mirror of
https://github.com/facebookresearch/faiss.git
synced 2025-06-03 21:54:02 +08:00
various bugfixes from github issues kmean with some frozen centroids GPU better tiling for large flat datasets default AVX for vector ops
845 lines
131 KiB
HTML
845 lines
131 KiB
HTML
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
|
<html xmlns="http://www.w3.org/1999/xhtml">
|
|
<head>
|
|
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
|
|
<meta http-equiv="X-UA-Compatible" content="IE=9"/>
|
|
<meta name="generator" content="Doxygen 1.8.5"/>
|
|
<title>Faiss: /data/users/matthijs/github_faiss/faiss/gpu/impl/IVFPQ.cu Source File</title>
|
|
<link href="tabs.css" rel="stylesheet" type="text/css"/>
|
|
<script type="text/javascript" src="jquery.js"></script>
|
|
<script type="text/javascript" src="dynsections.js"></script>
|
|
<link href="search/search.css" rel="stylesheet" type="text/css"/>
|
|
<script type="text/javascript" src="search/search.js"></script>
|
|
<script type="text/javascript">
|
|
$(document).ready(function() { searchBox.OnSelectItem(0); });
|
|
</script>
|
|
<link href="doxygen.css" rel="stylesheet" type="text/css" />
|
|
</head>
|
|
<body>
|
|
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
|
|
<div id="titlearea">
|
|
<table cellspacing="0" cellpadding="0">
|
|
<tbody>
|
|
<tr style="height: 56px;">
|
|
<td style="padding-left: 0.5em;">
|
|
<div id="projectname">Faiss
|
|
</div>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
</div>
|
|
<!-- end header part -->
|
|
<!-- Generated by Doxygen 1.8.5 -->
|
|
<script type="text/javascript">
|
|
var searchBox = new SearchBox("searchBox", "search",false,'Search');
|
|
</script>
|
|
<div id="navrow1" class="tabs">
|
|
<ul class="tablist">
|
|
<li><a href="index.html"><span>Main Page</span></a></li>
|
|
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
|
|
<li><a href="annotated.html"><span>Classes</span></a></li>
|
|
<li class="current"><a href="files.html"><span>Files</span></a></li>
|
|
<li>
|
|
<div id="MSearchBox" class="MSearchBoxInactive">
|
|
<span class="left">
|
|
<img id="MSearchSelect" src="search/mag_sel.png"
|
|
onmouseover="return searchBox.OnSearchSelectShow()"
|
|
onmouseout="return searchBox.OnSearchSelectHide()"
|
|
alt=""/>
|
|
<input type="text" id="MSearchField" value="Search" accesskey="S"
|
|
onfocus="searchBox.OnSearchFieldFocus(true)"
|
|
onblur="searchBox.OnSearchFieldFocus(false)"
|
|
onkeyup="searchBox.OnSearchFieldChange(event)"/>
|
|
</span><span class="right">
|
|
<a id="MSearchClose" href="javascript:searchBox.CloseResultsWindow()"><img id="MSearchCloseImg" border="0" src="search/close.png" alt=""/></a>
|
|
</span>
|
|
</div>
|
|
</li>
|
|
</ul>
|
|
</div>
|
|
<div id="navrow2" class="tabs2">
|
|
<ul class="tablist">
|
|
<li><a href="files.html"><span>File List</span></a></li>
|
|
</ul>
|
|
</div>
|
|
<!-- window showing the filter options -->
|
|
<div id="MSearchSelectWindow"
|
|
onmouseover="return searchBox.OnSearchSelectShow()"
|
|
onmouseout="return searchBox.OnSearchSelectHide()"
|
|
onkeydown="return searchBox.OnSearchSelectKey(event)">
|
|
<a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(0)"><span class="SelectionMark"> </span>All</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(1)"><span class="SelectionMark"> </span>Classes</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(2)"><span class="SelectionMark"> </span>Namespaces</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(3)"><span class="SelectionMark"> </span>Functions</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(4)"><span class="SelectionMark"> </span>Variables</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(5)"><span class="SelectionMark"> </span>Typedefs</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(6)"><span class="SelectionMark"> </span>Enumerations</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(7)"><span class="SelectionMark"> </span>Enumerator</a><a class="SelectItem" href="javascript:void(0)" onclick="searchBox.OnSelectItem(8)"><span class="SelectionMark"> </span>Friends</a></div>
|
|
|
|
<!-- iframe showing the search results (closed by default) -->
|
|
<div id="MSearchResultsWindow">
|
|
<iframe src="javascript:void(0)" frameborder="0"
|
|
name="MSearchResults" id="MSearchResults">
|
|
</iframe>
|
|
</div>
|
|
|
|
<div id="nav-path" class="navpath">
|
|
<ul>
|
|
<li class="navelem"><a class="el" href="dir_6b3ae6988449b0834e9596fad5d75199.html">gpu</a></li><li class="navelem"><a class="el" href="dir_49d1182a3b8dfb62757c53ae905481ad.html">impl</a></li> </ul>
|
|
</div>
|
|
</div><!-- top -->
|
|
<div class="header">
|
|
<div class="headertitle">
|
|
<div class="title">IVFPQ.cu</div> </div>
|
|
</div><!--header-->
|
|
<div class="contents">
|
|
<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) 2015-present, Facebook, Inc.</span></div>
|
|
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * All rights reserved.</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="comment"> * This source code is licensed under the BSD+Patents license found in the</span></div>
|
|
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * LICENSE file in the root directory of this source tree.</span></div>
|
|
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> */</span></div>
|
|
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div>
|
|
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment">// Copyright 2004-present Facebook. All Rights Reserved.</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="preprocessor">#include "IVFPQ.cuh"</span></div>
|
|
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include "../GpuResources.h"</span></div>
|
|
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include "BroadcastSum.cuh"</span></div>
|
|
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include "Distance.cuh"</span></div>
|
|
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include "FlatIndex.cuh"</span></div>
|
|
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include "InvertedListAppend.cuh"</span></div>
|
|
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include "L2Norm.cuh"</span></div>
|
|
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include "PQCodeDistances.cuh"</span></div>
|
|
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include "PQScanMultiPassNoPrecomputed.cuh"</span></div>
|
|
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include "PQScanMultiPassPrecomputed.cuh"</span></div>
|
|
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include "RemapIndices.h"</span></div>
|
|
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="preprocessor">#include "VectorResidual.cuh"</span></div>
|
|
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="preprocessor">#include "../utils/DeviceDefs.cuh"</span></div>
|
|
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="preprocessor">#include "../utils/DeviceUtils.h"</span></div>
|
|
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="preprocessor">#include "../utils/HostTensor.cuh"</span></div>
|
|
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="preprocessor">#include "../utils/MatrixMult.cuh"</span></div>
|
|
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="preprocessor">#include "../utils/NoTypeTensor.cuh"</span></div>
|
|
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="preprocessor">#include "../utils/Transpose.cuh"</span></div>
|
|
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="preprocessor">#include <limits></span></div>
|
|
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="preprocessor">#include <thrust/host_vector.h></span></div>
|
|
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="preprocessor">#include <unordered_map></span></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> <span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</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="classfaiss_1_1gpu_1_1IVFPQ.html#a18cfe8bf2178468f3372727d0b0bbc33"> 35</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#a18cfe8bf2178468f3372727d0b0bbc33">IVFPQ::IVFPQ</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html">GpuResources</a>* resources,</div>
|
|
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html">FlatIndex</a>* quantizer,</div>
|
|
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordtype">int</span> numSubQuantizers,</div>
|
|
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  <span class="keywordtype">int</span> bitsPerSubQuantizer,</div>
|
|
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="keywordtype">float</span>* pqCentroidData,</div>
|
|
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  IndicesOptions indicesOptions,</div>
|
|
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">bool</span> useFloat16LookupTables,</div>
|
|
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  MemorySpace space) :</div>
|
|
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html">IVFBase</a>(resources,</div>
|
|
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  quantizer,</div>
|
|
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  numSubQuantizers,</div>
|
|
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span>  indicesOptions,</div>
|
|
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  space),</div>
|
|
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  numSubQuantizers_(numSubQuantizers),</div>
|
|
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  bitsPerSubQuantizer_(bitsPerSubQuantizer),</div>
|
|
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  numSubQuantizerCodes_(utils::pow2(bitsPerSubQuantizer_)),</div>
|
|
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  dimPerSubQuantizer_(dim_ / numSubQuantizers),</div>
|
|
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  precomputedCodes_(false),</div>
|
|
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  useFloat16LookupTables_(useFloat16LookupTables) {</div>
|
|
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  FAISS_ASSERT(pqCentroidData);</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>  FAISS_ASSERT(bitsPerSubQuantizer_ <= 8);</div>
|
|
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  FAISS_ASSERT(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#aba3e3cfa469e5187f2d553fff10e0250">dim_</a> % numSubQuantizers_ == 0);</div>
|
|
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  FAISS_ASSERT(<a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#adb58eeacdceb0e0fde1820ca7f116e05">isSupportedPQCodeLength</a>(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>));</div>
|
|
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span> </div>
|
|
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="preprocessor">#ifndef FAISS_USE_FLOAT16</span></div>
|
|
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="preprocessor"></span> FAISS_ASSERT(!useFloat16LookupTables_);</div>
|
|
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="preprocessor"></span></div>
|
|
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  setPQCentroids_(pqCentroidData);</div>
|
|
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span> }</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> IVFPQ::~IVFPQ() {</div>
|
|
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> }</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> </div>
|
|
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span> <span class="keywordtype">bool</span></div>
