const int32_t *indices, Encoder< float > &output)</div><div class="ttdef"><b>Definition:</b> <a href="backends_2reference_2workloads_2_gather_8cpp_source.html#l00018">Gather.cpp:18</a></div></div>
<div class="ttc" id="classarmnn_1_1_decoder_html"><div class="ttname"><a href="classarmnn_1_1_decoder.html">armnn::Decoder< float ></a></div></div>
<div class="ttc" id="classarmnn_1_1_encoder_html"><div class="ttname"><a href="classarmnn_1_1_encoder.html">armnn::Encoder< float ></a></div></div>
<div class="ttc" id="_workload_data_8hpp_html"><div class="ttname"><a href="_workload_data_8hpp.html">WorkloadData.hpp</a></div></div>
<div class="ttc" id="namespacearmnn_html"><div class="ttname"><a href="namespacearmnn.html">armnn</a></div><div class="ttdef"><b>Definition:</b> <a href="_backend_helper_8hpp_source.html#l00011">BackendHelper.hpp:11</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_shape_html"><div class="ttname"><a href="classarmnn_1_1_tensor_shape.html">armnn::TensorShape</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00020">Tensor.hpp:20</a></div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_a8846406ac37fbd2204f0be16ee05d5b7"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#a8846406ac37fbd2204f0be16ee05d5b7">armnn::TensorInfo::GetNumElements</a></div><div class="ttdeci">unsigned int GetNumElements() const</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.html#l00093">Tensor.hpp:93</a></div></div>
<div class="ttc" id="classarmnn_1_1_decoder_html_ac729108381e2340bea12877971713ecb"><div class="ttname"><a href="classarmnn_1_1_decoder.html#ac729108381e2340bea12877971713ecb">armnn::Decoder::Get</a></div><div class="ttdeci">virtual IType Get() const =0</div></div>
<div class="ttc" id="classarmnn_1_1_tensor_info_html_a8b5d0f8a24e9d9238f412260a552acf8"><div class="ttname"><a href="classarmnn_1_1_tensor_info.html#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.html#l00088">Tensor.hpp:88</a></div></div>
<div class="ttc" id="classarmnn_1_1_encoder_html_ae3b62b846a9c239f332830b9e36030eb"><div class="ttname"><a href="classarmnn_1_1_encoder.html#ae3b62b846a9c239f332830b9e36030eb">armnn::Encoder::Set</a></div><div class="ttdeci">virtual void Set(IType right)=0</div></div>
<div class="ttc" id="_ref_workload_utils_8hpp_html"><div class="ttname"><a href="_ref_workload_utils_8hpp.html">RefWorkloadUtils.hpp</a></div></div>
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