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<li class="navelem"><a class="el" href="dir_5956a3e80a20e8e03eb577bedb92689f.html">gpu</a></li><li class="navelem"><a class="el" href="dir_2be73404b46ec2282840cd36fdb9a907.html">impl</a></li> </ul>
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<div class="title">IVFPQ.cuh</div> </div>
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<div class="contents">
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/**</span></div>
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<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) Facebook, Inc. and its affiliates.</span></div>
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<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div>
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<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * This source code is licensed under the MIT license found in the</span></div>
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<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> * LICENSE file in the root directory of this source tree.</span></div>
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<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> */</span></div>
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<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> </div>
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<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div>
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<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="preprocessor">#pragma once</span></div>
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<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="preprocessor"></span></div>
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<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="preprocessor">#include "IVFBase.cuh"</span></div>
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<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include "../utils/Float16.cuh"</span></div>
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<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div>
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<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
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<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"></span></div>
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<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment">/// Implementing class for IVFPQ on the GPU</span></div>
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<div class="line"><a name="l00017"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFPQ.html"> 17</a></span> <span class="comment"></span><span class="keyword">class </span><a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html">IVFPQ</a> : <span class="keyword">public</span> <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html">IVFBase</a> {</div>
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<div class="line"><a name="l00018"></a><span class="lineno"> 18</span>  <span class="keyword">public</span>:</div>
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<div class="line"><a name="l00019"></a><span class="lineno"> 19</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#a18cfe8bf2178468f3372727d0b0bbc33">IVFPQ</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html">GpuResources</a>* resources,<span class="comment"></span></div>
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<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> /// We do not own this reference</span></div>
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<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"></span> <a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html">FlatIndex</a>* quantizer,</div>
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<div class="line"><a name="l00022"></a><span class="lineno"> 22</span>  <span class="keywordtype">int</span> numSubQuantizers,</div>
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<div class="line"><a name="l00023"></a><span class="lineno"> 23</span>  <span class="keywordtype">int</span> bitsPerSubQuantizer,</div>
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<div class="line"><a name="l00024"></a><span class="lineno"> 24</span>  <span class="keywordtype">float</span>* pqCentroidData,</div>
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<div class="line"><a name="l00025"></a><span class="lineno"> 25</span>  IndicesOptions indicesOptions,</div>
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<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keywordtype">bool</span> useFloat16LookupTables,</div>
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<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  MemorySpace space);</div>
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<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment"></span></div>
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<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment"> /// Returns true if we support PQ in this size</span></div>
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<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="comment"></span> <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#adb58eeacdceb0e0fde1820ca7f116e05">isSupportedPQCodeLength</a>(<span class="keywordtype">int</span> size);</div>
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<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"></span></div>
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<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"> /// For no precomputed codes, is this a supported sub-dimension</span></div>
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<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> /// size?</span></div>
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<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"> /// FIXME: get MM implementation working again</span></div>
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<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment"></span> <span class="keyword">static</span> <span class="keywordtype">bool</span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#a0eedf0295ad73125ee1254173a176674">isSupportedNoPrecomputedSubDimSize</a>(<span class="keywordtype">int</span> dims);</div>
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<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> </div>
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<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  ~<a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html">IVFPQ</a>() <span class="keyword">override</span>;</div>
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<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> <span class="comment"></span></div>
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<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="comment"> /// Enable or disable pre-computed codes</span></div>
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<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#adcee5dbf48c3cb6b8a67f5f392e155fd">setPrecomputedCodes</a>(<span class="keywordtype">bool</span> enable);</div>
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<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="comment"></span></div>
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<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="comment"> /// Adds a set of codes and indices to a list; the data can be</span></div>
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<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="comment"> /// resident on either the host or the device</span></div>