|
|
<div class="line"><a name="l00072"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFPQ.html#adb58eeacdceb0e0fde1820ca7f116e05"> 72</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#adb58eeacdceb0e0fde1820ca7f116e05">IVFPQ::isSupportedPQCodeLength</a>(<span class="keywordtype">int</span> size) {</div>
|
|
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordflow">switch</span> (size) {</div>
|
|
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  <span class="keywordflow">case</span> 1:</div>
|
|
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <span class="keywordflow">case</span> 2:</div>
|
|
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keywordflow">case</span> 3:</div>
|
|
<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  <span class="keywordflow">case</span> 4:</div>
|
|
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <span class="keywordflow">case</span> 8:</div>
|
|
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keywordflow">case</span> 12:</div>
|
|
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordflow">case</span> 16:</div>
|
|
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="keywordflow">case</span> 20:</div>
|
|
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="keywordflow">case</span> 24:</div>
|
|
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordflow">case</span> 28:</div>
|
|
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <span class="keywordflow">case</span> 32:</div>
|
|
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  <span class="keywordflow">case</span> 40:</div>
|
|
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span>  <span class="keywordflow">case</span> 48:</div>
|
|
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keywordflow">case</span> 56: <span class="comment">// only supported with float16</span></div>
|
|
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="keywordflow">case</span> 64: <span class="comment">// only supported with float16</span></div>
|
|
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  <span class="keywordflow">case</span> 96: <span class="comment">// only supported with float16</span></div>
|
|
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  <span class="keywordflow">return</span> <span class="keyword">true</span>;</div>
|
|
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keywordflow">default</span>:</div>
|
|
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keywordflow">return</span> <span class="keyword">false</span>;</div>
|
|
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  }</div>
|
|
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span> }</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">bool</span></div>
|
|
<div class="line"><a name="l00097"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFPQ.html#a0eedf0295ad73125ee1254173a176674"> 97</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#a0eedf0295ad73125ee1254173a176674">IVFPQ::isSupportedNoPrecomputedSubDimSize</a>(<span class="keywordtype">int</span> dims) {</div>
|
|
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  <span class="keywordflow">return</span> faiss::gpu::isSupportedNoPrecomputedSubDimSize(dims);</div>
|
|
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span> }</div>
|
|
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span> </div>
|
|
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00102"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFPQ.html#adcee5dbf48c3cb6b8a67f5f392e155fd"> 102</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#adcee5dbf48c3cb6b8a67f5f392e155fd">IVFPQ::setPrecomputedCodes</a>(<span class="keywordtype">bool</span> enable) {</div>
|
|
<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordflow">if</span> (precomputedCodes_ != enable) {</div>
|
|
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  precomputedCodes_ = enable;</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>  <span class="keywordflow">if</span> (precomputedCodes_) {</div>
|
|
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  precomputeCodes_();</div>
|
|
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <span class="comment">// Clear out old precomputed code data</span></div>
|
|
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  precomputedCode_ = std::move(<a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 3, true></a>());</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="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
|
|
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="preprocessor"></span> precomputedCodeHalf_ = std::move(<a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<half, 3, true></a>());</div>
|
|
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="preprocessor"></span> }</div>
|
|
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  }</div>
|
|
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> }</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="keywordtype">int</span></div>
|
|
<div class="line"><a name="l00120"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFPQ.html#ab1e07b04b25569cc58c5f3f033f4dab3"> 120</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#ab1e07b04b25569cc58c5f3f033f4dab3">IVFPQ::classifyAndAddVectors</a>(<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& vecs,</div>
|
|
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<long, 1, true></a>& indices) {</div>
|
|
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  FAISS_ASSERT(vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0) == indices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0));</div>
|
|
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  FAISS_ASSERT(vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(1) == <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#aba3e3cfa469e5187f2d553fff10e0250">dim_</a>);</div>
|
|
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </div>
|
|
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  FAISS_ASSERT(!<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>->getUseFloat16());</div>
|
|
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keyword">auto</span>& coarseCentroids = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a12058744ffb3fbcbb047872449269c06">getVectorsFloat32Ref</a>();</div>
|
|
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keyword">auto</span>& mem = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a1dda2dc3db1bd62cde6657c5cdbfb6e1">getMemoryManagerCurrentDevice</a>();</div>
|
|
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>();</div>
|
|
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div>
|
|
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="comment">// Number of valid vectors that we actually add; we return this</span></div>
|
|
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  <span class="keywordtype">int</span> numAdded = 0;</div>
|
|
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span> </div>
|
|
<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="comment">// We don't actually need this</span></div>
|
|
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a> listDistance(mem, {vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), 1}, stream);</div>
|
|
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  <span class="comment">// We use this</span></div>
|
|
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 2, true></a> listIds2d(mem, {vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), 1}, stream);</div>
|
|
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keyword">auto</span> listIds = listIds2d.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a74dbc09519c9c14479b2d18f2e5042e8">view</a><1>({vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0)});</div>
|
|
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div>
|
|
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>->query(vecs, 1, listDistance, listIds2d, <span class="keyword">false</span>);</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">// Copy the lists that we wish to append to back to the CPU</span></div>
|
|
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  <span class="comment">// FIXME: really this can be into pinned memory and a true async</span></div>
|
|
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// copy on a different stream; we can start the copy early, but it's</span></div>
|
|
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="comment">// tiny</span></div>
|
|
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<int, 1, true></a> listIdsHost(listIds, stream);</div>
|
|
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span> </div>
|
|
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span>  <span class="comment">// Calculate the residual for each closest centroid</span></div>
|
|
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a> residuals(</div>
|
|
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  mem, {vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), vecs.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(1)}, stream);</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>  runCalcResidual(vecs, coarseCentroids, listIds, residuals, stream);</div>
|
|
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span> </div>
|
|
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="comment">// Residuals are in the form</span></div>
|
|
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  <span class="comment">// (vec x numSubQuantizer x dimPerSubQuantizer)</span></div>
|
|
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="comment">// transpose to</span></div>
|
|
<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="comment">// (numSubQuantizer x vec x dimPerSubQuantizer)</span></div>
|
|
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keyword">auto</span> residualsView = residuals.view<3>(</div>
|
|
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  {residuals.getSize(0), numSubQuantizers_, dimPerSubQuantizer_});</div>
|
|
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span> </div>
|
|
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 3, true></a> residualsTranspose(</div>
|
|
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  mem,</div>
|
|
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  {numSubQuantizers_, residuals.getSize(0), dimPerSubQuantizer_},</div>
|
|
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  stream);</div>
|
|
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div>
|
|
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  runTransposeAny(residualsView, 0, 1, residualsTranspose, stream);</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">// Get the product quantizer centroids in the form</span></div>
|
|
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="comment">// (numSubQuantizer x numSubQuantizerCodes x dimPerSubQuantizer)</span></div>
|
|
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="comment">// which is pqCentroidsMiddleCode_</span></div>
|
|
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span> </div>
|
|
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="comment">// We now have a batch operation to find the top-1 distances:</span></div>
|
|
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <span class="comment">// batch size: numSubQuantizer</span></div>
|
|
