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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
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756 lines
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<li class="navelem"><a class="el" href="dir_6b3ae6988449b0834e9596fad5d75199.html">gpu</a></li> </ul>
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<div class="title">GpuIndexFlat.cu</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> <span class="preprocessor">#include "GpuIndexFlat.h"</span></div>
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<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include "../IndexFlat.h"</span></div>
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<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="preprocessor">#include "GpuResources.h"</span></div>
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<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include "impl/FlatIndex.cuh"</span></div>
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<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="preprocessor">#include "utils/CopyUtils.cuh"</span></div>
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<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include "utils/DeviceUtils.h"</span></div>
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<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="preprocessor">#include "utils/Float16.cuh"</span></div>
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<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include "utils/StaticUtils.h"</span></div>
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<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> </div>
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<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="preprocessor">#include <thrust/execution_policy.h></span></div>
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<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="preprocessor">#include <thrust/transform.h></span></div>
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<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="preprocessor">#include <limits></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="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
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<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="comment"></span></div>
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<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="comment">/// Default CPU search size for which we use paged copies</span></div>
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<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="comment"></span>constexpr <span class="keywordtype">size_t</span> kMinPageSize = (size_t) 256 * 1024 * 1024;</div>
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<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment"></span></div>
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<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment">/// Size above which we page copies from the CPU to GPU (non-paged</span></div>
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<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="comment">/// memory usage)</span></div>
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<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"></span>constexpr <span class="keywordtype">size_t</span> kNonPinnedPageSize = (size_t) 256 * 1024 * 1024;</div>
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<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> </div>
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<div class="line"><a name="l00033"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#af8a1626e4c54a451d0b9f82df3a6687e"> 33</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#af8a1626e4c54a451d0b9f82df3a6687e">GpuIndexFlat::GpuIndexFlat</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html">GpuResources</a>* resources,</div>
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<div class="line"><a name="l00034"></a><span class="lineno"> 34</span>  <span class="keyword">const</span> <a class="code" href="structfaiss_1_1IndexFlat.html">faiss::IndexFlat</a>* index,</div>
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<div class="line"><a name="l00035"></a><span class="lineno"> 35</span>  <a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html">GpuIndexFlatConfig</a> config) :</div>
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<div class="line"><a name="l00036"></a><span class="lineno"> 36</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html">GpuIndex</a>(resources, index->d, index->metric_type, config),</div>
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<div class="line"><a name="l00037"></a><span class="lineno"> 37</span>  minPagedSize_(kMinPageSize),</div>
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<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  config_(config),</div>
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<div class="line"><a name="l00039"></a><span class="lineno"> 39</span>  data_(nullptr) {</div>
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<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  verifySettings_();</div>
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<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> </div>
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<div class="line"><a name="l00042"></a><span class="lineno"> 42</span>  <span class="comment">// Flat index doesn't need training</span></div>
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<div class="line"><a name="l00043"></a><span class="lineno"> 43</span>  this-><a class="code" href="structfaiss_1_1Index.html#a6e92732617c4dbe364e7678dd8773a7f">is_trained</a> = <span class="keyword">true</span>;</div>
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<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> </div>
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<div class="line"><a name="l00045"></a><span class="lineno"> 45</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#abb964875e0893de1d8334ca5ad0f62dc">copyFrom</a>(index);</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> </div>
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<div class="line"><a name="l00048"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#aff5330eb125352cc599224584bd5d6bb"> 48</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#af8a1626e4c54a451d0b9f82df3a6687e">GpuIndexFlat::GpuIndexFlat</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html">GpuResources</a>* resources,</div>
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<div class="line"><a name="l00049"></a><span class="lineno"> 49</span>  <span class="keywordtype">int</span> dims,</div>
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<div class="line"><a name="l00050"></a><span class="lineno"> 50</span>  <a class="code" href="namespacefaiss.html#afd12191c638da74760ff397cf319752c">faiss::MetricType</a> metric,</div>
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<div class="line"><a name="l00051"></a><span class="lineno"> 51</span>  <a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html">GpuIndexFlatConfig</a> config) :</div>
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<div class="line"><a name="l00052"></a><span class="lineno"> 52</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html">GpuIndex</a>(resources, dims, metric, config),</div>
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<div class="line"><a name="l00053"></a><span class="lineno"> 53</span>  minPagedSize_(kMinPageSize),</div>
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<div class="line"><a name="l00054"></a><span class="lineno"> 54</span>  config_(config),</div>
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<div class="line"><a name="l00055"></a><span class="lineno"> 55</span>  data_(nullptr) {</div>
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<div class="line"><a name="l00056"></a><span class="lineno"> 56</span>  verifySettings_();</div>
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<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> </div>
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<div class="line"><a name="l00058"></a><span class="lineno"> 58</span>  <span class="comment">// Flat index doesn't need training</span></div>
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<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  this-><a class="code" href="structfaiss_1_1Index.html#a6e92732617c4dbe364e7678dd8773a7f">is_trained</a> = <span class="keyword">true</span>;</div>
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<div class="line"><a name="l00060"></a><span class="lineno"> 60</span> </div>
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<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  <span class="comment">// Construct index</span></div>
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<div class="line"><a name="l00062"></a><span class="lineno"> 62</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceScope.html">DeviceScope</a> scope(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>);</div>
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<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a> = <span class="keyword">new</span> <a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html">FlatIndex</a>(resources,</div>
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<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  dims,</div>
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<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  metric == faiss::METRIC_L2,</div>
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<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#afd694186c87751937a646f3db2c8ba3d">useFloat16</a>,</div>
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<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#a5a2d8737f4277e55fc1a99ef4fc4c630">useFloat16Accumulator</a>,</div>
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<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#a0342a26f5e59563bfe04f3f80e3b27f0">storeTransposed</a>,</div>
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<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#af304169eac7781b573f76d545f37b7d9">memorySpace_</a>);</div>
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<div class="line"><a name="l00070"></a><span class="lineno"> 70</span> }</div>
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<div class="line"><a name="l00071"></a><span class="lineno"> 71</span> </div>
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<div class="line"><a name="l00072"></a><span class="lineno"> 72</span> GpuIndexFlat::~GpuIndexFlat() {</div>
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<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keyword">delete</span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>;</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> </div>
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<div class="line"><a name="l00076"></a><span class="lineno"> 76</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00077"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a752f8129ccb94fa0c6f346ae03ff536d"> 77</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a752f8129ccb94fa0c6f346ae03ff536d">GpuIndexFlat::setMinPagingSize</a>(<span class="keywordtype">size_t</span> size) {</div>
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<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#aad665a7b5888b4aafd47ae0f8d0e6c40">minPagedSize_</a> = size;</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> </div>
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<div class="line"><a name="l00081"></a><span class="lineno"> 81</span> <span class="keywordtype">size_t</span></div>
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<div class="line"><a name="l00082"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a44532c7e5165d36e5da57272d37544ae"> 82</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a44532c7e5165d36e5da57272d37544ae">GpuIndexFlat::getMinPagingSize</a>()<span class="keyword"> const </span>{</div>
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<div class="line"><a name="l00083"></a><span class="lineno"> 83</span>  <span class="keywordflow">return</span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#aad665a7b5888b4aafd47ae0f8d0e6c40">minPagedSize_</a>;</div>
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<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> }</div>
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<div class="line"><a name="l00085"></a><span class="lineno"> 85</span> </div>
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<div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#abb964875e0893de1d8334ca5ad0f62dc"> 87</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#abb964875e0893de1d8334ca5ad0f62dc">GpuIndexFlat::copyFrom</a>(<span class="keyword">const</span> <a class="code" href="structfaiss_1_1IndexFlat.html">faiss::IndexFlat</a>* index) {</div>
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<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceScope.html">DeviceScope</a> scope(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>);</div>
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<div class="line"><a name="l00089"></a><span class="lineno"> 89</span> </div>
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<div class="line"><a name="l00090"></a><span class="lineno"> 90</span>  this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a> = index-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>;</div>
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<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  this-><a class="code" href="structfaiss_1_1Index.html#a8e18f641854b2bde83ecff0a2f9a6f4e">metric_type</a> = index-><a class="code" href="structfaiss_1_1Index.html#a8e18f641854b2bde83ecff0a2f9a6f4e">metric_type</a>;</div>
