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0df3f646fc
various bugfixes from github issues kmean with some frozen centroids GPU better tiling for large flat datasets default AVX for vector ops
303 lines
34 KiB
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303 lines
34 KiB
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<li class="navelem"><a class="el" href="dir_59425e443f801f1f2fd8bbe4959a3ccf.html">tests</a></li> </ul>
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<div class="title">demo_imi_pq.cpp</div> </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/**</span></div>
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<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 2015-present, Facebook, Inc.</span></div>
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<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> * All rights reserved.</span></div>
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<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> *</span></div>
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<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>
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<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>
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<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> */</span></div>
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<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> </div>
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<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment">// Copyright 2004-present Facebook. All Rights Reserved</span></div>
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<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> </div>
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<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> </div>
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<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <cmath></span></div>
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<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include <cstdio></span></div>
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<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <cstdlib></span></div>
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<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div>
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<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <sys/time.h></span></div>
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<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div>
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<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> </div>
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<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="preprocessor">#include <faiss/IndexPQ.h></span></div>
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<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <faiss/IndexIVFPQ.h></span></div>
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<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include <faiss/IndexFlat.h></span></div>
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<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="preprocessor">#include <faiss/index_io.h></span></div>
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<div class="line"><a name="l00023"></a><span class="lineno"> 23</span> </div>
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<div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="keywordtype">double</span> elapsed ()</div>
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<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> {</div>
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<div class="line"><a name="l00026"></a><span class="lineno"> 26</span>  <span class="keyword">struct </span>timeval tv;</div>
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<div class="line"><a name="l00027"></a><span class="lineno"> 27</span>  gettimeofday (&tv, <span class="keyword">nullptr</span>);</div>
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<div class="line"><a name="l00028"></a><span class="lineno"> 28</span>  <span class="keywordflow">return</span> tv.tv_sec + tv.tv_usec * 1e-6;</div>
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<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> }</div>
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<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> </div>
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<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> </div>
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<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="keywordtype">int</span> main ()</div>
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<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> {</div>
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<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keywordtype">double</span> t0 = elapsed();</div>
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<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> </div>
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<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <span class="comment">// dimension of the vectors to index</span></div>
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<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  <span class="keywordtype">int</span> d = 64;</div>
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<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div>
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<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  <span class="comment">// size of the database we plan to index</span></div>
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<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  <span class="keywordtype">size_t</span> nb = 1000 * 1000;</div>
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<div class="line"><a name="l00041"></a><span class="lineno"> 41</span>  <span class="keywordtype">size_t</span> add_bs = 10000; <span class="comment">// # size of the blocks to add</span></div>
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<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> </div>
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<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  <span class="comment">// make a set of nt training vectors in the unit cube</span></div>
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<div class="line"><a name="l00044"></a><span class="lineno"> 44</span>  <span class="comment">// (could be the database)</span></div>
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<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <span class="keywordtype">size_t</span> nt = 100 * 1000;</div>
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<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> </div>
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<div class="line"><a name="l00047"></a><span class="lineno"> 47</span>  <span class="comment">//---------------------------------------------------------------</span></div>
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<div class="line"><a name="l00048"></a><span class="lineno"> 48</span>  <span class="comment">// Define the core quantizer</span></div>
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<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="comment">// We choose a multiple inverted index for faster training with less data</span></div>