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  <span class="comment">// centroids: (numSubQuantizerCodes x dimPerSubQuantizer)</span></div>
|
|
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="comment">// residuals: (vec x dimPerSubQuantizer)</span></div>
|
|
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="comment">// => (numSubQuantizer x vec x 1)</span></div>
|
|
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span> </div>
|
|
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 3, true></a> closestSubQDistance(</div>
|
|
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  mem, {numSubQuantizers_, residuals.getSize(0), 1}, stream);</div>
|
|
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 3, true></a> closestSubQIndex(</div>
|
|
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  mem, {numSubQuantizers_, residuals.getSize(0), 1}, stream);</div>
|
|
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span> </div>
|
|
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> subQ = 0; subQ < numSubQuantizers_; ++subQ) {</div>
|
|
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="keyword">auto</span> closestSubQDistanceView = closestSubQDistance[subQ].<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a74dbc09519c9c14479b2d18f2e5042e8">view</a>();</div>
|
|
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keyword">auto</span> closestSubQIndexView = closestSubQIndex[subQ].view();</div>
|
|
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span> </div>
|
|
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="keyword">auto</span> pqCentroidsMiddleCodeView = pqCentroidsMiddleCode_[subQ].<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a74dbc09519c9c14479b2d18f2e5042e8">view</a>();</div>
|
|
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keyword">auto</span> residualsTransposeView = residualsTranspose[subQ].view();</div>
|
|
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div>
|
|
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  runL2Distance(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>,</div>
|
|
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  pqCentroidsMiddleCodeView,</div>
|
|
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keyword">nullptr</span>, <span class="comment">// no transposed storage</span></div>
|
|
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keyword">nullptr</span>, <span class="comment">// no precomputed norms</span></div>
|
|
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  residualsTransposeView,</div>
|
|
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  1,</div>
|
|
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  closestSubQDistanceView,</div>
|
|
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  closestSubQIndexView,</div>
|
|
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="comment">// We don't care about distances</span></div>
|
|
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  <span class="keyword">true</span>);</div>
|
|
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  }</div>
|
|
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span> </div>
|
|
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  <span class="comment">// Now, we have the nearest sub-q centroid for each slice of the</span></div>
|
|
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="comment">// residual vector.</span></div>
|
|
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  <span class="keyword">auto</span> closestSubQIndexView = closestSubQIndex.view<2>(</div>
|
|
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span>  {numSubQuantizers_, residuals.getSize(0)});</div>
|
|
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span> </div>
|
|
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="comment">// Transpose this for easy use</span></div>
|
|
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 2, true></a> encodings(</div>
|
|
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  mem, {residuals.getSize(0), numSubQuantizers_}, stream);</div>
|
|
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span> </div>
|
|
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  runTransposeAny(closestSubQIndexView, 0, 1, encodings, stream);</div>
|
|
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span> </div>
|
|
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  <span class="comment">// Now we add the encoded vectors to the individual lists</span></div>
|
|
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  <span class="comment">// First, make sure that there is space available for adding the new</span></div>
|
|
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="comment">// encoded vectors and indices</span></div>
|
|
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div>
|
|
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="comment">// list id -> # being added</span></div>
|
|
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  std::unordered_map<int, int> assignCounts;</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>  <span class="comment">// vector id -> offset in list</span></div>
|
|
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="comment">// (we already have vector id -> list id in listIds)</span></div>
|
|
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<int, 1, true></a> listOffsetHost({listIdsHost.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0)});</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>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < listIdsHost.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0); ++i) {</div>
|
|
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keywordtype">int</span> listId = listIdsHost[i];</div>
|
|
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span> </div>
|
|
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  <span class="comment">// Add vector could be invalid (contains NaNs etc)</span></div>
|
|
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="keywordflow">if</span> (listId < 0) {</div>
|
|
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  listOffsetHost[i] = -1;</div>
|
|
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="keywordflow">continue</span>;</div>
|
|
<div class="line"><a name="l00230"></a><span class="lineno"> 230</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>  FAISS_ASSERT(listId < <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#accc4d96c14643e5f471220cb1e92ac70">numLists_</a>);</div>
|
|
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  ++numAdded;</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>  <span class="keywordtype">int</span> offset = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>[listId]->size() / <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>;</div>
|
|
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span> </div>
|
|
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  <span class="keyword">auto</span> it = assignCounts.find(listId);</div>
|
|
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="keywordflow">if</span> (it != assignCounts.end()) {</div>
|
|
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  offset += it->second;</div>
|
|
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  it->second++;</div>
|
|
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  assignCounts[listId] = 1;</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> </div>
|
|
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  listOffsetHost[i] = offset;</div>
|
|
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  }</div>
|
|
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span> </div>
|
|
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="comment">// If we didn't add anything (all invalid vectors), no need to</span></div>
|
|
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="comment">// continue</span></div>
|
|
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordflow">if</span> (numAdded == 0) {</div>
|
|
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="keywordflow">return</span> 0;</div>
|
|
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  }</div>
|
|
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span> </div>
|
|
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="comment">// We need to resize the data structures for the inverted lists on</span></div>
|
|
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="comment">// the GPUs, which means that they might need reallocation, which</span></div>
|
|
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <span class="comment">// means that their base address may change. Figure out the new base</span></div>
|
|
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  <span class="comment">// addresses, and update those in a batch on the device</span></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>  <span class="comment">// Resize all of the lists that we are appending to</span></div>
|
|
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& counts : assignCounts) {</div>
|
|
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keyword">auto</span>& codes = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>[counts.first];</div>
|
|
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  codes->resize(codes->size() + counts.second * <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>,</div>
|
|
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  stream);</div>
|
|
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordtype">int</span> newNumVecs = (int) (codes->size() / <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>);</div>
|
|
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span> </div>
|
|
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keyword">auto</span>& indices = deviceListIndices_[counts.first];</div>
|
|
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="keywordflow">if</span> ((<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_32_BIT) ||</div>
|
|
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_64_BIT)) {</div>
|
|
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keywordtype">size_t</span> indexSize =</div>
|
|
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_32_BIT) ? <span class="keyword">sizeof</span>(<span class="keywordtype">int</span>) : <span class="keyword">sizeof</span>(long);</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>  indices->resize(indices->size() + counts.second * indexSize, stream);</div>
|
|
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_CPU) {</div>
|
|
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="comment">// indices are stored on the CPU side</span></div>
|
|
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  FAISS_ASSERT(counts.first < <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">listOffsetToUserIndex_</a>.size());</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="keyword">auto</span>& userIndices = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">listOffsetToUserIndex_</a>[counts.first];</div>
|
|
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  userIndices.resize(newNumVecs);</div>
|
|
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="comment">// indices are not stored on the GPU or CPU side</span></div>
|
|
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  FAISS_ASSERT(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_IVF);</div>
|
|