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<div class="line"><a name="l00092"></a><span class="lineno"> 92</span> </div>
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<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  <span class="comment">// GPU code has 32 bit indices</span></div>
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<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  FAISS_THROW_IF_NOT_FMT(index-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> <=</div>
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<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  (<a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a>) std::numeric_limits<int>::max(),</div>
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<div class="line"><a name="l00096"></a><span class="lineno"> 96</span>  <span class="stringliteral">"GPU index only supports up to %zu indices; "</span></div>
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<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  <span class="stringliteral">"attempting to copy CPU index with %zu parameters"</span>,</div>
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<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  (<span class="keywordtype">size_t</span>) std::numeric_limits<int>::max(),</div>
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<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  (<span class="keywordtype">size_t</span>) index-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>);</div>
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<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> = index-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>;</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>  <span class="keyword">delete</span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>;</div>
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<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a> = <span class="keyword">new</span> <a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html">FlatIndex</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">resources_</a>,</div>
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<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>,</div>
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<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  index-><a class="code" href="structfaiss_1_1Index.html#a8e18f641854b2bde83ecff0a2f9a6f4e">metric_type</a> == faiss::METRIC_L2,</div>
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<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#afd694186c87751937a646f3db2c8ba3d">useFloat16</a>,</div>
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<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#a5a2d8737f4277e55fc1a99ef4fc4c630">useFloat16Accumulator</a>,</div>
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<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#a0342a26f5e59563bfe04f3f80e3b27f0">storeTransposed</a>,</div>
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<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#af304169eac7781b573f76d545f37b7d9">memorySpace_</a>);</div>
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<div class="line"><a name="l00110"></a><span class="lineno"> 110</span> </div>
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<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  <span class="comment">// The index could be empty</span></div>
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<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  <span class="keywordflow">if</span> (index-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> > 0) {</div>
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<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#ab91c9ddf7dd258620f424619cb029e22">add</a>(index-><a class="code" href="structfaiss_1_1IndexFlat.html#a9001de47890fe5d2eced9551d3613d47">xb</a>.data(),</div>
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<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  index-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>,</div>
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<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a6c564198df6ba675920c993e2af34b8c">getDefaultStream</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>));</div>
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<div class="line"><a name="l00116"></a><span class="lineno"> 116</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> </div>
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<div class="line"><a name="l00119"></a><span class="lineno"> 119</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00120"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a046007ff2fafcafc6ae328769c700e39"> 120</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a046007ff2fafcafc6ae328769c700e39">GpuIndexFlat::copyTo</a>(<a class="code" href="structfaiss_1_1IndexFlat.html">faiss::IndexFlat</a>* index)<span class="keyword"> const </span>{</div>
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<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceScope.html">DeviceScope</a> scope(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>);</div>
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<div class="line"><a name="l00122"></a><span class="lineno"> 122</span> </div>
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<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  index-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a> = this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>;</div>
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<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  index-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> = this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>;</div>
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<div class="line"><a name="l00125"></a><span class="lineno"> 125</span>  index-><a class="code" href="structfaiss_1_1Index.html#a8e18f641854b2bde83ecff0a2f9a6f4e">metric_type</a> = this-><a class="code" href="structfaiss_1_1Index.html#a8e18f641854b2bde83ecff0a2f9a6f4e">metric_type</a>;</div>
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<div class="line"><a name="l00126"></a><span class="lineno"> 126</span> </div>
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<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  FAISS_ASSERT(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a6988df17792dae30f24cc859728777e6">getSize</a>() == this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>);</div>
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<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  index-><a class="code" href="structfaiss_1_1IndexFlat.html#a9001de47890fe5d2eced9551d3613d47">xb</a>.resize(this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> * this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>);</div>
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<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div>
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<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a6c564198df6ba675920c993e2af34b8c">getDefaultStream</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>);</div>
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<div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div>
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<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keywordflow">if</span> (this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> > 0) {</div>
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<div class="line"><a name="l00133"></a><span class="lineno"> 133</span>  <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#afd694186c87751937a646f3db2c8ba3d">useFloat16</a>) {</div>
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<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keyword">auto</span> vecFloat32 = <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a258b0dd61a9c352ec7d68fa8bac0d7ad">getVectorsFloat32Copy</a>(stream);</div>
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<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  fromDevice(vecFloat32, index-><a class="code" href="structfaiss_1_1IndexFlat.html#a9001de47890fe5d2eced9551d3613d47">xb</a>.data(), stream);</div>
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<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  } <span class="keywordflow">else</span> {</div>
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<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  fromDevice(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a12058744ffb3fbcbb047872449269c06">getVectorsFloat32Ref</a>(), index-><a class="code" href="structfaiss_1_1IndexFlat.html#a9001de47890fe5d2eced9551d3613d47">xb</a>.data(), stream);</div>
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<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  }</div>
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<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  }</div>
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<div class="line"><a name="l00140"></a><span class="lineno"> 140</span> }</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> <span class="keywordtype">size_t</span></div>
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<div class="line"><a name="l00143"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a51b5aa0d68670ec7ccb32b0353c7387f"> 143</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a51b5aa0d68670ec7ccb32b0353c7387f">GpuIndexFlat::getNumVecs</a>()<span class="keyword"> const </span>{</div>
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<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordflow">return</span> this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>;</div>
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<div class="line"><a name="l00145"></a><span class="lineno"> 145</span> }</div>
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<div class="line"><a name="l00146"></a><span class="lineno"> 146</span> </div>
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<div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00148"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a67161796f274a7171a67c36bdf1ef1db"> 148</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a67161796f274a7171a67c36bdf1ef1db">GpuIndexFlat::reset</a>() {</div>
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<div class="line"><a name="l00149"></a><span class="lineno"> 149</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceScope.html">DeviceScope</a> scope(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>);</div>
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<div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div>
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<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <span class="comment">// Free the underlying memory</span></div>
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<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#ae06cb2ffd46659b6639b97297546096e">reset</a>();</div>
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<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> = 0;</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="keywordtype">void</span></div>
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<div class="line"><a name="l00157"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a0e74fad76628ddfb5ae3dc1d1c69f7e8"> 157</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a0e74fad76628ddfb5ae3dc1d1c69f7e8">GpuIndexFlat::train</a>(<a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">Index::idx_t</a> n, <span class="keyword">const</span> <span class="keywordtype">float</span>* x) {</div>
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<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="comment">// nothing to do</span></div>
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<div class="line"><a name="l00159"></a><span class="lineno"> 159</span> }</div>
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<div class="line"><a name="l00160"></a><span class="lineno"> 160</span> </div>
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<div class="line"><a name="l00161"></a><span class="lineno"> 161</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00162"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a35d31b6b5ea89629b369655fd03bd505"> 162</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a35d31b6b5ea89629b369655fd03bd505">GpuIndexFlat::add</a>(<a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">Index::idx_t</a> n, <span class="keyword">const</span> <span class="keywordtype">float</span>* x) {</div>
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<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceScope.html">DeviceScope</a> scope(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>);</div>
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<div class="line"><a name="l00164"></a><span class="lineno"> 164</span> </div>
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<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="comment">// To avoid multiple re-allocations, ensure we have enough storage</span></div>
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<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  <span class="comment">// available</span></div>
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<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a7a06b678b97e3732939f6a4fb5106ef6">reserve</a>(n, <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a6c564198df6ba675920c993e2af34b8c">getDefaultStream</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>));</div>
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<div class="line"><a name="l00168"></a><span class="lineno"> 168</span> </div>