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<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <span class="comment">// and because it usually offers best accuracy/speed trade-offs</span></div>
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<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <span class="comment">//</span></div>
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<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <span class="comment">// We here assume that its lifespan of this coarse quantizer will cover the</span></div>
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<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  <span class="comment">// lifespan of the inverted-file quantizer IndexIVFFlat below</span></div>
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<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  <span class="comment">// With dynamic allocation, one may give the responsability to free the</span></div>
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<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  <span class="comment">// quantizer to the inverted-file index (with attribute do_delete_quantizer)</span></div>
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<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  <span class="comment">//</span></div>
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<div class="line"><a name="l00057"></a><span class="lineno"> 57</span>  <span class="comment">// Note: a regular clustering algorithm would be defined as:</span></div>
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<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="comment">// faiss::IndexFlatL2 coarse_quantizer (d);</span></div>
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<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="comment">//</span></div>
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<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  <span class="comment">// Use nhash=2 subquantizers used to define the product coarse quantizer</span></div>
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<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="comment">// Number of bits: we will have 2^nbits_coarse centroids per subquantizer</span></div>
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<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <span class="comment">// meaning (2^12)^nhash distinct inverted lists</span></div>
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<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="comment">//</span></div>
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<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="comment">// The parameter bytes_per_code is determined by the memory</span></div>
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<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="comment">// constraint, the dataset will use nb * (bytes_per_code + 8)</span></div>
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<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <span class="comment">// bytes.</span></div>
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<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <span class="comment">//</span></div>
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<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <span class="comment">// The parameter nbits_subq is determined by the size of the dataset to index.</span></div>
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<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="comment">//</span></div>
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<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  <span class="keywordtype">size_t</span> nhash = 2;</div>
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<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  <span class="keywordtype">size_t</span> nbits_subq = 9;</div>
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<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="keywordtype">size_t</span> ncentroids = 1 << (nhash * nbits_subq); <span class="comment">// total # of centroids</span></div>
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<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordtype">int</span> bytes_per_code = 16;</div>
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<div class="line"><a name="l00074"></a><span class="lineno"> 74</span> </div>
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<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  <a class="code" href="structfaiss_1_1MultiIndexQuantizer.html">faiss::MultiIndexQuantizer</a> coarse_quantizer (d, nhash, nbits_subq);</div>
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<div class="line"><a name="l00076"></a><span class="lineno"> 76</span> </div>
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<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  printf (<span class="stringliteral">"IMI (%ld,%ld): %ld virtual centroids (target: %ld base vectors)"</span>,</div>
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<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  nhash, nbits_subq, ncentroids, nb);</div>
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<div class="line"><a name="l00079"></a><span class="lineno"> 79</span> </div>
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<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="comment">// the coarse quantizer should not be dealloced before the index</span></div>
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<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  <span class="comment">// 4 = nb of bytes per code (d must be a multiple of this)</span></div>
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<div class="line"><a name="l00082"></a><span class="lineno"> 82</span>  <span class="comment">// 8 = nb of bits per sub-code (almost always 8)</span></div>
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<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <a class="code" href="namespacefaiss.html#afd12191c638da74760ff397cf319752c">faiss::MetricType</a> metric = faiss::METRIC_L2; <span class="comment">// can be METRIC_INNER_PRODUCT</span></div>
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<div class="line"><a name="l00084"></a><span class="lineno"> 84</span>  <a class="code" href="structfaiss_1_1IndexIVFPQ.html">faiss::IndexIVFPQ</a> index (&coarse_quantizer, d, ncentroids, bytes_per_code, 8);</div>
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<div class="line"><a name="l00085"></a><span class="lineno"> 85</span>  index.quantizer_trains_alone = <span class="keyword">true</span>;</div>
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<div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div>
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<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="comment">// define the number of probes. 2048 is for high-dim, overkill in practice</span></div>
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<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <span class="comment">// Use 4-1024 depending on the trade-off speed accuracy that you want</span></div>
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<div class="line"><a name="l00089"></a><span class="lineno"> 89</span>  index.nprobe = 2048;</div>
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<div class="line"><a name="l00090"></a><span class="lineno"> 90</span> </div>
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<div class="line"><a name="l00091"></a><span class="lineno"> 91</span> </div>