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  }</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>  <span class="comment">// This is used by the multi-pass query to decide how much scratch</span></div>
|
|
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="comment">// space to allocate for intermediate results</span></div>
|
|
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a> = std::max(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a>, newNumVecs);</div>
|
|
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  }</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="comment">// Update all pointers and sizes on the device for lists that we</span></div>
|
|
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <span class="comment">// appended to</span></div>
|
|
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  {</div>
|
|
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  std::vector<int> listIds(assignCounts.size());</div>
|
|
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keywordtype">int</span> i = 0;</div>
|
|
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keywordflow">for</span> (<span class="keyword">auto</span>& counts : assignCounts) {</div>
|
|
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  listIds[i++] = counts.first;</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> </div>
|
|
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#acc695610c9513952b8d234dc0db78e5c">updateDeviceListInfo_</a>(listIds, stream);</div>
|
|
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  }</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="comment">// If we're maintaining the indices on the CPU side, update our</span></div>
|
|
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  <span class="comment">// map. We already resized our map above.</span></div>
|
|
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_CPU) {</div>
|
|
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="comment">// We need to maintain the indices on the CPU side</span></div>
|
|
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<long, 1, true></a> hostIndices(indices, stream);</div>
|
|
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span> </div>
|
|
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < hostIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0); ++i) {</div>
|
|
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keywordtype">int</span> listId = listIdsHost[i];</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">// Add vector could be invalid (contains NaNs etc)</span></div>
|
|
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keywordflow">if</span> (listId < 0) {</div>
|
|
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  <span class="keywordflow">continue</span>;</div>
|
|
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  }</div>
|
|
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span> </div>
|
|
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordtype">int</span> offset = listOffsetHost[i];</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>  FAISS_ASSERT(listId < <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">listOffsetToUserIndex_</a>.size());</div>
|
|
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  <span class="keyword">auto</span>& userIndices = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">listOffsetToUserIndex_</a>[listId];</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>  FAISS_ASSERT(offset < userIndices.size());</div>
|
|
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  userIndices[offset] = hostIndices[i];</div>
|
|
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  }</div>
|
|
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  }</div>
|
|
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span> </div>
|
|
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="comment">// We similarly need to actually append the new encoded vectors</span></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>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 1, true></a> listOffset(mem, listOffsetHost, stream);</div>
|
|
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div>
|
|
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="comment">// This kernel will handle appending each encoded vector + index to</span></div>
|
|
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="comment">// the appropriate list</span></div>
|
|
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  runIVFPQInvertedListAppend(listIds,</div>
|
|
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  listOffset,</div>
|
|
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  encodings,</div>
|
|
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  indices,</div>
|
|
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a96240a08b42bd1913e2286d7d514fc56">deviceListDataPointers_</a>,</div>
|
|
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a9aedcf0e6a20b908980ae96d73461f4c">deviceListIndexPointers_</a>,</div>
|
|
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a>,</div>
|
|
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  stream);</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> </div>
|
|
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keywordflow">return</span> numAdded;</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> </div>
|
|
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00346"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFPQ.html#a9992b38226dc8f92ca2691582fabb675"> 346</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#a9992b38226dc8f92ca2691582fabb675">IVFPQ::addCodeVectorsFromCpu</a>(<span class="keywordtype">int</span> listId,</div>
|
|
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  <span class="keyword">const</span> <span class="keywordtype">void</span>* codes,</div>
|
|
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keyword">const</span> <span class="keywordtype">long</span>* indices,</div>
|
|
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keywordtype">size_t</span> numVecs) {</div>
|
|
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  <span class="comment">// This list must already exist</span></div>
|
|
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  FAISS_ASSERT(listId < <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>.size());</div>
|
|
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>();</div>
|
|
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span> </div>
|
|
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="comment">// If there's nothing to add, then there's nothing we have to do</span></div>
|
|
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="keywordflow">if</span> (numVecs == 0) {</div>
|
|
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="keywordflow">return</span>;</div>
|
|
<div class="line"><a name="l00357"></a><span class="lineno"> 357</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="keywordtype">size_t</span> lengthInBytes = numVecs * <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>;</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>  <span class="keyword">auto</span>& listCodes = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>[listId];</div>
|
|
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="keyword">auto</span> prevCodeData = listCodes->data();</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">// We only have int32 length representations on the GPU per each</span></div>
|
|
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="comment">// list; the length is in sizeof(char)</span></div>
|
|
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  FAISS_ASSERT(listCodes->size() % bytesPerVector_ == 0);</div>
|
|
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  FAISS_ASSERT(listCodes->size() + lengthInBytes <=</div>
|
|
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  (size_t) std::numeric_limits<int>::max());</div>
|
|
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span> </div>
|
|
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  listCodes->append((<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>*) codes,</div>
|
|
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  lengthInBytes,</div>
|
|
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  stream,</div>
|
|
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  <span class="keyword">true</span> <span class="comment">/* exact reserved size */</span>);</div>
|
|
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span> </div>
|
|
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="comment">// Handle the indices as well</span></div>
|
|
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a5027720549de98f4e609d6339099df35">addIndicesFromCpu_</a>(listId, indices, numVecs);</div>
|
|
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div>
|
|
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="comment">// This list address may have changed due to vector resizing, but</span></div>
|
|
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="comment">// only bother updating it on the device if it has changed</span></div>
|
|
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keywordflow">if</span> (prevCodeData != listCodes->data()) {</div>
|
|
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a96240a08b42bd1913e2286d7d514fc56">deviceListDataPointers_</a>[listId] = listCodes->data();</div>
|
|
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  }</div>
|
|
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span> </div>
|
|
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="comment">// And our size has changed too</span></div>
|
|
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  <span class="keywordtype">int</span> listLength = listCodes->size() / <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>;</div>
|
|
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a3a1c2031a4763f7d55bc8a400c63af66">deviceListLengths_</a>[listId] = listLength;</div>
|
|
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span> </div>
|
|
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="comment">// We update this as well, since the multi-pass algorithm uses it</span></div>
|
|
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a> = std::max(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a>, listLength);</div>
|
|
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span> </div>
|
|
<div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  <span class="comment">// device_vector add is potentially happening on a different stream</span></div>
|
|
<div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="comment">// than our default stream</span></div>
|
|
<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>() != 0) {</div>
|
|
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  streamWait({stream}, {0});</div>
|
|
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  }</div>
|
|
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span> }</div>
|
|
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span> </div>
|
|
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span> IVFPQ::setPQCentroids_(<span class="keywordtype">float</span>* data) {</div>
|
|
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keywordtype">size_t</span> pqSize =</div>
|
|
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  numSubQuantizers_ * numSubQuantizerCodes_ * dimPerSubQuantizer_;</div>