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<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="comment">// If we're not operating in float16 mode, we don't need the input</span></div>
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<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  <span class="comment">// data to be resident on our device; we can add directly.</span></div>
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<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  <span class="keywordflow">if</span> (!<a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#afd694186c87751937a646f3db2c8ba3d">useFloat16</a>) {</div>
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<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae0c916b911eda2f1a09a55f42ebc729c">addImpl_</a>(n, x, <span class="keyword">nullptr</span>);</div>
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<div class="line"><a name="l00173"></a><span class="lineno"> 173</span>  } <span class="keywordflow">else</span> {</div>
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<div class="line"><a name="l00174"></a><span class="lineno"> 174</span>  <span class="comment">// Otherwise, perform the paging</span></div>
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<div class="line"><a name="l00175"></a><span class="lineno"> 175</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#af576341f6996b0e80e26b9748db51eb7">GpuIndex::add</a>(n, x);</div>
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<div class="line"><a name="l00176"></a><span class="lineno"> 176</span>  }</div>
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<div class="line"><a name="l00177"></a><span class="lineno"> 177</span> }</div>
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<div class="line"><a name="l00178"></a><span class="lineno"> 178</span> </div>
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<div class="line"><a name="l00179"></a><span class="lineno"> 179</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00180"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae0c916b911eda2f1a09a55f42ebc729c"> 180</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae0c916b911eda2f1a09a55f42ebc729c">GpuIndexFlat::addImpl_</a>(<a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">Index::idx_t</a> n,</div>
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<div class="line"><a name="l00181"></a><span class="lineno"> 181</span>  <span class="keyword">const</span> <span class="keywordtype">float</span>* x,</div>
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<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keyword">const</span> <a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">Index::idx_t</a>* ids) {</div>
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<div class="line"><a name="l00183"></a><span class="lineno"> 183</span>  <span class="comment">// Device is already set in GpuIndex::addInternal_</span></div>
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<div class="line"><a name="l00184"></a><span class="lineno"> 184</span> </div>
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<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <span class="comment">// We do not support add_with_ids</span></div>
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<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  FAISS_THROW_IF_NOT_MSG(!ids, <span class="stringliteral">"add_with_ids not supported"</span>);</div>
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<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  FAISS_THROW_IF_NOT(n > 0);</div>
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<div class="line"><a name="l00188"></a><span class="lineno"> 188</span> </div>
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<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="comment">// Due to GPU indexing in int32, we can't store more than this</span></div>
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<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  <span class="comment">// number of vectors on a GPU</span></div>
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<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  FAISS_THROW_IF_NOT_FMT(this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> + n <=</div>
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<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  (<a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a>) std::numeric_limits<int>::max(),</div>
|
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<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  <span class="stringliteral">"GPU index only supports up to %zu indices"</span>,</div>
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<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  (<span class="keywordtype">size_t</span>) std::numeric_limits<int>::max());</div>
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<div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div>
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<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#ab91c9ddf7dd258620f424619cb029e22">add</a>(x, n, <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a6c564198df6ba675920c993e2af34b8c">getDefaultStream</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>));</div>
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<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> += n;</div>
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<div class="line"><a name="l00198"></a><span class="lineno"> 198</span> }</div>
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<div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div>
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<div class="line"><a name="l00200"></a><span class="lineno"><a class="line" href="structfaiss_1_1gpu_1_1IntToLong.html"> 200</a></span> <span class="keyword">struct </span><a class="code" href="structfaiss_1_1gpu_1_1IntToLong.html">IntToLong</a> {</div>
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<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  __device__ <span class="keywordtype">long</span> operator()(<span class="keywordtype">int</span> v)<span class="keyword"> const </span>{ <span class="keywordflow">return</span> (<span class="keywordtype">long</span>) v; }</div>
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<div class="line"><a name="l00202"></a><span class="lineno"> 202</span> };</div>
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<div class="line"><a name="l00203"></a><span class="lineno"> 203</span> </div>
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<div class="line"><a name="l00204"></a><span class="lineno"> 204</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00205"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ac0f0301829363f920e619f673a4d97f3"> 205</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ac0f0301829363f920e619f673a4d97f3">GpuIndexFlat::search</a>(<a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a> n,</div>
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<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  <span class="keyword">const</span> <span class="keywordtype">float</span>* x,</div>
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<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  <a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a> k,</div>
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<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  <span class="keywordtype">float</span>* distances,</div>
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<div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  <a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a>* labels)<span class="keyword"> const </span>{</div>
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<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordflow">if</span> (n == 0) {</div>
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<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  <span class="keywordflow">return</span>;</div>
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<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  }</div>
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<div class="line"><a name="l00213"></a><span class="lineno"> 213</span> </div>
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<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  <span class="comment">// For now, only support <= max int results</span></div>
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<div class="line"><a name="l00215"></a><span class="lineno"> 215</span>  FAISS_THROW_IF_NOT_FMT(n <=</div>
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<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  (<a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a>) std::numeric_limits<int>::max(),</div>
|
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<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  <span class="stringliteral">"GPU index only supports up to %zu indices"</span>,</div>
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<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  (<span class="keywordtype">size_t</span>) std::numeric_limits<int>::max());</div>
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<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  FAISS_THROW_IF_NOT_FMT(k <= 1024,</div>
|
|
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="stringliteral">"GPU only supports k <= 1024 (requested %d)"</span>,</div>
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|
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  (<span class="keywordtype">int</span>) k); <span class="comment">// select limitation</span></div>
|
|
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span> </div>
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|
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceScope.html">DeviceScope</a> scope(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>);</div>
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<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a6c564198df6ba675920c993e2af34b8c">getDefaultStream</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>);</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">// The input vectors may be too large for the GPU, but we still</span></div>
|
|
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="comment">// assume that the output distances and labels are not.</span></div>
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|
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="comment">// Go ahead and make space for output distances and labels on the</span></div>
|
|
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="comment">// GPU.</span></div>
|
|
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="comment">// If we reach a point where all inputs are too big, we can add</span></div>
|
|
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="comment">// another level of tiling.</span></div>
|
|
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keyword">auto</span> outDistances = toDevice<float, 2>(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">resources_</a>,</div>
|
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<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>,</div>
|
|
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  distances,</div>
|
|
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  stream,</div>
|
|
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  {(int) n, (<span class="keywordtype">int</span>) k});</div>
|
|
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span> </div>
|
|
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="comment">// FlatIndex only supports an interface returning int indices</span></div>
|
|
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<int, 2, true></a> outIntIndices(</div>
|
|
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  resources_->getMemoryManagerCurrentDevice(),</div>
|
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<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  {(int) n, (<span class="keywordtype">int</span>) k}, stream);</div>
|
|
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span> </div>
|
|
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  <span class="keywordtype">bool</span> usePaged = <span class="keyword">false</span>;</div>
|
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<div class="line"><a name="l00244"></a><span class="lineno"> 244</span> </div>
|
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<div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  <span class="keywordflow">if</span> (getDeviceForAddress(x) == -1) {</div>
|
|
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span>  <span class="comment">// It is possible that the user is querying for a vector set size</span></div>
|
|
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="comment">// `x` that won't fit on the GPU.</span></div>
|
|
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="comment">// In this case, we will have to handle paging of the data from CPU</span></div>
|
|
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="comment">// -> GPU.</span></div>
|
|
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="comment">// Currently, we don't handle the case where the output data won't</span></div>
|
|
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  <span class="comment">// fit on the GPU (e.g., n * k is too large for the GPU memory).</span></div>
|
|
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordtype">size_t</span> dataSize = (size_t) n * this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a> * <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>);</div>
|
|
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span> </div>
|