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<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  { <span class="comment">// training.</span></div>
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<div class="line"><a name="l00093"></a><span class="lineno"> 93</span> </div>
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<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  <span class="comment">// The distribution of the training vectors should be the same</span></div>
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<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="comment">// as the database vectors. It could be a sub-sample of the</span></div>
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<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="comment">// database vectors, if sampling is not biased. Here we just</span></div>
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<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="comment">// randomly generate the vectors.</span></div>
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<div class="line"><a name="l00098"></a><span class="lineno"> 98</span> </div>
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<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  printf (<span class="stringliteral">"[%.3f s] Generating %ld vectors in %dD for training\n"</span>,</div>
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<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  elapsed() - t0, nt, d);</div>
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<div class="line"><a name="l00101"></a><span class="lineno"> 101</span> </div>
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<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  std::vector <float> trainvecs (nt * d);</div>
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<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < nt; i++) {</div>
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<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < d; j++) {</div>
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<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  trainvecs[i * d + j] = drand48();</div>
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<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  }</div>
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<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  }</div>
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<div class="line"><a name="l00108"></a><span class="lineno"> 108</span> </div>
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<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  printf (<span class="stringliteral">"[%.3f s] Training the index\n"</span>, elapsed() - t0);</div>
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<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  index.verbose = <span class="keyword">true</span>;</div>
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<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  index.train (nt, trainvecs.data());</div>
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<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  }</div>
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<div class="line"><a name="l00113"></a><span class="lineno"> 113</span> </div>
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<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="comment">// the index can be re-loaded later with</span></div>
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<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <span class="comment">// faiss::Index * idx = faiss::read_index("/tmp/trained_index.faissindex");</span></div>
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<div class="line"><a name="l00116"></a><span class="lineno"> 116</span>  faiss::write_index(&index, <span class="stringliteral">"/tmp/trained_index.faissindex"</span>);</div>
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<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> </div>
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<div class="line"><a name="l00118"></a><span class="lineno"> 118</span>  <span class="keywordtype">size_t</span> nq;</div>
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<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  std::vector<float> queries;</div>
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<div class="line"><a name="l00120"></a><span class="lineno"> 120</span> </div>
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<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  { <span class="comment">// populating the database</span></div>
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<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  printf (<span class="stringliteral">"[%.3f s] Building a dataset of %ld vectors to index\n"</span>,</div>
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<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  elapsed() - t0, nb);</div>
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<div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </div>
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<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  std::vector <float> database (nb * d);</div>
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<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  std::vector <long> ids (nb);</div>
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<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < nb; i++) {</div>
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<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < d; j++) {</div>
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<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  database[i * d + j] = drand48();</div>
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<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  }</div>
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<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  ids[i] = 8760000000L + i;</div>
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<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  }</div>
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<div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div>
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<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  printf (<span class="stringliteral">"[%.3f s] Adding the vectors to the index\n"</span>, elapsed() - t0);</div>
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<div class="line"><a name="l00135"></a><span class="lineno"> 135</span> </div>
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<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> begin = 0; begin < nb; begin += add_bs) {</div>
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<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keywordtype">size_t</span> end = std::min (begin + add_bs, nb);</div>
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<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  index.add_with_ids (end - begin,</div>
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<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  database.data() + d * begin,</div>
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<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  ids.data() + begin);</div>
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<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  }</div>