|
|
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span> </div>
|
|
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <span class="comment">// Make sure the data is on the host</span></div>
|
|
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="comment">// FIXME: why are we doing this?</span></div>
|
|
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  thrust::host_vector<float> hostMemory;</div>
|
|
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  hostMemory.insert(hostMemory.end(), data, data + pqSize);</div>
|
|
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span> </div>
|
|
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<float, 3, true></a> pqHost(</div>
|
|
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  hostMemory.data(),</div>
|
|
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  {numSubQuantizers_, numSubQuantizerCodes_, dimPerSubQuantizer_});</div>
|
|
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  DeviceTensor<float, 3, true> pqDevice(</div>
|
|
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  pqHost,</div>
|
|
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>());</div>
|
|
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span> </div>
|
|
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  DeviceTensor<float, 3, true> pqDeviceTranspose(</div>
|
|
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  {numSubQuantizers_, dimPerSubQuantizer_, numSubQuantizerCodes_});</div>
|
|
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  runTransposeAny(pqDevice, 1, 2, pqDeviceTranspose,</div>
|
|
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>());</div>
|
|
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span> </div>
|
|
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  pqCentroidsInnermostCode_ = std::move(pqDeviceTranspose);</div>
|
|
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span> </div>
|
|
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="comment">// Also maintain the PQ centroids in the form</span></div>
|
|
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="comment">// (sub q)(code id)(sub dim)</span></div>
|
|
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  DeviceTensor<float, 3, true> pqCentroidsMiddleCode(</div>
|
|
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  {numSubQuantizers_, numSubQuantizerCodes_, dimPerSubQuantizer_});</div>
|
|
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  runTransposeAny(pqCentroidsInnermostCode_, 1, 2, pqCentroidsMiddleCode,</div>
|
|
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>());</div>
|
|
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span> </div>
|
|
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  pqCentroidsMiddleCode_ = std::move(pqCentroidsMiddleCode);</div>
|
|
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span> }</div>
|
|
<div class="line"><a name="l00431"></a><span class="lineno"> 431</span> </div>
|
|
<div class="line"><a name="l00432"></a><span class="lineno"> 432</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00433"></a><span class="lineno"> 433</span> IVFPQ::precomputeCodes_() {</div>
|
|
<div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <span class="comment">// d = || x - y_C ||^2 + || y_R ||^2 + 2 * (y_C|y_R) - 2 * (x|y_R)</span></div>
|
|
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <span class="comment">// --------------- --------------------------- -------</span></div>
|
|
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="comment">// term 1 term 2 term 3</span></div>
|
|
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span> </div>
|
|
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <span class="comment">// Terms 1 and 3 are available only at query time. We compute term 2</span></div>
|
|
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="comment">// here.</span></div>
|
|
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  FAISS_ASSERT(!<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>->getUseFloat16());</div>
|
|
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <span class="keyword">auto</span>& coarseCentroids = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a12058744ffb3fbcbb047872449269c06">getVectorsFloat32Ref</a>();</div>
|
|
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span> </div>
|
|
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="comment">// Compute ||y_R||^2 by treating</span></div>
|
|
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <span class="comment">// (sub q)(code id)(sub dim) as (sub q * code id)(sub dim)</span></div>
|
|
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <span class="keyword">auto</span> pqCentroidsMiddleCodeView =</div>
|
|
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  pqCentroidsMiddleCode_.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a74dbc09519c9c14479b2d18f2e5042e8">view</a><2>(</div>
|
|
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  {numSubQuantizers_ * numSubQuantizerCodes_, dimPerSubQuantizer_});</div>
|
|
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  DeviceTensor<float, 1, true> subQuantizerNorms(</div>
|
|
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  {numSubQuantizers_ * numSubQuantizerCodes_});</div>
|
|
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span> </div>
|
|
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  runL2Norm(pqCentroidsMiddleCodeView, subQuantizerNorms, <span class="keyword">true</span>,</div>
|
|
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>());</div>
|
|
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span> </div>
|
|
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <span class="comment">// Compute 2 * (y_C|y_R) via batch matrix multiplication</span></div>
|
|
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="comment">// batch size (sub q) x {(centroid id)(sub dim) x (code id)(sub dim)'}</span></div>
|
|
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="comment">// => (sub q) x {(centroid id)(code id)}</span></div>
|
|
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <span class="comment">// => (sub q)(centroid id)(code id)</span></div>
|
|
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span> </div>
|
|
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <span class="comment">// View (centroid id)(dim) as</span></div>
|
|
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <span class="comment">// (centroid id)(sub q)(dim)</span></div>
|
|
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="comment">// Transpose (centroid id)(sub q)(sub dim) to</span></div>
|
|
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <span class="comment">// (sub q)(centroid id)(sub dim)</span></div>
|
|
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <span class="keyword">auto</span> centroidView = coarseCentroids.view<3>(</div>
|
|
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  {coarseCentroids.getSize(0), numSubQuantizers_, dimPerSubQuantizer_});</div>
|
|
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  DeviceTensor<float, 3, true> centroidsTransposed(</div>
|
|
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  {numSubQuantizers_, coarseCentroids.getSize(0), dimPerSubQuantizer_});</div>
|
|
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span> </div>
|
|
<div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  runTransposeAny(centroidView, 0, 1, centroidsTransposed,</div>
|
|
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>());</div>
|
|
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span> </div>
|
|
<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  DeviceTensor<float, 3, true> coarsePQProduct(</div>
|
|
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  {numSubQuantizers_, coarseCentroids.getSize(0), numSubQuantizerCodes_});</div>
|
|
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span> </div>
|
|
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  runIteratedMatrixMult(coarsePQProduct, <span class="keyword">false</span>,</div>
|
|
<div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  centroidsTransposed, <span class="keyword">false</span>,</div>
|
|
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  pqCentroidsMiddleCode_, <span class="keyword">true</span>,</div>
|
|
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  2.0f, 0.0f,</div>
|
|
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a00cb7bcbc5f1a00da673f30749149b12">getBlasHandleCurrentDevice</a>(),</div>
|
|
<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>());</div>
|
|
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span> </div>
|
|
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <span class="comment">// Transpose (sub q)(centroid id)(code id) to</span></div>
|
|
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  <span class="comment">// (centroid id)(sub q)(code id)</span></div>
|
|
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  DeviceTensor<float, 3, true> coarsePQProductTransposed(</div>
|
|
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  {coarseCentroids.getSize(0), numSubQuantizers_, numSubQuantizerCodes_});</div>
|
|
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  runTransposeAny(coarsePQProduct, 0, 1, coarsePQProductTransposed,</div>
|
|
<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>());</div>
|
|
<div class="line"><a name="l00489"></a><span class="lineno"> 489</span> </div>
|
|
<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <span class="comment">// View (centroid id)(sub q)(code id) as</span></div>
|
|
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="comment">// (centroid id)(sub q * code id)</span></div>
|
|
<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <span class="keyword">auto</span> coarsePQProductTransposedView = coarsePQProductTransposed.view<2>(</div>
|
|
<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  {coarseCentroids.getSize(0), numSubQuantizers_ * numSubQuantizerCodes_});</div>
|
|
<div class="line"><a name="l00494"></a><span class="lineno"> 494</span> </div>
|
|
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="comment">// Sum || y_R ||^2 + 2 * (y_C|y_R)</span></div>
|
|
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="comment">// i.e., add norms (sub q * code id)</span></div>
|
|
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  <span class="comment">// along columns of inner product (centroid id)(sub q * code id)</span></div>
|
|
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  runSumAlongColumns(subQuantizerNorms, coarsePQProductTransposedView,</div>
|
|
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>());</div>
|
|
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span> </div>
|
|
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span> <span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
|
|
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span> <span class="preprocessor"></span> <span class="keywordflow">if</span> (useFloat16LookupTables_) {</div>
|
|
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  precomputedCodeHalf_ = toHalf(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>,</div>
|
|
<div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>(),</div>
|
|
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  coarsePQProductTransposed);</div>
|
|