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<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keywordflow">if</span> (dataSize >= <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#aad665a7b5888b4aafd47ae0f8d0e6c40">minPagedSize_</a>) {</div>
|
|
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#afedeff5442b6ed94f856cecb8d8e598d">searchFromCpuPaged_</a>(n, x, k,</div>
|
|
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  outDistances.data(),</div>
|
|
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  outIntIndices.data());</div>
|
|
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  usePaged = <span class="keyword">true</span>;</div>
|
|
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span>  }</div>
|
|
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  }</div>
|
|
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span> </div>
|
|
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  <span class="keywordflow">if</span> (!usePaged) {</div>
|
|
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  searchNonPaged_(n, x, k,</div>
|
|
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  outDistances.data(),</div>
|
|
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  outIntIndices.data());</div>
|
|
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  }</div>
|
|
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span> </div>
|
|
<div class="line"><a name="l00268"></a><span class="lineno"> 268</span>  <span class="comment">// Convert and copy int indices out</span></div>
|
|
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keyword">auto</span> outIndices = toDevice<faiss::Index::idx_t, 2>(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">resources_</a>,</div>
|
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<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>,</div>
|
|
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  labels,</div>
|
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<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  stream,</div>
|
|
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  {(int) n, (<span class="keywordtype">int</span>) k});</div>
|
|
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span> </div>
|
|
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="comment">// Convert int to long</span></div>
|
|
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  thrust::transform(thrust::cuda::par.on(stream),</div>
|
|
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  outIntIndices.data(),</div>
|
|
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  outIntIndices.end(),</div>
|
|
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  outIndices.data(),</div>
|
|
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <a class="code" href="structfaiss_1_1gpu_1_1IntToLong.html">IntToLong</a>());</div>
|
|
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span> </div>
|
|
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="comment">// Copy back if necessary</span></div>
|
|
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  fromDevice<float, 2>(outDistances, distances, stream);</div>
|
|
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  fromDevice<faiss::Index::idx_t, 2>(outIndices, labels, stream);</div>
|
|
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span> }</div>
|
|
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div>
|
|
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00288"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ac99bfd11ff5150f29cf054ea55fc8fe4"> 288</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ac99bfd11ff5150f29cf054ea55fc8fe4">GpuIndexFlat::searchImpl_</a>(<a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a> n,</div>
|
|
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keyword">const</span> <span class="keywordtype">float</span>* x,</div>
|
|
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a> k,</div>
|
|
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keywordtype">float</span>* distances,</div>
|
|
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a>* labels)<span class="keyword"> const </span>{</div>
|
|
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  FAISS_ASSERT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"Should not be called"</span>);</div>
|
|
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span> }</div>
|
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<div class="line"><a name="l00295"></a><span class="lineno"> 295</span> </div>
|
|
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span> GpuIndexFlat::searchNonPaged_(<span class="keywordtype">int</span> n,</div>
|
|
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keyword">const</span> <span class="keywordtype">float</span>* x,</div>
|
|
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  <span class="keywordtype">int</span> k,</div>
|
|
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <span class="keywordtype">float</span>* outDistancesData,</div>
|
|
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordtype">int</span>* outIndicesData)<span class="keyword"> const </span>{</div>
|
|
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a> outDistances(outDistancesData, {n, k});</div>
|
|
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  Tensor<int, 2, true> outIndices(outIndicesData, {n, k});</div>
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<div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div>
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<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keyword">auto</span> stream = <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">resources_</a>-><a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html#a6c564198df6ba675920c993e2af34b8c">getDefaultStream</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>);</div>
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<div class="line"><a name="l00306"></a><span class="lineno"> 306</span> </div>
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<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="comment">// Make sure arguments are on the device we desire; use temporary</span></div>
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|
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  <span class="comment">// memory allocations to move it if necessary</span></div>
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|
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  <span class="keyword">auto</span> vecs = toDevice<float, 2>(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">resources_</a>,</div>
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<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">device_</a>,</div>
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<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keyword">const_cast<</span><span class="keywordtype">float</span>*<span class="keyword">></span>(x),</div>
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<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  stream,</div>
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<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  {n, (int) this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>});</div>
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|
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span> </div>
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<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>->query(vecs, k, outDistances, outIndices, <span class="keyword">true</span>);</div>
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<div class="line"><a name="l00316"></a><span class="lineno"> 316</span> }</div>
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<div class="line"><a name="l00317"></a><span class="lineno"> 317</span> </div>
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<div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00319"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#afedeff5442b6ed94f856cecb8d8e598d"> 319</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#afedeff5442b6ed94f856cecb8d8e598d">GpuIndexFlat::searchFromCpuPaged_</a>(<span class="keywordtype">int</span> n,</div>
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<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keyword">const</span> <span class="keywordtype">float</span>* x,</div>
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<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  <span class="keywordtype">int</span> k,</div>
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<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keywordtype">float</span>* outDistancesData,</div>
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<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keywordtype">int</span>* outIndicesData)<span class="keyword"> const </span>{</div>
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|
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<float, 2, true></a> outDistances(outDistancesData, {n, k});</div>
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|
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <a class="code" href="classfaiss_1_1gpu_1_1Tensor.html">Tensor<int, 2, true></a> outIndices(outIndicesData, {n, k});</div>
|
|
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span> </div>
|
|
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="comment">// Is pinned memory available?</span></div>
|
|
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keyword">auto</span> pinnedAlloc = resources_->getPinnedMemory();</div>
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|
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <span class="keywordtype">int</span> pageSizeInVecs =</div>
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|
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  (int) ((pinnedAlloc.second / 2) / (<span class="keyword">sizeof</span>(float) * this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>));</div>
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<div class="line"><a name="l00331"></a><span class="lineno"> 331</span> </div>
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<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keywordflow">if</span> (!pinnedAlloc.first || pageSizeInVecs < 1) {</div>
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<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="comment">// Just page without overlapping copy with compute</span></div>
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<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordtype">int</span> batchSize = utils::nextHighestPowerOf2(</div>
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<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  (<span class="keywordtype">int</span>) ((<span class="keywordtype">size_t</span>) kNonPinnedPageSize /</div>
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<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  (<span class="keyword">sizeof</span>(<span class="keywordtype">float</span>) * this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>)));</div>
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<div class="line"><a name="l00337"></a><span class="lineno"> 337</span> </div>
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<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> cur = 0; cur < n; cur += batchSize) {</div>
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<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  <span class="keywordtype">int</span> num = std::min(batchSize, n - cur);</div>
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<div class="line"><a name="l00340"></a><span class="lineno"> 340</span> </div>
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<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keyword">auto</span> outDistancesSlice = outDistances.narrowOutermost(cur, num);</div>
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|
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  <span class="keyword">auto</span> outIndicesSlice = outIndices.narrowOutermost(cur, num);</div>
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|
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span> </div>
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|
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  searchNonPaged_(num,</div>
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<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  x + (<span class="keywordtype">size_t</span>) cur * this->d,</div>
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<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  k,</div>
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<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  outDistancesSlice.data(),</div>
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|
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  outIndicesSlice.data());</div>
|
|
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  }</div>
|
|
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span> </div>
|
|
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  <span class="keywordflow">return</span>;</div>
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|
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  }</div>
|
|
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span> </div>
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|
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  <span class="comment">// Pinned memory is available, so we can overlap copy with compute.</span></div>
|
|
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  <span class="comment">// We use two pinned memory buffers, and triple-buffer the</span></div>
|
|
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  <span class="comment">// procedure:</span></div>
|
|
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="comment">// 1 CPU copy -> pinned</span></div>
|
|