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<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#a9992b38226dc8f92ca2691582fabb675">addCodeVectorsFromCpu</a>(<span class="keywordtype">int</span> listId,</div>
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<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keyword">const</span> <span class="keywordtype">void</span>* codes,</div>
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<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  <span class="keyword">const</span> <span class="keywordtype">long</span>* indices,</div>
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<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="keywordtype">size_t</span> numVecs);</div>
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<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="comment"></span></div>
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<div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="comment"> /// Calcuates the residual and quantizes the vectors, adding them to</span></div>
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<div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="comment"> /// this index</span></div>
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<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"> /// The input data must be on our current device.</span></div>
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<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment"> /// Returns the number of vectors successfully added. Vectors may</span></div>
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<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"> /// not be able to be added because they contain NaNs.</span></div>
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<div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="comment"></span> <span class="keywordtype">int</span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#ab1e07b04b25569cc58c5f3f033f4dab3">classifyAndAddVectors</a>(<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& vecs,</div>
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<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<long, 1, true></a>& indices);</div>
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<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> <span class="comment"></span></div>
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<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> /// Find the approximate k nearest neigbors for `queries` against</span></div>
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<div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"> /// our database</span></div>
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<div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#ab0c458aab9a3d903f31b0e63ce16e623">query</a>(<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& queries,</div>
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<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="keywordtype">int</span> nprobe,</div>
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<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="keywordtype">int</span> k,</div>
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<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& outDistances,</div>
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<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<long, 2, true></a>& outIndices);</div>
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<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment"></span></div>
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<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> <span class="comment"> /// Return the list codes of a particular list back to the CPU</span></div>
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<div class="line"><a name="l00066"></a><span class="lineno"> 66</span> <span class="comment"></span> std::vector<unsigned char> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#a5b349dd021b11b5f48531825359b0657">getListCodes</a>(<span class="keywordtype">int</span> listId) <span class="keyword">const</span>;</div>
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<div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="comment"></span></div>
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<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="comment"> /// Returns our set of sub-quantizers of the form</span></div>
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<div class="line"><a name="l00069"></a><span class="lineno"> 69</span> <span class="comment"> /// (sub q)(code id)(sub dim)</span></div>
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<div class="line"><a name="l00070"></a><span class="lineno"> 70</span> <span class="comment"></span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 3, true></a> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#a3e8bff50f894c243c62e832f923e88e7">getPQCentroids</a>();</div>
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<div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div>
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<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keyword">private</span>:<span class="comment"></span></div>
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<div class="line"><a name="l00073"></a><span class="lineno"> 73</span> <span class="comment"> /// Sets the current product quantizer centroids; the data can be</span></div>
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<div class="line"><a name="l00074"></a><span class="lineno"> 74</span> <span class="comment"> /// resident on either the host or the device. It will be transposed</span></div>
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<div class="line"><a name="l00075"></a><span class="lineno"> 75</span> <span class="comment"> /// into our preferred data layout</span></div>
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<div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="comment"> /// Data must be a row-major, 3-d array of size</span></div>
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<div class="line"><a name="l00077"></a><span class="lineno"> 77</span> <span class="comment"> /// (numSubQuantizers, numSubQuantizerCodes, dim / numSubQuantizers)</span></div>
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<div class="line"><a name="l00078"></a><span class="lineno"> 78</span> <span class="comment"></span> <span class="keywordtype">void</span> setPQCentroids_(<span class="keywordtype">float</span>* data);</div>
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<div class="line"><a name="l00079"></a><span class="lineno"> 79</span> <span class="comment"></span></div>
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<div class="line"><a name="l00080"></a><span class="lineno"> 80</span> <span class="comment"> /// Calculate precomputed residual distance information</span></div>
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<div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="comment"></span> <span class="keywordtype">void</span> precomputeCodes_();</div>
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<div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="comment"></span></div>
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<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="comment"> /// Runs kernels for scanning inverted lists with precomputed codes</span></div>
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<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="comment"></span> <span class="keywordtype">void</span> runPQPrecomputedCodes_(<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& queries,</div>