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  <span class="keywordflow">return</span>;</div>
|
|
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  }</div>
|
|
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span> <span class="preprocessor"></span></div>
|
|
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <span class="comment">// We added into the view, so `coarsePQProductTransposed` is now our</span></div>
|
|
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <span class="comment">// precomputed term 2.</span></div>
|
|
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  precomputedCode_ = std::move(coarsePQProductTransposed);</div>
|
|
<div class="line"><a name="l00513"></a><span class="lineno"> 513</span> }</div>
|
|
<div class="line"><a name="l00514"></a><span class="lineno"> 514</span> </div>
|
|
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00516"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFPQ.html#ab0c458aab9a3d903f31b0e63ce16e623"> 516</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#ab0c458aab9a3d903f31b0e63ce16e623">IVFPQ::query</a>(<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& queries,</div>
|
|
<div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <span class="keywordtype">int</span> nprobe,</div>
|
|
<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="keywordtype">int</span> k,</div>
|
|
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& outDistances,</div>
|
|
<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<long, 2, true></a>& outIndices) {</div>
|
|
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <span class="comment">// Validate these at a top level</span></div>
|
|
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  FAISS_ASSERT(nprobe <= 1024);</div>
|
|
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  FAISS_ASSERT(k <= 1024);</div>
|
|
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span> </div>
|
|
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  <span class="keyword">auto</span>& mem = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a1dda2dc3db1bd62cde6657c5cdbfb6e1">getMemoryManagerCurrentDevice</a>();</div>
|
|
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>();</div>
|
|
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  nprobe = std::min(nprobe, <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a6988df17792dae30f24cc859728777e6">getSize</a>());</div>
|
|
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span> </div>
|
|
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  FAISS_ASSERT(queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(1) == <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#aba3e3cfa469e5187f2d553fff10e0250">dim_</a>);</div>
|
|
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  FAISS_ASSERT(outDistances.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0) == queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0));</div>
|
|
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  FAISS_ASSERT(outIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0) == queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0));</div>
|
|
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span> </div>
|
|
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="comment">// Reserve space for the closest coarse centroids</span></div>
|
|
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a></div>
|
|
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  coarseDistances(mem, {queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), nprobe}, stream);</div>
|
|
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 2, true></a></div>
|
|
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  coarseIndices(mem, {queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), nprobe}, stream);</div>
|
|
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span> </div>
|
|
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  <span class="comment">// Find the `nprobe` closest coarse centroids; we can use int</span></div>
|
|
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <span class="comment">// indices both internally and externally</span></div>
|
|
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>->query(queries,</div>
|
|
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  nprobe,</div>
|
|
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  coarseDistances,</div>
|
|
<div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  coarseIndices,</div>
|
|
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  <span class="keyword">true</span>);</div>
|
|
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span> </div>
|
|
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  <span class="keywordflow">if</span> (precomputedCodes_) {</div>
|
|
<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  runPQPrecomputedCodes_(queries,</div>
|
|
<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  coarseDistances,</div>
|
|
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  coarseIndices,</div>
|
|
<div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  k,</div>
|
|
<div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  outDistances,</div>
|
|
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  outIndices);</div>
|
|
<div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  runPQNoPrecomputedCodes_(queries,</div>
|
|
<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  coarseDistances,</div>
|
|
<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  coarseIndices,</div>
|
|
<div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  k,</div>
|
|
<div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  outDistances,</div>
|
|
<div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  outIndices);</div>
|
|
<div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  }</div>
|
|
<div class="line"><a name="l00562"></a><span class="lineno"> 562</span> </div>
|
|
<div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  <span class="comment">// If the GPU isn't storing indices (they are on the CPU side), we</span></div>
|
|
<div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  <span class="comment">// need to perform the re-mapping here</span></div>
|
|
<div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <span class="comment">// FIXME: we might ultimately be calling this function with inputs</span></div>
|
|
<div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <span class="comment">// from the CPU, these are unnecessary copies</span></div>
|
|
<div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a> == INDICES_CPU) {</div>
|
|
<div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <a class="code" href="classfaiss_1_1gpu_1_1HostTensor.html">HostTensor<long, 2, true></a> hostOutIndices(outIndices, stream);</div>
|
|
<div class="line"><a name="l00569"></a><span class="lineno"> 569</span> </div>
|
|
<div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  ivfOffsetToUserIndex(hostOutIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">data</a>(),</div>
|
|
<div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#accc4d96c14643e5f471220cb1e92ac70">numLists_</a>,</div>
|
|
<div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  hostOutIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0),</div>
|
|
<div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  hostOutIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(1),</div>
|
|
<div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">listOffsetToUserIndex_</a>);</div>
|
|
<div class="line"><a name="l00575"></a><span class="lineno"> 575</span> </div>
|
|
<div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="comment">// Copy back to GPU, since the input to this function is on the</span></div>
|
|
<div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  <span class="comment">// GPU</span></div>
|
|
<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  outIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6dc00c182a92389b74c89ba7fcab40d3">copyFrom</a>(hostOutIndices, stream);</div>
|
|
<div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  }</div>
|
|
<div class="line"><a name="l00580"></a><span class="lineno"> 580</span> }</div>
|
|
<div class="line"><a name="l00581"></a><span class="lineno"> 581</span> </div>
|
|
<div class="line"><a name="l00582"></a><span class="lineno"> 582</span> std::vector<unsigned char></div>
|
|
<div class="line"><a name="l00583"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFPQ.html#a5b349dd021b11b5f48531825359b0657"> 583</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#a5b349dd021b11b5f48531825359b0657">IVFPQ::getListCodes</a>(<span class="keywordtype">int</span> listId)<span class="keyword"> const </span>{</div>
|
|
<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  FAISS_ASSERT(listId < <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>.size());</div>
|
|
<div class="line"><a name="l00585"></a><span class="lineno"> 585</span> </div>
|
|
<div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">deviceListData_</a>[listId]->copyToHost<<span class="keywordtype">unsigned</span> <span class="keywordtype">char</span>>(</div>
|
|
<div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>());</div>
|
|
<div class="line"><a name="l00588"></a><span class="lineno"> 588</span> }</div>
|
|
<div class="line"><a name="l00589"></a><span class="lineno"> 589</span> </div>
|
|
<div class="line"><a name="l00590"></a><span class="lineno"> 590</span> <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 3, true></a></div>
|
|
<div class="line"><a name="l00591"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1IVFPQ.html#a3e8bff50f894c243c62e832f923e88e7"> 591</a></span> <a class="code" href="classfaiss_1_1gpu_1_1IVFPQ.html#a3e8bff50f894c243c62e832f923e88e7">IVFPQ::getPQCentroids</a>() {</div>
|
|
<div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="keywordflow">return</span> pqCentroidsMiddleCode_;</div>
|
|
<div class="line"><a name="l00593"></a><span class="lineno"> 593</span> }</div>
|
|
<div class="line"><a name="l00594"></a><span class="lineno"> 594</span> </div>
|
|
<div class="line"><a name="l00595"></a><span class="lineno"> 595</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00596"></a><span class="lineno"> 596</span> IVFPQ::runPQPrecomputedCodes_(</div>
|
|
<div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& queries,</div>
|
|
<div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a>& coarseDistances,</div>
|
|
<div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 2, true></a>& coarseIndices,</div>
|
|
<div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keywordtype">int</span> k,</div>
|
|
<div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a>& outDistances,</div>
|
|
<div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<long, 2, true></a>& outIndices) {</div>
|
|
<div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <span class="keyword">auto</span>& mem = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a1dda2dc3db1bd62cde6657c5cdbfb6e1">getMemoryManagerCurrentDevice</a>();</div>
|
|
<div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">getDefaultStreamCurrentDevice</a>();</div>
|
|
<div class="line"><a name="l00605"></a><span class="lineno"> 605</span> </div>
|
|
<div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="comment">// Compute precomputed code term 3, - 2 * (x|y_R)</span></div>
|
|