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  <span class="comment">// 2 pinned copy -> GPU</span></div>
|
|
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  <span class="comment">// 3 GPU compute</span></div>
|
|
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  <span class="comment">// 1 2 3 1 2 3 ... (pinned buf A)</span></div>
|
|
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  <span class="comment">// 1 2 3 1 2 ... (pinned buf B)</span></div>
|
|
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  <span class="comment">// 1 2 3 1 ... (pinned buf A)</span></div>
|
|
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="comment">// time -></span></div>
|
|
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <span class="keyword">auto</span> defaultStream = resources_->getDefaultStream(device_);</div>
|
|
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keyword">auto</span> copyStream = resources_->getAsyncCopyStream(device_);</div>
|
|
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span> </div>
|
|
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  FAISS_ASSERT((<span class="keywordtype">size_t</span>) pageSizeInVecs * this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a> <=</div>
|
|
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  (<span class="keywordtype">size_t</span>) std::numeric_limits<int>::max());</div>
|
|
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span> </div>
|
|
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordtype">float</span>* bufPinnedA = (<span class="keywordtype">float</span>*) pinnedAlloc.first;</div>
|
|
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordtype">float</span>* bufPinnedB = bufPinnedA + (<span class="keywordtype">size_t</span>) pageSizeInVecs * this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>;</div>
|
|
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordtype">float</span>* bufPinned[2] = {bufPinnedA, bufPinnedB};</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">// Reserve space on the GPU for the destination of the pinned buffer</span></div>
|
|
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="comment">// copy</span></div>
|
|
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a> bufGpuA(</div>
|
|
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  resources_->getMemoryManagerCurrentDevice(),</div>
|
|
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  {(int) pageSizeInVecs, (<span class="keywordtype">int</span>) this->d},</div>
|
|
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  defaultStream);</div>
|
|
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a> bufGpuB(</div>
|
|
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  resources_->getMemoryManagerCurrentDevice(),</div>
|
|
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  {(int) pageSizeInVecs, (<span class="keywordtype">int</span>) this->d},</div>
|
|
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  defaultStream);</div>
|
|
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a>* bufGpus[2] = {&bufGpuA, &bufGpuB};</div>
|
|
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span> </div>
|
|
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  <span class="comment">// Copy completion events for the pinned buffers</span></div>
|
|
<div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  std::unique_ptr<CudaEvent> eventPinnedCopyDone[2];</div>
|
|
<div class="line"><a name="l00392"></a><span class="lineno"> 392</span> </div>
|
|
<div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  <span class="comment">// Execute completion events for the GPU buffers</span></div>
|
|
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  std::unique_ptr<CudaEvent> eventGpuExecuteDone[2];</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>  <span class="comment">// All offsets are in terms of number of vectors; they remain within</span></div>
|
|
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="comment">// int bounds (as this function only handles max in vectors)</span></div>
|
|
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span> </div>
|
|
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="comment">// Current start offset for buffer 1</span></div>
|
|
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keywordtype">int</span> cur1 = 0;</div>
|
|
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keywordtype">int</span> cur1BufIndex = 0;</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">// Current start offset for buffer 2</span></div>
|
|
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="keywordtype">int</span> cur2 = -1;</div>
|
|
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="keywordtype">int</span> cur2BufIndex = 0;</div>
|
|
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span> </div>
|
|
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="comment">// Current start offset for buffer 3</span></div>
|
|
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  <span class="keywordtype">int</span> cur3 = -1;</div>
|
|
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  <span class="keywordtype">int</span> cur3BufIndex = 0;</div>
|
|
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span> </div>
|
|
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  <span class="keywordflow">while</span> (cur3 < n) {</div>
|
|
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <span class="comment">// Start async pinned -> GPU copy first (buf 2)</span></div>
|
|
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  <span class="keywordflow">if</span> (cur2 != -1 && cur2 < n) {</div>
|
|
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  <span class="comment">// Copy pinned to GPU</span></div>
|
|
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="keywordtype">int</span> numToCopy = std::min(pageSizeInVecs, n - cur2);</div>
|
|
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span> </div>
|
|
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  <span class="comment">// Make sure any previous execution has completed before continuing</span></div>
|
|
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <span class="keyword">auto</span>& eventPrev = eventGpuExecuteDone[cur2BufIndex];</div>
|
|
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <span class="keywordflow">if</span> (eventPrev.get()) {</div>
|
|
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  eventPrev->streamWaitOnEvent(copyStream);</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> </div>
|
|
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  CUDA_VERIFY(cudaMemcpyAsync(bufGpus[cur2BufIndex]->data(),</div>
|
|
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  bufPinned[cur2BufIndex],</div>
|
|
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  (<span class="keywordtype">size_t</span>) numToCopy * this->d * <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>),</div>
|
|
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  cudaMemcpyHostToDevice,</div>
|
|
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  copyStream));</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>  <span class="comment">// Mark a completion event in this stream</span></div>
|
|
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  eventPinnedCopyDone[cur2BufIndex] =</div>
|
|
<div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  std::move(std::unique_ptr<CudaEvent>(<span class="keyword">new</span> <a class="code" href="classfaiss_1_1gpu_1_1CudaEvent.html">CudaEvent</a>(copyStream)));</div>
|
|
<div class="line"><a name="l00432"></a><span class="lineno"> 432</span> </div>
|
|
<div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="comment">// We pick up from here</span></div>
|
|
<div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  cur3 = cur2;</div>
|
|
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  cur2 += numToCopy;</div>
|
|
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  cur2BufIndex = (cur2BufIndex == 0) ? 1 : 0;</div>
|
|
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  }</div>
|
|
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span> </div>
|
|
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="keywordflow">if</span> (cur3 != -1 && cur3 < n) {</div>
|
|
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <span class="comment">// Process on GPU</span></div>
|
|
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="keywordtype">int</span> numToProcess = std::min(pageSizeInVecs, n - cur3);</div>
|
|
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span> </div>
|
|
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <span class="comment">// Make sure the previous copy has completed before continuing</span></div>
|
|
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <span class="keyword">auto</span>& eventPrev = eventPinnedCopyDone[cur3BufIndex];</div>
|
|
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  FAISS_ASSERT(eventPrev.get());</div>
|
|
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span> </div>
|
|
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  eventPrev->streamWaitOnEvent(defaultStream);</div>
|
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<div class="line"><a name="l00448"></a><span class="lineno"> 448</span> </div>
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<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <span class="comment">// Create tensor wrappers</span></div>
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<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceTensor.html">DeviceTensor<float, 2, true></a> input(bufGpus[cur3BufIndex]->data(),</div>
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<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  {numToProcess, this->d});</div>
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<div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="keyword">auto</span> outDistancesSlice = outDistances.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#ac2d0fc7199901a8e0788b58f0970b133">narrowOutermost</a>(cur3, numToProcess);</div>
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<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="keyword">auto</span> outIndicesSlice = outIndices.<a class="code" href="classfaiss_1_1gpu_1_1Tensor.html#ac2d0fc7199901a8e0788b58f0970b133">narrowOutermost</a>(cur3, numToProcess);</div>
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<div class="line"><a name="l00454"></a><span class="lineno"> 454</span> </div>
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<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>->query(input, k,</div>
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<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  outDistancesSlice,</div>
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<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  outIndicesSlice, <span class="keyword">true</span>);</div>
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<div class="line"><a name="l00458"></a><span class="lineno"> 458</span> </div>
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<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <span class="comment">// Create completion event</span></div>
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<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  eventGpuExecuteDone[cur3BufIndex] =</div>
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<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  std::move(std::unique_ptr<CudaEvent>(<span class="keyword">new</span> <a class="code" href="classfaiss_1_1gpu_1_1CudaEvent.html">CudaEvent</a>(defaultStream)));</div>
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<div class="line"><a name="l00462"></a><span class="lineno"> 462</span> </div>
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<div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <span class="comment">// We pick up from here</span></div>
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<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  cur3BufIndex = (cur3BufIndex == 0) ? 1 : 0;</div>
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<div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  cur3 += numToProcess;</div>
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<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  }</div>
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<div class="line"><a name="l00467"></a><span class="lineno"> 467</span> </div>
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<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  <span class="keywordflow">if</span> (cur1 < n) {</div>
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<div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <span class="comment">// Copy CPU mem to CPU pinned</span></div>
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<div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="keywordtype">int</span> numToCopy = std::min(pageSizeInVecs, n - cur1);</div>
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<div class="line"><a name="l00471"></a><span class="lineno"> 471</span> </div>
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<div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  <span class="comment">// Make sure any previous copy has completed before continuing</span></div>
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<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <span class="keyword">auto</span>& eventPrev = eventPinnedCopyDone[cur1BufIndex];</div>
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<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="keywordflow">if</span> (eventPrev.get()) {</div>
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<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  eventPrev->cpuWaitOnEvent();</div>
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<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  }</div>
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<div class="line"><a name="l00477"></a><span class="lineno"> 477</span> </div>