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<div class="line"><a name="l00142"></a><span class="lineno"> 142</span> </div>
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<div class="line"><a name="l00143"></a><span class="lineno"> 143</span>  <span class="comment">// remember a few elements from the database as queries</span></div>
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<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordtype">int</span> i0 = 1234;</div>
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|
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="keywordtype">int</span> i1 = 1244;</div>
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|
<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>  nq = i1 - i0;</div>
|
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<div class="line"><a name="l00148"></a><span class="lineno"> 148</span>  queries.resize (nq * d);</div>
|
|
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = i0; i < i1; i++) {</div>
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<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j < d; j++) {</div>
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|
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  queries [(i - i0) * d + j] = database [i * d + j];</div>
|
|
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  }</div>
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<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  }</div>
|
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<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  }</div>
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<div class="line"><a name="l00155"></a><span class="lineno"> 155</span> </div>
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<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  <span class="comment">// A few notes on the internal format of the index:</span></div>
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|
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="comment">//</span></div>
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|
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="comment">// - the positing lists for PQ codes are index.codes, which is a</span></div>
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|
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  <span class="comment">// std::vector < std::vector<uint8_t> ></span></div>
|
|
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="comment">// if n is the length of posting list #i, codes[i] has length bytes_per_code * n</span></div>
|
|
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  <span class="comment">// - the corresponding ids are stored in index.ids</span></div>
|
|
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00164"></a><span class="lineno"> 164</span>  <span class="comment">// - given a vector float *x, finding which k centroids are</span></div>
|
|
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="comment">// closest to it (ie to find the nearest neighbors) can be done with</span></div>
|
|
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <span class="comment">// long *centroid_ids = new long[k];</span></div>
|
|
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="comment">// float *distances = new float[k];</span></div>
|
|
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="comment">// index.quantizer->search (1, x, k, dis, centroids_ids);</span></div>
|
|
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="comment">//</span></div>
|
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<div class="line"><a name="l00171"></a><span class="lineno"> 171</span> </div>
|
|
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  faiss::write_index(&index, <span class="stringliteral">"/tmp/populated_index.faissindex"</span>);</div>
|
|
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span> </div>
|
|
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  { <span class="comment">// searching the database</span></div>
|
|
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <span class="keywordtype">int</span> k = 5;</div>
|
|
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  printf (<span class="stringliteral">"[%.3f s] Searching the %d nearest neighbors "</span></div>
|
|
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="stringliteral">"of %ld vectors in the index\n"</span>,</div>
|
|
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  elapsed() - t0, k, nq);</div>
|
|
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div>
|
|
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  std::vector<faiss::Index::idx_t> nns (k * nq);</div>
|
|
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  std::vector<float> dis (k * nq);</div>
|
|
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span> </div>
|
|
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  index.search (nq, queries.data(), k, dis.data(), nns.data());</div>
|
|
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div>
|
|
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  printf (<span class="stringliteral">"[%.3f s] Query results (vector ids, then distances):\n"</span>,</div>
|
|
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  elapsed() - t0);</div>
|
|
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span> </div>
|
|
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < nq; i++) {</div>
|
|
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  printf (<span class="stringliteral">"query %2d: "</span>, i);</div>
|
|
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j < k; j++) {</div>
|
|
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  printf (<span class="stringliteral">"%7ld "</span>, nns[j + i * k]);</div>
|
|
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  }</div>
|
|
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  printf (<span class="stringliteral">"\n dis: "</span>);</div>
|
|
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j < k; j++) {</div>
|
|
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  printf (<span class="stringliteral">"%7g "</span>, dis[j + i * k]);</div>
|
|
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  }</div>
|
|
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  printf (<span class="stringliteral">"\n"</span>);</div>
|
|
<div class="line"><a name="l00198"></a><span class="lineno"> 198</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>  <span class="keywordflow">return</span> 0;</div>
|
|
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span> }</div>
|
|
<div class="ttc" id="structfaiss_1_1IndexIVFPQ_html"><div class="ttname"><a href="structfaiss_1_1IndexIVFPQ.html">faiss::IndexIVFPQ</a></div><div class="ttdef"><b>Definition:</b> <a href="IndexIVFPQ_8h_source.html#l00029">IndexIVFPQ.h:29</a></div></div>
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|
<div class="ttc" id="structfaiss_1_1MultiIndexQuantizer_html"><div class="ttname"><a href="structfaiss_1_1MultiIndexQuantizer.html">faiss::MultiIndexQuantizer</a></div><div class="ttdef"><b>Definition:</b> <a href="IndexPQ_8h_source.html#l00135">IndexPQ.h:135</a></div></div>
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<div class="ttc" id="namespacefaiss_html_afd12191c638da74760ff397cf319752c"><div class="ttname"><a href="namespacefaiss.html#afd12191c638da74760ff397cf319752c">faiss::MetricType</a></div><div class="ttdeci">MetricType</div><div class="ttdoc">Some algorithms support both an inner product version and a L2 search version. </div><div class="ttdef"><b>Definition:</b> <a href="Index_8h_source.html#l00043">Index.h:43</a></div></div>
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