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<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a>& coarseDistances,</div>
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<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 2, true></a>& coarseIndices,</div>
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<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keywordtype">int</span> k,</div>
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<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& outDistances,</div>
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<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<long, 2, true></a>& outIndices);</div>
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<div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="comment"></span></div>
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<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> <span class="comment"> /// Runs kernels for scanning inverted lists without precomputed codes</span></div>
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<div class="line"><a name="l00092"></a><span class="lineno"> 92</span> <span class="comment"></span> <span class="keywordtype">void</span> runPQNoPrecomputedCodes_(<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& queries,</div>
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<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a>& coarseDistances,</div>
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<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 2, true></a>& coarseIndices,</div>
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<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keywordtype">int</span> k,</div>
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<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& outDistances,</div>
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<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<long, 2, true></a>& outIndices);</div>
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<div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div>
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<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keyword">private</span>:<span class="comment"></span></div>
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<div class="line"><a name="l00100"></a><span class="lineno"> 100</span> <span class="comment"> /// Number of sub-quantizers per vector</span></div>
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<div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="comment"></span> <span class="keyword">const</span> <span class="keywordtype">int</span> numSubQuantizers_;</div>
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<div class="line"><a name="l00102"></a><span class="lineno"> 102</span> <span class="comment"></span></div>
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<div class="line"><a name="l00103"></a><span class="lineno"> 103</span> <span class="comment"> /// Number of bits per sub-quantizer</span></div>
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<div class="line"><a name="l00104"></a><span class="lineno"> 104</span> <span class="comment"></span> <span class="keyword">const</span> <span class="keywordtype">int</span> bitsPerSubQuantizer_;</div>
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<div class="line"><a name="l00105"></a><span class="lineno"> 105</span> <span class="comment"></span></div>
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<div class="line"><a name="l00106"></a><span class="lineno"> 106</span> <span class="comment"> /// Number of per sub-quantizer codes (2^bits)</span></div>
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<div class="line"><a name="l00107"></a><span class="lineno"> 107</span> <span class="comment"></span> <span class="keyword">const</span> <span class="keywordtype">int</span> numSubQuantizerCodes_;</div>
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<div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="comment"></span></div>
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<div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="comment"> /// Number of dimensions per each sub-quantizer</span></div>
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<div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="comment"></span> <span class="keyword">const</span> <span class="keywordtype">int</span> dimPerSubQuantizer_;</div>
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<div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="comment"></span></div>
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<div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="comment"> /// Do we maintain precomputed terms and lookup tables in float16</span></div>
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<div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="comment"> /// form?</span></div>
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<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="comment"></span> <span class="keyword">const</span> <span class="keywordtype">bool</span> useFloat16LookupTables_;</div>
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<div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment"></span></div>
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<div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="comment"> /// On the GPU, we prefer different PQ centroid data layouts for</span></div>
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<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="comment"> /// different purposes.</span></div>
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<div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="comment"> ///</span></div>
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<div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="comment"> /// (sub q)(sub dim)(code id)</span></div>
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<div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="comment"></span> <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 3, true></a> pqCentroidsInnermostCode_;</div>
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<div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="comment"></span></div>
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<div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="comment"> /// (sub q)(code id)(sub dim)</span></div>
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<div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="comment"></span> <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 3, true></a> pqCentroidsMiddleCode_;</div>
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<div class="line"><a name="l00124"></a><span class="lineno"> 124</span> <span class="comment"></span></div>
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<div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="comment"> /// Are precomputed codes enabled? (additional factoring and</span></div>
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<div class="line"><a name="l00126"></a><span class="lineno"> 126</span> <span class="comment"> /// precomputation of the residual distance, to reduce query-time work)</span></div>
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<div class="line"><a name="l00127"></a><span class="lineno"> 127</span> <span class="comment"></span> <span class="keywordtype">bool</span> precomputedCodes_;</div>
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<div class="line"><a name="l00128"></a><span class="lineno"> 128</span> <span class="comment"></span></div>