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<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  memcpy(bufPinned[cur1BufIndex],</div>
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<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  x + (<span class="keywordtype">size_t</span>) cur1 * this->d,</div>
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<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  (<span class="keywordtype">size_t</span>) numToCopy * this->d * <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>));</div>
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<div class="line"><a name="l00481"></a><span class="lineno"> 481</span> </div>
|
|
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <span class="comment">// We pick up from here</span></div>
|
|
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  cur2 = cur1;</div>
|
|
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  cur1 += numToCopy;</div>
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<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  cur1BufIndex = (cur1BufIndex == 0) ? 1 : 0;</div>
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<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  }</div>
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<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  }</div>
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<div class="line"><a name="l00488"></a><span class="lineno"> 488</span> }</div>
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<div class="line"><a name="l00489"></a><span class="lineno"> 489</span> </div>
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<div class="line"><a name="l00490"></a><span class="lineno"> 490</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00491"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a7f1cdf03d3545a43fc91bb5cace3b6fd"> 491</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a7f1cdf03d3545a43fc91bb5cace3b6fd">GpuIndexFlat::reconstruct</a>(<a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a> key,</div>
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<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  <span class="keywordtype">float</span>* out)<span class="keyword"> const </span>{</div>
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<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceScope.html">DeviceScope</a> scope(device_);</div>
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<div class="line"><a name="l00494"></a><span class="lineno"> 494</span> </div>
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<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  FAISS_THROW_IF_NOT_MSG(key < this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>, <span class="stringliteral">"index out of bounds"</span>);</div>
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<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keyword">auto</span> stream = resources_->getDefaultStream(device_);</div>
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<div class="line"><a name="l00497"></a><span class="lineno"> 497</span> </div>
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<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#afd694186c87751937a646f3db2c8ba3d">useFloat16</a>) {</div>
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|
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  <span class="keyword">auto</span> vec = <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a258b0dd61a9c352ec7d68fa8bac0d7ad">getVectorsFloat32Copy</a>(key, 1, stream);</div>
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<div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  fromDevice(vec.data(), out, this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>, stream);</div>
|
|
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <span class="keyword">auto</span> vec = <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a12058744ffb3fbcbb047872449269c06">getVectorsFloat32Ref</a>()[key];</div>
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|
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  fromDevice(vec.data(), out, this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>, stream);</div>
|
|
<div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  }</div>
|
|
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span> }</div>
|
|
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span> </div>
|
|
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00508"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a472732e9bd8ffb1aa4c3abc31063dd28"> 508</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a472732e9bd8ffb1aa4c3abc31063dd28">GpuIndexFlat::reconstruct_n</a>(<a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a> i0,</div>
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|
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a> num,</div>
|
|
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <span class="keywordtype">float</span>* out)<span class="keyword"> const </span>{</div>
|
|
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  <a class="code" href="classfaiss_1_1gpu_1_1DeviceScope.html">DeviceScope</a> scope(device_);</div>
|
|
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span> </div>
|
|
<div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  FAISS_THROW_IF_NOT_MSG(i0 < this-><a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>, <span class="stringliteral">"index out of bounds"</span>);</div>
|
|
<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  FAISS_THROW_IF_NOT_MSG(i0 + num - 1 < this->ntotal, <span class="stringliteral">"num out of bounds"</span>);</div>
|
|
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <span class="keyword">auto</span> stream = resources_->getDefaultStream(device_);</div>
|
|
<div class="line"><a name="l00516"></a><span class="lineno"> 516</span> </div>
|
|
<div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#afd694186c87751937a646f3db2c8ba3d">useFloat16</a>) {</div>
|
|
<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="keyword">auto</span> vec = <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a258b0dd61a9c352ec7d68fa8bac0d7ad">getVectorsFloat32Copy</a>(i0, num, stream);</div>
|
|
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  fromDevice(vec.data(), out, num * this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>, stream);</div>
|
|
<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <span class="keyword">auto</span> vec = <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">data_</a>-><a class="code" href="classfaiss_1_1gpu_1_1FlatIndex.html#a12058744ffb3fbcbb047872449269c06">getVectorsFloat32Ref</a>()[i0];</div>
|
|
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  fromDevice(vec.data(), out, this-><a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a> * num, stream);</div>
|
|
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  }</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> </div>
|
|
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span> GpuIndexFlat::verifySettings_()<span class="keyword"> const </span>{</div>
|
|
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <span class="comment">// If we want Hgemm, ensure that it is supported on this device</span></div>
|
|
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  <span class="keywordflow">if</span> (<a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#a5a2d8737f4277e55fc1a99ef4fc4c630">useFloat16Accumulator</a>) {</div>
|
|
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span> <span class="preprocessor">#ifdef FAISS_USE_FLOAT16</span></div>
|
|
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span> <span class="preprocessor"></span> FAISS_THROW_IF_NOT_MSG(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#afd694186c87751937a646f3db2c8ba3d">useFloat16</a>,</div>
|
|
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  <span class="stringliteral">"useFloat16Accumulator can only be enabled "</span></div>
|
|
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="stringliteral">"with useFloat16"</span>);</div>
|
|
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span> </div>
|
|
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  FAISS_THROW_IF_NOT_FMT(getDeviceSupportsFloat16Math(<a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexConfig.html#aab05a0aa7b42feae7df4e556a52ead57">device</a>),</div>
|
|
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <span class="stringliteral">"Device %d does not support Hgemm "</span></div>
|
|
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  <span class="stringliteral">"(useFloat16Accumulator)"</span>,</div>
|
|
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">config_</a>.<a class="code" href="structfaiss_1_1gpu_1_1GpuIndexConfig.html#aab05a0aa7b42feae7df4e556a52ead57">device</a>);</div>
|
|
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span> <span class="preprocessor">#else</span></div>
|
|
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span> <span class="preprocessor"></span> FAISS_THROW_IF_NOT_MSG(<span class="keyword">false</span>, <span class="stringliteral">"not compiled with float16 support"</span>);</div>
|
|
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span> <span class="preprocessor"></span> }</div>
|
|
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span> }</div>
|
|
<div class="line"><a name="l00544"></a><span class="lineno"> 544</span> </div>
|
|
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span> <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span> <span class="comment">// GpuIndexFlatL2</span></div>
|
|
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span> <span class="comment">//</span></div>
|
|
<div class="line"><a name="l00548"></a><span class="lineno"> 548</span> </div>
|
|
<div class="line"><a name="l00549"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#aed22de4a439fa0b2f560e3c716a7c626"> 549</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#aed22de4a439fa0b2f560e3c716a7c626">GpuIndexFlatL2::GpuIndexFlatL2</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html">GpuResources</a>* resources,</div>
|
|
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <a class="code" href="structfaiss_1_1IndexFlatL2.html">faiss::IndexFlatL2</a>* index,</div>
|
|
<div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  <a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html">GpuIndexFlatConfig</a> config) :</div>
|
|
<div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html">GpuIndexFlat</a>(resources, index, config) {</div>
|
|
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span> }</div>
|
|
<div class="line"><a name="l00554"></a><span class="lineno"> 554</span> </div>
|
|
<div class="line"><a name="l00555"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#a514832ff1173021362b583a6b2941b87"> 555</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#aed22de4a439fa0b2f560e3c716a7c626">GpuIndexFlatL2::GpuIndexFlatL2</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html">GpuResources</a>* resources,</div>
|
|
<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  <span class="keywordtype">int</span> dims,</div>
|
|
<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html">GpuIndexFlatConfig</a> config) :</div>
|
|
<div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html">GpuIndexFlat</a>(resources, dims, faiss::METRIC_L2, config) {</div>
|
|
<div class="line"><a name="l00559"></a><span class="lineno"> 559</span> }</div>
|
|
<div class="line"><a name="l00560"></a><span class="lineno"> 560</span> </div>
|
|
<div class="line"><a name="l00561"></a><span class="lineno"> 561</span> <span class="keywordtype">void</span></div>
|
|
<div class="line"><a name="l00562"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#a9a9de859274bb73e6d8ea02cae5ca9a6"> 562</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#a9a9de859274bb73e6d8ea02cae5ca9a6">GpuIndexFlatL2::copyFrom</a>(<a class="code" href="structfaiss_1_1IndexFlatL2.html">faiss::IndexFlatL2</a>* index) {</div>
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<div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#abb964875e0893de1d8334ca5ad0f62dc">GpuIndexFlat::copyFrom</a>(index);</div>
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<div class="line"><a name="l00564"></a><span class="lineno"> 564</span> }</div>
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<div class="line"><a name="l00565"></a><span class="lineno"> 565</span> </div>
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<div class="line"><a name="l00566"></a><span class="lineno"> 566</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00567"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#ab21960d379190b98aaa05ae3877dea09"> 567</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#ab21960d379190b98aaa05ae3877dea09">GpuIndexFlatL2::copyTo</a>(<a class="code" href="structfaiss_1_1IndexFlatL2.html">faiss::IndexFlatL2</a>* index) {</div>
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<div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a046007ff2fafcafc6ae328769c700e39">GpuIndexFlat::copyTo</a>(index);</div>
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<div class="line"><a name="l00569"></a><span class="lineno"> 569</span> }</div>
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<div class="line"><a name="l00570"></a><span class="lineno"> 570</span> </div>
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<div class="line"><a name="l00571"></a><span class="lineno"> 571</span> <span class="comment">//</span></div>
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<div class="line"><a name="l00572"></a><span class="lineno"> 572</span> <span class="comment">// GpuIndexFlatIP</span></div>
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<div class="line"><a name="l00573"></a><span class="lineno"> 573</span> <span class="comment">//</span></div>