<div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="comment">// This is done via batch MM</span></div>
|
|
<div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <span class="comment">// {sub q} x {(query id)(sub dim) * (code id)(sub dim)'} =></span></div>
|
|
<div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <span class="comment">// {sub q} x {(query id)(code id)}</span></div>
|
|
<div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 3, true></a> term3Transposed(</div>
|
|
<div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  mem,</div>
|
|
<div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  {queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), numSubQuantizers_, numSubQuantizerCodes_},</div>
|
|
<div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  stream);</div>
|
|
<div class="line"><a name="l00614"></a><span class="lineno"> 614</span> </div>
|
|
<div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  <span class="comment">// These allocations within are only temporary, so release them when</span></div>
|
|
<div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <span class="comment">// we're done to maximize free space</span></div>
|
|
<div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  {</div>
|
|
<div class="line"><a name="l00618"></a><span class="lineno"> 618</span>  <span class="keyword">auto</span> querySubQuantizerView = queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a74dbc09519c9c14479b2d18f2e5042e8">view</a><3>(</div>
|
|
<div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  {queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), numSubQuantizers_, dimPerSubQuantizer_});</div>
|
|
<div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  DeviceTensor<float, 3, true> queriesTransposed(</div>
|
|
<div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  mem,</div>
|
|
<div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  {numSubQuantizers_, queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), dimPerSubQuantizer_},</div>
|
|
<div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  stream);</div>
|
|
<div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  runTransposeAny(querySubQuantizerView, 0, 1, queriesTransposed, stream);</div>
|
|
<div class="line"><a name="l00625"></a><span class="lineno"> 625</span> </div>
|
|
<div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  DeviceTensor<float, 3, true> term3(</div>
|
|
<div class="line"><a name="l00627"></a><span class="lineno"> 627</span>  mem,</div>
|
|
<div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  {numSubQuantizers_, queries.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">getSize</a>(0), numSubQuantizerCodes_},</div>
|
|
<div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  stream);</div>
|
|
<div class="line"><a name="l00630"></a><span class="lineno"> 630</span> </div>
|
|
<div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  runIteratedMatrixMult(term3, <span class="keyword">false</span>,</div>
|
|
<div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  queriesTransposed, <span class="keyword">false</span>,</div>
|
|
<div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  pqCentroidsMiddleCode_, <span class="keyword">true</span>,</div>
|
|
<div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  -2.0f, 0.0f,</div>
|
|
<div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a00cb7bcbc5f1a00da673f30749149b12">getBlasHandleCurrentDevice</a>(),</div>
|
|
<div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  stream);</div>
|
|
<div class="line"><a name="l00637"></a><span class="lineno"> 637</span> </div>
|
|
<div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  runTransposeAny(term3, 0, 1, term3Transposed, stream);</div>
|
|
<div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  }</div>
|
|
<div class="line"><a name="l00640"></a><span class="lineno"> 640</span> </div>
|
|
<div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  NoTypeTensor<3, true> term2;</div>
|
|
<div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  NoTypeTensor<3, true> term3;</div>
|
|
<div class="line"><a name="l00643"></a><span class="lineno"> 643</span> <span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
|
|
<div class="line"><a name="l00644"></a><span class="lineno"> 644</span> <span class="preprocessor"></span> DeviceTensor<half, 3, true> term3Half;</div>
|
|
<div class="line"><a name="l00645"></a><span class="lineno"> 645</span> </div>
|
|
<div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  <span class="keywordflow">if</span> (useFloat16LookupTables_) {</div>
|
|
<div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  term3Half = toHalf(<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>, stream, term3Transposed);</div>
|
|
<div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  term2 = NoTypeTensor<3, true>(precomputedCodeHalf_);</div>
|
|
<div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  term3 = NoTypeTensor<3, true>(term3Half);</div>
|
|
<div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  }</div>
|
|
<div class="line"><a name="l00651"></a><span class="lineno"> 651</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00652"></a><span class="lineno"> 652</span> <span class="preprocessor"></span></div>
|
|
<div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  <span class="keywordflow">if</span> (!useFloat16LookupTables_) {</div>
|
|
<div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  term2 = NoTypeTensor<3, true>(precomputedCode_);</div>
|
|
<div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  term3 = NoTypeTensor<3, true>(term3Transposed);</div>
|
|
<div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  }</div>
|
|
<div class="line"><a name="l00657"></a><span class="lineno"> 657</span> </div>
|
|
<div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  runPQScanMultiPassPrecomputed(queries,</div>
|
|
<div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  coarseDistances, <span class="comment">// term 1</span></div>
|
|
<div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  term2, <span class="comment">// term 2</span></div>
|
|
<div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  term3, <span class="comment">// term 3</span></div>
|
|
<div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  coarseIndices,</div>
|
|
<div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  useFloat16LookupTables_,</div>
|
|
<div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>,</div>
|
|
<div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  numSubQuantizers_,</div>
|
|
<div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  numSubQuantizerCodes_,</div>
|
|
<div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a96240a08b42bd1913e2286d7d514fc56">deviceListDataPointers_</a>,</div>
|
|
<div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a9aedcf0e6a20b908980ae96d73461f4c">deviceListIndexPointers_</a>,</div>
|
|
<div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a>,</div>
|
|
<div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a3a1c2031a4763f7d55bc8a400c63af66">deviceListLengths_</a>,</div>
|
|
<div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a>,</div>
|
|
<div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  k,</div>
|
|
<div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  outDistances,</div>
|
|
<div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  outIndices,</div>
|
|
<div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>);</div>
|
|
<div class="line"><a name="l00676"></a><span class="lineno"> 676</span> }</div>
|
|
<div class="line"><a name="l00677"></a><span class="lineno"> 677</span> </div>
|
|
<div class="line"><a name="l00678"></a><span class="lineno"> 678</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00679"></a><span class="lineno"> 679</span> IVFPQ::runPQNoPrecomputedCodes_(</div>
|
|
<div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  Tensor<float, 2, true>& queries,</div>
|
|
<div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  DeviceTensor<float, 2, true>& coarseDistances,</div>
|
|
<div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  DeviceTensor<int, 2, true>& coarseIndices,</div>
|
|
<div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  <span class="keywordtype">int</span> k,</div>
|
|
<div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  Tensor<float, 2, true>& outDistances,</div>
|
|
<div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  Tensor<long, 2, true>& outIndices) {</div>
|
|
<div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  FAISS_ASSERT(!<a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>->getUseFloat16());</div>
|
|
<div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  <span class="keyword">auto</span>& coarseCentroids = <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">quantizer_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a12058744ffb3fbcbb047872449269c06">getVectorsFloat32Ref</a>();</div>
|
|
<div class="line"><a name="l00688"></a><span class="lineno"> 688</span> </div>
|
|
<div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  runPQScanMultiPassNoPrecomputed(queries,</div>
|
|
<div class="line"><a name="l00690"></a><span class="lineno"> 690</span>  coarseCentroids,</div>
|
|
<div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  pqCentroidsInnermostCode_,</div>
|
|
<div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  coarseIndices,</div>
|
|
<div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  useFloat16LookupTables_,</div>
|
|
<div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">bytesPerVector_</a>,</div>
|
|
<div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  numSubQuantizers_,</div>
|
|
<div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  numSubQuantizerCodes_,</div>
|
|
<div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a96240a08b42bd1913e2286d7d514fc56">deviceListDataPointers_</a>,</div>
|
|
<div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a9aedcf0e6a20b908980ae96d73461f4c">deviceListIndexPointers_</a>,</div>
|
|
<div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">indicesOptions_</a>,</div>
|
|
<div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a3a1c2031a4763f7d55bc8a400c63af66">deviceListLengths_</a>,</div>
|
|
<div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">maxListLength_</a>,</div>
|
|
<div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  k,</div>
|
|
<div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  outDistances,</div>
|
|
<div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  outIndices,</div>
|
|
<div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  <a class="code" href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">resources_</a>);</div>
|
|
<div class="line"><a name="l00706"></a><span class="lineno"> 706</span> }</div>
|
|
<div class="line"><a name="l00707"></a><span class="lineno"> 707</span> </div>
|
|