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<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> <span class="comment"> /// Precomputed term 2 in float form</span></div>
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<div class="line"><a name="l00130"></a><span class="lineno"> 130</span> <span class="comment"> /// (centroid id)(sub q)(code id)</span></div>
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<div class="line"><a name="l00131"></a><span class="lineno"> 131</span> <span class="comment"></span> <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 3, true></a> precomputedCode_;</div>
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<div class="line"><a name="l00132"></a><span class="lineno"> 132</span> </div>
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<div class="line"><a name="l00133"></a><span class="lineno"> 133</span> <span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
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<div class="line"><a name="l00134"></a><span class="lineno"> 134</span> <span class="preprocessor"></span><span class="comment"> /// Precomputed term 2 in half form</span></div>
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<div class="line"><a name="l00135"></a><span class="lineno"> 135</span> <span class="comment"></span> <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<half, 3, true></a> precomputedCodeHalf_;</div>
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<div class="line"><a name="l00136"></a><span class="lineno"> 136</span> <span class="preprocessor">#endif</span></div>
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<div class="line"><a name="l00137"></a><span class="lineno"> 137</span> <span class="preprocessor"></span>};</div>
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<div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div>
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<div class="line"><a name="l00139"></a><span class="lineno"> 139</span> } } <span class="comment">// namespace</span></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFPQ_html_a9992b38226dc8f92ca2691582fabb675"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFPQ.html#a9992b38226dc8f92ca2691582fabb675">faiss::gpu::IVFPQ::addCodeVectorsFromCpu</a></div><div class="ttdeci">void addCodeVectorsFromCpu(int listId, const void *codes, const long *indices, size_t numVecs)</div><div class="ttdef"><b>Definition:</b> <a href="IVFPQ_8cu_source.html#l00345">IVFPQ.cu:345</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1FlatIndex_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1FlatIndex.html">faiss::gpu::FlatIndex</a></div><div class="ttdoc">Holder of GPU resources for a particular flat index. </div><div class="ttdef"><b>Definition:</b> <a href="FlatIndex_8cuh_source.html#l00021">FlatIndex.cuh:21</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html">faiss::gpu::IVFBase</a></div><div class="ttdoc">Base inverted list functionality for IVFFlat and IVFPQ. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00025">IVFBase.cuh:25</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuResources_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuResources.html">faiss::gpu::GpuResources</a></div><div class="ttdef"><b>Definition:</b> <a href="GpuResources_8h_source.html#l00021">GpuResources.h:21</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFPQ_html_adb58eeacdceb0e0fde1820ca7f116e05"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFPQ.html#adb58eeacdceb0e0fde1820ca7f116e05">faiss::gpu::IVFPQ::isSupportedPQCodeLength</a></div><div class="ttdeci">static bool isSupportedPQCodeLength(int size)</div><div class="ttdoc">Returns true if we support PQ in this size. </div><div class="ttdef"><b>Definition:</b> <a href="IVFPQ_8cu_source.html#l00070">IVFPQ.cu:70</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFPQ_html_ab1e07b04b25569cc58c5f3f033f4dab3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFPQ.html#ab1e07b04b25569cc58c5f3f033f4dab3">faiss::gpu::IVFPQ::classifyAndAddVectors</a></div><div class="ttdeci">int classifyAndAddVectors(Tensor< float, 2, true > &vecs, Tensor< long, 1, true > &indices)</div><div class="ttdef"><b>Definition:</b> <a href="IVFPQ_8cu_source.html#l00118">IVFPQ.cu:118</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFPQ_html_ab0c458aab9a3d903f31b0e63ce16e623"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFPQ.html#ab0c458aab9a3d903f31b0e63ce16e623">faiss::gpu::IVFPQ::query</a></div><div class="ttdeci">void query(Tensor< float, 2, true > &queries, int nprobe, int k, Tensor< float, 2, true > &outDistances, Tensor< long, 2, true > &outIndices)</div><div class="ttdef"><b>Definition:</b> <a href="IVFPQ_8cu_source.html#l00516">IVFPQ.cu:516</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFPQ_html_a3e8bff50f894c243c62e832f923e88e7"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFPQ.html#a3e8bff50f894c243c62e832f923e88e7">faiss::gpu::IVFPQ::getPQCentroids</a></div><div class="ttdeci">Tensor< float, 3, true > getPQCentroids()</div><div class="ttdef"><b>Definition:</b> <a href="IVFPQ_8cu_source.html#l00591">IVFPQ.cu:591</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFPQ_html_adcee5dbf48c3cb6b8a67f5f392e155fd"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFPQ.html#adcee5dbf48c3cb6b8a67f5f392e155fd">faiss::gpu::IVFPQ::setPrecomputedCodes</a></div><div class="ttdeci">void setPrecomputedCodes(bool enable)</div><div class="ttdoc">Enable or disable pre-computed codes. </div><div class="ttdef"><b>Definition:</b> <a href="IVFPQ_8cu_source.html#l00100">IVFPQ.cu:100</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFPQ_html_a5b349dd021b11b5f48531825359b0657"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFPQ.html#a5b349dd021b11b5f48531825359b0657">faiss::gpu::IVFPQ::getListCodes</a></div><div class="ttdeci">std::vector< unsigned char > getListCodes(int listId) const </div><div class="ttdoc">Return the list codes of a particular list back to the CPU. </div><div class="ttdef"><b>Definition:</b> <a href="IVFPQ_8cu_source.html#l00583">IVFPQ.cu:583</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html">faiss::gpu::Tensor</a></div><div class="ttdoc">Our tensor type. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00028">Tensor.cuh:28</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1DeviceTensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1DeviceTensor.html">faiss::gpu::DeviceTensor< float, 2, true ></a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFPQ_html_a18cfe8bf2178468f3372727d0b0bbc33"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFPQ.html#a18cfe8bf2178468f3372727d0b0bbc33">faiss::gpu::IVFPQ::IVFPQ</a></div><div class="ttdeci">IVFPQ(GpuResources *resources, FlatIndex *quantizer, int numSubQuantizers, int bitsPerSubQuantizer, float *pqCentroidData, IndicesOptions indicesOptions, bool useFloat16LookupTables, MemorySpace space)</div><div class="ttdef"><b>Definition:</b> <a href="IVFPQ_8cu_source.html#l00033">IVFPQ.cu:33</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFPQ_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFPQ.html">faiss::gpu::IVFPQ</a></div><div class="ttdoc">Implementing class for IVFPQ on the GPU. </div><div class="ttdef"><b>Definition:</b> <a href="IVFPQ_8cuh_source.html#l00017">IVFPQ.cuh:17</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1IVFPQ_html_a0eedf0295ad73125ee1254173a176674"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFPQ.html#a0eedf0295ad73125ee1254173a176674">faiss::gpu::IVFPQ::isSupportedNoPrecomputedSubDimSize</a></div><div class="ttdeci">static bool isSupportedNoPrecomputedSubDimSize(int dims)</div><div class="ttdef"><b>Definition:</b> <a href="IVFPQ_8cu_source.html#l00095">IVFPQ.cu:95</a></div></div>
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