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<div class="line"><a name="l00574"></a><span class="lineno"> 574</span> </div>
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<div class="line"><a name="l00575"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#a5f8c6e1a31cae06f6a5bcd1828307304"> 575</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#a5f8c6e1a31cae06f6a5bcd1828307304">GpuIndexFlatIP::GpuIndexFlatIP</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html">GpuResources</a>* resources,</div>
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<div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <a class="code" href="structfaiss_1_1IndexFlatIP.html">faiss::IndexFlatIP</a>* index,</div>
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<div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  <a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html">GpuIndexFlatConfig</a> config) :</div>
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<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html">GpuIndexFlat</a>(resources, index, config) {</div>
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<div class="line"><a name="l00579"></a><span class="lineno"> 579</span> }</div>
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<div class="line"><a name="l00580"></a><span class="lineno"> 580</span> </div>
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<div class="line"><a name="l00581"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#ad7ef0af6369d33f136579340f5bc8e0a"> 581</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#a5f8c6e1a31cae06f6a5bcd1828307304">GpuIndexFlatIP::GpuIndexFlatIP</a>(<a class="code" href="classfaiss_1_1gpu_1_1GpuResources.html">GpuResources</a>* resources,</div>
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<div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  <span class="keywordtype">int</span> dims,</div>
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<div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <a class="code" href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html">GpuIndexFlatConfig</a> config) :</div>
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<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html">GpuIndexFlat</a>(resources, dims, faiss::METRIC_INNER_PRODUCT, config) {</div>
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<div class="line"><a name="l00585"></a><span class="lineno"> 585</span> }</div>
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<div class="line"><a name="l00586"></a><span class="lineno"> 586</span> </div>
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<div class="line"><a name="l00587"></a><span class="lineno"> 587</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00588"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#aa181b1778a8dca81ac5cf6cd6a3d5f1d"> 588</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#aa181b1778a8dca81ac5cf6cd6a3d5f1d">GpuIndexFlatIP::copyFrom</a>(<a class="code" href="structfaiss_1_1IndexFlatIP.html">faiss::IndexFlatIP</a>* index) {</div>
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<div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#abb964875e0893de1d8334ca5ad0f62dc">GpuIndexFlat::copyFrom</a>(index);</div>
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<div class="line"><a name="l00590"></a><span class="lineno"> 590</span> }</div>
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<div class="line"><a name="l00591"></a><span class="lineno"> 591</span> </div>
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<div class="line"><a name="l00592"></a><span class="lineno"> 592</span> <span class="keywordtype">void</span></div>
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<div class="line"><a name="l00593"></a><span class="lineno"><a class="line" href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#af70d0fe80cf3bf16ffffd8b16ed64f08"> 593</a></span> <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#af70d0fe80cf3bf16ffffd8b16ed64f08">GpuIndexFlatIP::copyTo</a>(<a class="code" href="structfaiss_1_1IndexFlatIP.html">faiss::IndexFlatIP</a>* index) {</div>
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<div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <a class="code" href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a046007ff2fafcafc6ae328769c700e39">GpuIndexFlat::copyTo</a>(index);</div>
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<div class="line"><a name="l00595"></a><span class="lineno"> 595</span> }</div>
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<div class="line"><a name="l00596"></a><span class="lineno"> 596</span> </div>
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<div class="line"><a name="l00597"></a><span class="lineno"> 597</span> } } <span class="comment">// namespace</span></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1FlatIndex_html_a258b0dd61a9c352ec7d68fa8bac0d7ad"><div class="ttname"><a href="classfaiss_1_1gpu_1_1FlatIndex.html#a258b0dd61a9c352ec7d68fa8bac0d7ad">faiss::gpu::FlatIndex::getVectorsFloat32Copy</a></div><div class="ttdeci">DeviceTensor< float, 2, true > getVectorsFloat32Copy(cudaStream_t stream)</div><div class="ttdef"><b>Definition:</b> <a href="FlatIndex_8cu_source.html#l00091">FlatIndex.cu:91</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexFlat_html"><div class="ttname"><a href="structfaiss_1_1IndexFlat.html">faiss::IndexFlat</a></div><div class="ttdef"><b>Definition:</b> <a href="IndexFlat_8h_source.html#l00023">IndexFlat.h:23</a></div></div>
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<div class="ttc" id="structfaiss_1_1gpu_1_1GpuIndexFlatConfig_html_a5a2d8737f4277e55fc1a99ef4fc4c630"><div class="ttname"><a href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#a5a2d8737f4277e55fc1a99ef4fc4c630">faiss::gpu::GpuIndexFlatConfig::useFloat16Accumulator</a></div><div class="ttdeci">bool useFloat16Accumulator</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8h_source.html#l00040">GpuIndexFlat.h:40</a></div></div>
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<div class="ttc" id="structfaiss_1_1gpu_1_1GpuIndexFlatConfig_html_a0342a26f5e59563bfe04f3f80e3b27f0"><div class="ttname"><a href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#a0342a26f5e59563bfe04f3f80e3b27f0">faiss::gpu::GpuIndexFlatConfig::storeTransposed</a></div><div class="ttdeci">bool storeTransposed</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8h_source.html#l00048">GpuIndexFlat.h:48</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlatL2_html_a9a9de859274bb73e6d8ea02cae5ca9a6"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#a9a9de859274bb73e6d8ea02cae5ca9a6">faiss::gpu::GpuIndexFlatL2::copyFrom</a></div><div class="ttdeci">void copyFrom(faiss::IndexFlatL2 *index)</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00562">GpuIndexFlat.cu:562</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_a046007ff2fafcafc6ae328769c700e39"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a046007ff2fafcafc6ae328769c700e39">faiss::gpu::GpuIndexFlat::copyTo</a></div><div class="ttdeci">void copyTo(faiss::IndexFlat *index) const </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00120">GpuIndexFlat.cu:120</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_a472732e9bd8ffb1aa4c3abc31063dd28"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a472732e9bd8ffb1aa4c3abc31063dd28">faiss::gpu::GpuIndexFlat::reconstruct_n</a></div><div class="ttdeci">void reconstruct_n(faiss::Index::idx_t i0, faiss::Index::idx_t num, float *out) const override</div><div class="ttdoc">Batch reconstruction method. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00508">GpuIndexFlat.cu:508</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_a44532c7e5165d36e5da57272d37544ae"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a44532c7e5165d36e5da57272d37544ae">faiss::gpu::GpuIndexFlat::getMinPagingSize</a></div><div class="ttdeci">size_t getMinPagingSize() const </div><div class="ttdoc">Returns the current minimum data size for paged searches. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00082">GpuIndexFlat.cu:82</a></div></div>
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<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>
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<div class="ttc" id="classfaiss_1_1gpu_1_1FlatIndex_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1FlatIndex.html">faiss::gpu::FlatIndex</a></div><div class="ttdoc">Holder of GPU resources for a particular flat index. </div><div class="ttdef"><b>Definition:</b> <a href="FlatIndex_8cuh_source.html#l00023">FlatIndex.cuh:23</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlatL2_html_ab21960d379190b98aaa05ae3877dea09"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#ab21960d379190b98aaa05ae3877dea09">faiss::gpu::GpuIndexFlatL2::copyTo</a></div><div class="ttdeci">void copyTo(faiss::IndexFlatL2 *index)</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00567">GpuIndexFlat.cu:567</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexFlatL2_html"><div class="ttname"><a href="structfaiss_1_1IndexFlatL2.html">faiss::IndexFlatL2</a></div><div class="ttdef"><b>Definition:</b> <a href="IndexFlat_8h_source.html#l00079">IndexFlat.h:79</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_afedeff5442b6ed94f856cecb8d8e598d"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#afedeff5442b6ed94f856cecb8d8e598d">faiss::gpu::GpuIndexFlat::searchFromCpuPaged_</a></div><div class="ttdeci">void searchFromCpuPaged_(int n, const float *x, int k, float *outDistancesData, int *outIndicesData) const </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00319">GpuIndexFlat.cu:319</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_ae0c916b911eda2f1a09a55f42ebc729c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae0c916b911eda2f1a09a55f42ebc729c">faiss::gpu::GpuIndexFlat::addImpl_</a></div><div class="ttdeci">void addImpl_(faiss::Index::idx_t n, const float *x, const faiss::Index::idx_t *ids) override</div><div class="ttdoc">Called from GpuIndex for add. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00180">GpuIndexFlat.cu:180</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_ac99bfd11ff5150f29cf054ea55fc8fe4"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ac99bfd11ff5150f29cf054ea55fc8fe4">faiss::gpu::GpuIndexFlat::searchImpl_</a></div><div class="ttdeci">void searchImpl_(faiss::Index::idx_t n, const float *x, faiss::Index::idx_t k, float *distances, faiss::Index::idx_t *labels) const override</div><div class="ttdoc">Should not be called (we have our own implementation) </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00288">GpuIndexFlat.cu:288</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_a51b5aa0d68670ec7ccb32b0353c7387f"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a51b5aa0d68670ec7ccb32b0353c7387f">faiss::gpu::GpuIndexFlat::getNumVecs</a></div><div class="ttdeci">size_t getNumVecs() const </div><div class="ttdoc">Returns the number of vectors we contain. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00143">GpuIndexFlat.cu:143</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuResources_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuResources.html">faiss::gpu::GpuResources</a></div><div class="ttdef"><b>Definition:</b> <a href="GpuResources_8h_source.html#l00023">GpuResources.h:23</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_af8a1626e4c54a451d0b9f82df3a6687e"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#af8a1626e4c54a451d0b9f82df3a6687e">faiss::gpu::GpuIndexFlat::GpuIndexFlat</a></div><div class="ttdeci">GpuIndexFlat(GpuResources *resources, const faiss::IndexFlat *index, GpuIndexFlatConfig config=GpuIndexFlatConfig())</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00033">GpuIndexFlat.cu:33</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexFlatIP_html"><div class="ttname"><a href="structfaiss_1_1IndexFlatIP.html">faiss::IndexFlatIP</a></div><div class="ttdef"><b>Definition:</b> <a href="IndexFlat_8h_source.html#l00073">IndexFlat.h:73</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_a752f8129ccb94fa0c6f346ae03ff536d"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a752f8129ccb94fa0c6f346ae03ff536d">faiss::gpu::GpuIndexFlat::setMinPagingSize</a></div><div class="ttdeci">void setMinPagingSize(size_t size)</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00077">GpuIndexFlat.cu:77</a></div></div>
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<div class="ttc" id="structfaiss_1_1gpu_1_1GpuIndexFlatConfig_html_afd694186c87751937a646f3db2c8ba3d"><div class="ttname"><a href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html#afd694186c87751937a646f3db2c8ba3d">faiss::gpu::GpuIndexFlatConfig::useFloat16</a></div><div class="ttdeci">bool useFloat16</div><div class="ttdoc">Whether or not data is stored as float16. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8h_source.html#l00035">GpuIndexFlat.h:35</a></div></div>
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<div class="ttc" id="structfaiss_1_1gpu_1_1GpuIndexConfig_html_aab05a0aa7b42feae7df4e556a52ead57"><div class="ttname"><a href="structfaiss_1_1gpu_1_1GpuIndexConfig.html#aab05a0aa7b42feae7df4e556a52ead57">faiss::gpu::GpuIndexConfig::device</a></div><div class="ttdeci">int device</div><div class="ttdoc">GPU device on which the index is resident. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndex_8h_source.html#l00027">GpuIndex.h:27</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndex_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndex.html">faiss::gpu::GpuIndex</a></div><div class="ttdef"><b>Definition:</b> <a href="GpuIndex_8h_source.html#l00035">GpuIndex.h:35</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlatL2_html_aed22de4a439fa0b2f560e3c716a7c626"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlatL2.html#aed22de4a439fa0b2f560e3c716a7c626">faiss::gpu::GpuIndexFlatL2::GpuIndexFlatL2</a></div><div class="ttdeci">GpuIndexFlatL2(GpuResources *resources, faiss::IndexFlatL2 *index, GpuIndexFlatConfig config=GpuIndexFlatConfig())</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00549">GpuIndexFlat.cu:549</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuResources_html_a6c564198df6ba675920c993e2af34b8c"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuResources.html#a6c564198df6ba675920c993e2af34b8c">faiss::gpu::GpuResources::getDefaultStream</a></div><div class="ttdeci">virtual cudaStream_t getDefaultStream(int device)=0</div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html_ac2d0fc7199901a8e0788b58f0970b133"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html#ac2d0fc7199901a8e0788b58f0970b133">faiss::gpu::Tensor::narrowOutermost</a></div><div class="ttdeci">__host__ __device__ Tensor< T, Dim, InnerContig, IndexT, PtrTraits > narrowOutermost(IndexT start, IndexT size)</div><div class="ttdef"><b>Definition:</b> <a href="Tensor-inl_8cuh_source.html#l00625">Tensor-inl.cuh:625</a></div></div>