<div class="line"><a name="l00708"></a><span class="lineno"> 708</span> } } <span class="comment">// namespace</span></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_accc4d96c14643e5f471220cb1e92ac70"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#accc4d96c14643e5f471220cb1e92ac70">faiss::gpu::IVFBase::numLists_</a></div><div class="ttdeci">const int numLists_</div><div class="ttdoc">Number of inverted lists we maintain. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00091">IVFBase.cuh:91</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_ae25ea0901fb628844868413f51c85bda"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#ae25ea0901fb628844868413f51c85bda">faiss::gpu::IVFBase::maxListLength_</a></div><div class="ttdeci">int maxListLength_</div><div class="ttdoc">Maximum list length seen. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00115">IVFBase.cuh:115</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1GpuResources_html_aa0354aa570c24e17a9f8a6a45b153ed2"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuResources.html#aa0354aa570c24e17a9f8a6a45b153ed2">faiss::gpu::GpuResources::getDefaultStreamCurrentDevice</a></div><div class="ttdeci">cudaStream_t getDefaultStreamCurrentDevice()</div><div class="ttdoc">Calls getDefaultStream with the current device. </div><div class="ttdef"><b>Definition:</b> <a href="GpuResources_8cpp_source.html#l00025">GpuResources.cpp:25</a></div></div>
|
|
<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#l00346">IVFPQ.cu:346</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1FlatIndex_html_a6988df17792dae30f24cc859728777e6"><div class="ttname"><a href="classfaiss_1_1gpu_1_1FlatIndex.html#a6988df17792dae30f24cc859728777e6">faiss::gpu::FlatIndex::getSize</a></div><div class="ttdeci">int getSize() const </div><div class="ttdoc">Returns the number of vectors we contain. </div><div class="ttdef"><b>Definition:</b> <a href="FlatIndex_8cu_source.html#l00047">FlatIndex.cu:47</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a53f3c382a79b7f89630a85dfbc3a1fed"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a53f3c382a79b7f89630a85dfbc3a1fed">faiss::gpu::IVFBase::listOffsetToUserIndex_</a></div><div class="ttdeci">std::vector< std::vector< long > > listOffsetToUserIndex_</div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00127">IVFBase.cuh:127</a></div></div>
|
|
<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#l00023">FlatIndex.cuh:23</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a74dbc09519c9c14479b2d18f2e5042e8"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a74dbc09519c9c14479b2d18f2e5042e8">faiss::gpu::Tensor::view</a></div><div class="ttdeci">__host__ __device__ Tensor< T, SubDim, InnerContig, IndexT, PtrTraits > view(DataPtrType at)</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00598">Tensor-inl.cuh:598</a></div></div>
|
|
<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#l00027">IVFBase.cuh:27</a></div></div>
|
|
<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#l00023">GpuResources.h:23</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a3a1c2031a4763f7d55bc8a400c63af66"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a3a1c2031a4763f7d55bc8a400c63af66">faiss::gpu::IVFBase::deviceListLengths_</a></div><div class="ttdeci">thrust::device_vector< int > deviceListLengths_</div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00112">IVFBase.cuh:112</a></div></div>
|
|
<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#l00072">IVFPQ.cu:72</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a9aedcf0e6a20b908980ae96d73461f4c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a9aedcf0e6a20b908980ae96d73461f4c">faiss::gpu::IVFBase::deviceListIndexPointers_</a></div><div class="ttdeci">thrust::device_vector< void * > deviceListIndexPointers_</div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00108">IVFBase.cuh:108</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1GpuResources_html_a00cb7bcbc5f1a00da673f30749149b12"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuResources.html#a00cb7bcbc5f1a00da673f30749149b12">faiss::gpu::GpuResources::getBlasHandleCurrentDevice</a></div><div class="ttdeci">cublasHandle_t getBlasHandleCurrentDevice()</div><div class="ttdoc">Calls getBlasHandle with the current device. </div><div class="ttdef"><b>Definition:</b> <a href="GpuResources_8cpp_source.html#l00020">GpuResources.cpp:20</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1GpuResources_html_a1dda2dc3db1bd62cde6657c5cdbfb6e1"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuResources.html#a1dda2dc3db1bd62cde6657c5cdbfb6e1">faiss::gpu::GpuResources::getMemoryManagerCurrentDevice</a></div><div class="ttdeci">DeviceMemory & getMemoryManagerCurrentDevice()</div><div class="ttdoc">Calls getMemoryManager for the current device. </div><div class="ttdef"><b>Definition:</b> <a href="GpuResources_8cpp_source.html#l00035">GpuResources.cpp:35</a></div></div>
|
|
<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#l00120">IVFPQ.cu:120</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a6dc00c182a92389b74c89ba7fcab40d3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a6dc00c182a92389b74c89ba7fcab40d3">faiss::gpu::Tensor::copyFrom</a></div><div class="ttdeci">__host__ void copyFrom(Tensor< T, Dim, InnerContig, IndexT, PtrTraits > &t, cudaStream_t stream)</div><div class="ttdoc">Copies a tensor into ourselves; sizes must match. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00101">Tensor-inl.cuh:101</a></div></div>
|
|
<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>
|
|
<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>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a878114abdba07c9cf7735f9c0ed594c3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a878114abdba07c9cf7735f9c0ed594c3">faiss::gpu::IVFBase::quantizer_</a></div><div class="ttdeci">FlatIndex * quantizer_</div><div class="ttdoc">Quantizer object. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00085">IVFBase.cuh:85</a></div></div>
|
|
<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#l00102">IVFPQ.cu:102</a></div></div>
|
|
<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>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a6699c311648457f257afa340c61f417c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a6699c311648457f257afa340c61f417c">faiss::gpu::Tensor::getSize</a></div><div class="ttdeci">__host__ __device__ IndexT getSize(int i) const </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00226">Tensor.cuh:226</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a96240a08b42bd1913e2286d7d514fc56"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a96240a08b42bd1913e2286d7d514fc56">faiss::gpu::IVFBase::deviceListDataPointers_</a></div><div class="ttdeci">thrust::device_vector< void * > deviceListDataPointers_</div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00104">IVFBase.cuh:104</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_a50411ce4d0fa32ef715e3321b6e33212"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#a50411ce4d0fa32ef715e3321b6e33212">faiss::gpu::Tensor::data</a></div><div class="ttdeci">__host__ __device__ DataPtrType data()</div><div class="ttdoc">Returns a raw pointer to the start of our data. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00178">Tensor.cuh:178</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a05e6400358ec1f529a67209d3f24cc63"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a05e6400358ec1f529a67209d3f24cc63">faiss::gpu::IVFBase::resources_</a></div><div class="ttdeci">GpuResources * resources_</div><div class="ttdoc">Collection of GPU resources that we use. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00082">IVFBase.cuh:82</a></div></div>
|
|
<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#l00030">Tensor.cuh:30</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a319568b832518392fed33ea4f8bfc613"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a319568b832518392fed33ea4f8bfc613">faiss::gpu::IVFBase::bytesPerVector_</a></div><div class="ttdeci">const int bytesPerVector_</div><div class="ttdoc">Number of bytes per vector in the list. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00094">IVFBase.cuh:94</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_acc695610c9513952b8d234dc0db78e5c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#acc695610c9513952b8d234dc0db78e5c">faiss::gpu::IVFBase::updateDeviceListInfo_</a></div><div class="ttdeci">void updateDeviceListInfo_(cudaStream_t stream)</div><div class="ttdoc">Update all device-side list pointer and size information. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cu_source.html#l00138">IVFBase.cu:138</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1FlatIndex_html_a12058744ffb3fbcbb047872449269c06"><div class="ttname"><a href="classfaiss_1_1gpu_1_1FlatIndex.html#a12058744ffb3fbcbb047872449269c06">faiss::gpu::FlatIndex::getVectorsFloat32Ref</a></div><div class="ttdeci">Tensor< float, 2, true > & getVectorsFloat32Ref()</div><div class="ttdoc">Returns a reference to our vectors currently in use. </div><div class="ttdef"><b>Definition:</b> <a href="FlatIndex_8cu_source.html#l00079">FlatIndex.cu:79</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_afb6d10e23d6448c10f472b9234e0bcab"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#afb6d10e23d6448c10f472b9234e0bcab">faiss::gpu::IVFBase::indicesOptions_</a></div><div class="ttdeci">const IndicesOptions indicesOptions_</div><div class="ttdoc">How are user indices stored on the GPU? </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00097">IVFBase.cuh:97</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1HostTensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1HostTensor.html">faiss::gpu::HostTensor</a></div><div class="ttdef"><b>Definition:</b> <a href="HostTensor_8cuh_source.html#l00022">HostTensor.cuh:22</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a2facc7285107de1f24d3471cbcf15f26"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a2facc7285107de1f24d3471cbcf15f26">faiss::gpu::IVFBase::deviceListData_</a></div><div class="ttdeci">std::vector< std::unique_ptr< DeviceVector< unsigned char > > > deviceListData_</div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00121">IVFBase.cuh:121</a></div></div>
|
|
<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, 3, true ></a></div></div>
|
|
<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#l00035">IVFPQ.cu:35</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_aba3e3cfa469e5187f2d553fff10e0250"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#aba3e3cfa469e5187f2d553fff10e0250">faiss::gpu::IVFBase::dim_</a></div><div class="ttdeci">const int dim_</div><div class="ttdoc">Expected dimensionality of the vectors. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cuh_source.html#l00088">IVFBase.cuh:88</a></div></div>
|
|
<div class="ttc" id="classfaiss_1_1gpu_1_1IVFBase_html_a5027720549de98f4e609d6339099df35"><div class="ttname"><a href="classfaiss_1_1gpu_1_1IVFBase.html#a5027720549de98f4e609d6339099df35">faiss::gpu::IVFBase::addIndicesFromCpu_</a></div><div class="ttdeci">void addIndicesFromCpu_(int listId, const long *indices, size_t numVecs)</div><div class="ttdoc">Shared function to copy indices from CPU to GPU. </div><div class="ttdef"><b>Definition:</b> <a href="IVFBase_8cu_source.html#l00245">IVFBase.cu:245</a></div></div>
|
|
<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#l00097">IVFPQ.cu:97</a></div></div>
|
|
</div><!-- fragment --></div><!-- contents -->
|
|
<!-- start footer part -->
|
|
<hr class="footer"/><address class="footer"><small>
|
|
Generated by  <a href="http://www.doxygen.org/index.html">
|
|
<img class="footer" src="doxygen.png" alt="doxygen"/>
|
|
</a> 1.8.5
|
|
</small></address>
|
|
</body>
|
|
</html>
|