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<div class="ttc" id="structfaiss_1_1Index_html_a2a002388d2c081c2dbab8508dcefe73d"><div class="ttname"><a href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">faiss::Index::d</a></div><div class="ttdeci">int d</div><div class="ttdoc">vector dimension </div><div class="ttdef"><b>Definition:</b> <a href="Index_8h_source.html#l00064">Index.h:64</a></div></div>
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<div class="ttc" id="structfaiss_1_1gpu_1_1GpuIndexFlatConfig_html"><div class="ttname"><a href="structfaiss_1_1gpu_1_1GpuIndexFlatConfig.html">faiss::gpu::GpuIndexFlatConfig</a></div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8h_source.html#l00027">GpuIndexFlat.h:27</a></div></div>
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<div class="ttc" id="structfaiss_1_1gpu_1_1IntToLong_html"><div class="ttname"><a href="structfaiss_1_1gpu_1_1IntToLong.html">faiss::gpu::IntToLong</a></div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00200">GpuIndexFlat.cu:200</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_a7f1cdf03d3545a43fc91bb5cace3b6fd"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a7f1cdf03d3545a43fc91bb5cace3b6fd">faiss::gpu::GpuIndexFlat::reconstruct</a></div><div class="ttdeci">void reconstruct(faiss::Index::idx_t key, float *out) const override</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00491">GpuIndexFlat.cu:491</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndex_html_a67750633faa35677ee505a1e61cfe142"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndex.html#a67750633faa35677ee505a1e61cfe142">faiss::gpu::GpuIndex::device_</a></div><div class="ttdeci">const int device_</div><div class="ttdoc">The GPU device we are resident on. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndex_8h_source.html#l00094">GpuIndex.h:94</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlatIP_html_af70d0fe80cf3bf16ffffd8b16ed64f08"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#af70d0fe80cf3bf16ffffd8b16ed64f08">faiss::gpu::GpuIndexFlatIP::copyTo</a></div><div class="ttdeci">void copyTo(faiss::IndexFlatIP *index)</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00593">GpuIndexFlat.cu:593</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlatIP_html_a5f8c6e1a31cae06f6a5bcd1828307304"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#a5f8c6e1a31cae06f6a5bcd1828307304">faiss::gpu::GpuIndexFlatIP::GpuIndexFlatIP</a></div><div class="ttdeci">GpuIndexFlatIP(GpuResources *resources, faiss::IndexFlatIP *index, GpuIndexFlatConfig config=GpuIndexFlatConfig())</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00575">GpuIndexFlat.cu:575</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndex_html_a17b82a8a11783da6eb1b07c9aab98c36"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndex.html#a17b82a8a11783da6eb1b07c9aab98c36">faiss::gpu::GpuIndex::resources_</a></div><div class="ttdeci">GpuResources * resources_</div><div class="ttdoc">Manages streans, cuBLAS handles and scratch memory for devices. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndex_8h_source.html#l00091">GpuIndex.h:91</a></div></div>
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<div class="ttc" id="structfaiss_1_1Index_html_a040c6aed1f224f3ea7bf58eebc0c31a4"><div class="ttname"><a href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">faiss::Index::idx_t</a></div><div class="ttdeci">long idx_t</div><div class="ttdoc">all indices are this type </div><div class="ttdef"><b>Definition:</b> <a href="Index_8h_source.html#l00062">Index.h:62</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1FlatIndex_html_a7a06b678b97e3732939f6a4fb5106ef6"><div class="ttname"><a href="classfaiss_1_1gpu_1_1FlatIndex.html#a7a06b678b97e3732939f6a4fb5106ef6">faiss::gpu::FlatIndex::reserve</a></div><div class="ttdeci">void reserve(size_t numVecs, cudaStream_t stream)</div><div class="ttdoc">Reserve storage that can contain at least this many vectors. </div><div class="ttdef"><b>Definition:</b> <a href="FlatIndex_8cu_source.html#l00068">FlatIndex.cu:68</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1FlatIndex_html_ab91c9ddf7dd258620f424619cb029e22"><div class="ttname"><a href="classfaiss_1_1gpu_1_1FlatIndex.html#ab91c9ddf7dd258620f424619cb029e22">faiss::gpu::FlatIndex::add</a></div><div class="ttdeci">void add(const float *data, int numVecs, cudaStream_t stream)</div><div class="ttdef"><b>Definition:</b> <a href="FlatIndex_8cu_source.html#l00195">FlatIndex.cu:195</a></div></div>
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<div class="ttc" id="structfaiss_1_1Index_html_a6970683faa021b7a6f1a0865c0d4eccd"><div class="ttname"><a href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">faiss::Index::ntotal</a></div><div class="ttdeci">idx_t ntotal</div><div class="ttdoc">total nb of indexed vectors </div><div class="ttdef"><b>Definition:</b> <a href="Index_8h_source.html#l00065">Index.h:65</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndex_html_af576341f6996b0e80e26b9748db51eb7"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndex.html#af576341f6996b0e80e26b9748db51eb7">faiss::gpu::GpuIndex::add</a></div><div class="ttdeci">void add(faiss::Index::idx_t, const float *x) override</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndex_8cu_source.html#l00061">GpuIndex.cu:61</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_abb964875e0893de1d8334ca5ad0f62dc"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#abb964875e0893de1d8334ca5ad0f62dc">faiss::gpu::GpuIndexFlat::copyFrom</a></div><div class="ttdeci">void copyFrom(const faiss::IndexFlat *index)</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00087">GpuIndexFlat.cu:87</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1Tensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1Tensor.html">faiss::gpu::Tensor</a></div><div class="ttdoc">Our tensor type. </div><div class="ttdef"><b>Definition:</b> <a href="Tensor_8cuh_source.html#l00030">Tensor.cuh:30</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1DeviceScope_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1DeviceScope.html">faiss::gpu::DeviceScope</a></div><div class="ttdef"><b>Definition:</b> <a href="DeviceUtils_8h_source.html#l00065">DeviceUtils.h:65</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndex_html_af304169eac7781b573f76d545f37b7d9"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndex.html#af304169eac7781b573f76d545f37b7d9">faiss::gpu::GpuIndex::memorySpace_</a></div><div class="ttdeci">const MemorySpace memorySpace_</div><div class="ttdoc">The memory space of our primary storage on the GPU. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndex_8h_source.html#l00097">GpuIndex.h:97</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_aad665a7b5888b4aafd47ae0f8d0e6c40"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#aad665a7b5888b4aafd47ae0f8d0e6c40">faiss::gpu::GpuIndexFlat::minPagedSize_</a></div><div class="ttdeci">size_t minPagedSize_</div><div class="ttdoc">Size above which we page copies from the CPU to GPU. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8h_source.html#l00160">GpuIndexFlat.h:160</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_a9efdc92bf03d2d6820fb989cf77e8067"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a9efdc92bf03d2d6820fb989cf77e8067">faiss::gpu::GpuIndexFlat::config_</a></div><div class="ttdeci">const GpuIndexFlatConfig config_</div><div class="ttdoc">Our config object. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8h_source.html#l00157">GpuIndexFlat.h:157</a></div></div>
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<div class="ttc" id="structfaiss_1_1Index_html_a8e18f641854b2bde83ecff0a2f9a6f4e"><div class="ttname"><a href="structfaiss_1_1Index.html#a8e18f641854b2bde83ecff0a2f9a6f4e">faiss::Index::metric_type</a></div><div class="ttdeci">MetricType metric_type</div><div class="ttdoc">type of metric this index uses for search </div><div class="ttdef"><b>Definition:</b> <a href="Index_8h_source.html#l00072">Index.h:72</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_a35d31b6b5ea89629b369655fd03bd505"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a35d31b6b5ea89629b369655fd03bd505">faiss::gpu::GpuIndexFlat::add</a></div><div class="ttdeci">void add(faiss::Index::idx_t, const float *x) override</div><div class="ttdoc">Overrides to avoid excessive copies. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00162">GpuIndexFlat.cu:162</a></div></div>
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<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>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html">faiss::gpu::GpuIndexFlat</a></div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8h_source.html#l00054">GpuIndexFlat.h:54</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_a67161796f274a7171a67c36bdf1ef1db"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a67161796f274a7171a67c36bdf1ef1db">faiss::gpu::GpuIndexFlat::reset</a></div><div class="ttdeci">void reset() override</div><div class="ttdoc">Clears all vectors from this index. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00148">GpuIndexFlat.cu:148</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlatIP_html_aa181b1778a8dca81ac5cf6cd6a3d5f1d"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlatIP.html#aa181b1778a8dca81ac5cf6cd6a3d5f1d">faiss::gpu::GpuIndexFlatIP::copyFrom</a></div><div class="ttdeci">void copyFrom(faiss::IndexFlatIP *index)</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00588">GpuIndexFlat.cu:588</a></div></div>
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<div class="ttc" id="structfaiss_1_1Index_html_a6e92732617c4dbe364e7678dd8773a7f"><div class="ttname"><a href="structfaiss_1_1Index.html#a6e92732617c4dbe364e7678dd8773a7f">faiss::Index::is_trained</a></div><div class="ttdeci">bool is_trained</div><div class="ttdoc">set if the Index does not require training, or if training is done already </div><div class="ttdef"><b>Definition:</b> <a href="Index_8h_source.html#l00069">Index.h:69</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1FlatIndex_html_ae06cb2ffd46659b6639b97297546096e"><div class="ttname"><a href="classfaiss_1_1gpu_1_1FlatIndex.html#ae06cb2ffd46659b6639b97297546096e">faiss::gpu::FlatIndex::reset</a></div><div class="ttdeci">void reset()</div><div class="ttdoc">Free all storage. </div><div class="ttdef"><b>Definition:</b> <a href="FlatIndex_8cu_source.html#l00269">FlatIndex.cu:269</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1CudaEvent_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1CudaEvent.html">faiss::gpu::CudaEvent</a></div><div class="ttdef"><b>Definition:</b> <a href="DeviceUtils_8h_source.html#l00087">DeviceUtils.h:87</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_ac0f0301829363f920e619f673a4d97f3"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ac0f0301829363f920e619f673a4d97f3">faiss::gpu::GpuIndexFlat::search</a></div><div class="ttdeci">void search(faiss::Index::idx_t n, const float *x, faiss::Index::idx_t k, float *distances, faiss::Index::idx_t *labels) const override</div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00205">GpuIndexFlat.cu:205</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1DeviceTensor_html"><div class="ttname"><a href="classfaiss_1_1gpu_1_1DeviceTensor.html">faiss::gpu::DeviceTensor</a></div><div class="ttdef"><b>Definition:</b> <a href="DeviceTensor_8cuh_source.html#l00024">DeviceTensor.cuh:24</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexFlat_html_a9001de47890fe5d2eced9551d3613d47"><div class="ttname"><a href="structfaiss_1_1IndexFlat.html#a9001de47890fe5d2eced9551d3613d47">faiss::IndexFlat::xb</a></div><div class="ttdeci">std::vector< float > xb</div><div class="ttdoc">database vectors, size ntotal * d </div><div class="ttdef"><b>Definition:</b> <a href="IndexFlat_8h_source.html#l00025">IndexFlat.h:25</a></div></div>
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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_a0e74fad76628ddfb5ae3dc1d1c69f7e8"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#a0e74fad76628ddfb5ae3dc1d1c69f7e8">faiss::gpu::GpuIndexFlat::train</a></div><div class="ttdeci">void train(Index::idx_t n, const float *x) override</div><div class="ttdoc">This index is not trained, so this does nothing. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8cu_source.html#l00157">GpuIndexFlat.cu:157</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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<div class="ttc" id="classfaiss_1_1gpu_1_1GpuIndexFlat_html_ae393840fc80403369452c25c9155e067"><div class="ttname"><a href="classfaiss_1_1gpu_1_1GpuIndexFlat.html#ae393840fc80403369452c25c9155e067">faiss::gpu::GpuIndexFlat::data_</a></div><div class="ttdeci">FlatIndex * data_</div><div class="ttdoc">Holds our GPU data containing the list of vectors. </div><div class="ttdef"><b>Definition:</b> <a href="GpuIndexFlat_8h_source.html#l00163">GpuIndexFlat.h:163</a></div></div>
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